From 20c9760894567e32ca94967defbfda890a9d70bf Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 6 Jan 2016 12:41:18 -0800 Subject: [PATCH 01/64] Minor formatting revisions and edits in preparation to identify volunteers to finish. --- VersionDate.tex | 2 +- authorlist.tex | 20 +++---- exgal_roadmap.pdf | Bin 230063 -> 265377 bytes exgal_roadmap.tex | 2 +- .../black_holes/black_holes.tex | 2 +- .../informatics/informatics.tex | 2 +- science_background/lss/lss.tex | 2 +- .../strong_lensing/strong_lensing.tex | 2 +- .../weak_lensing/weak_lensing.tex | 2 +- task_lists/galaxies/galaxies.tex | 51 ++++++------------ task_lists/informatics/informatics.tex | 2 +- task_lists/lss/lss.tex | 2 +- task_lists/strong_lensing/strong_lensing.tex | 2 +- task_lists/weak_lensing/weak_lensing.tex | 2 +- 14 files changed, 36 insertions(+), 57 deletions(-) diff --git a/VersionDate.tex b/VersionDate.tex index b9e47a3..616cf4d 100644 --- a/VersionDate.tex +++ b/VersionDate.tex @@ -1,4 +1,4 @@ \begin{center} Version -March 24, 2015 +January 6, 2016 \end{center} diff --git a/authorlist.tex b/authorlist.tex index 05cdc43..6d07089 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -1,27 +1,27 @@ -Borne, Kirk$^{1}$ -Brandt, William$^{2}$ +Borne, Kirk$^{1}$, +Brandt, William$^{2}$, Connolly, Andrew$^{3}$, -Cooper, Michael$^{4}$ -Ferguson, Henry C.$^{5}$ +Cooper, Michael$^{4}$, +Ferguson, Henry C.$^{5}$, Gawiser, Eric$^{6}$, Ho, Shirley$^{7}$, Ivezi\'{c}, \v{Z}eljko$^{3}$, -Juric, Mario$^{3}$ +Juric, Mario$^{3}$, Kahn, Steven M.$^{28, 29}$, Lupton, Robert$^{10}$, Mandelbaum, Rachel$^{7}$, Marshall, Philip. J$^{8,9}$, Newman, Jeffrey A.$^{11}$, -Ptak, Andrew$^{12}$ -Richards, Gordon$^{13}$ -Robertson, Brant$^{14}$ +Ptak, Andrew$^{12}$, +Richards, Gordon$^{13}$, +Robertson, Brant$^{14}$, Strauss, Michael A.$^{10}$, Tyson, J. Anthony$^{15}$, ... And Many Others, TBD.... \vspace*{5mm} -\begin{table}[htdp] +\begin{table}[htp] \centering {\renewcommand{\arraystretch}{0.8} \begin{tabular}{p{10cm}} @@ -39,7 +39,7 @@ $^{11}$University of Pittsburgh\\ $^{12}$The Johns Hopkins University\\ $^{13}$Drexel University\\ -$^{14}$University of Arizona\\ +$^{14}$University of California, Santa Cruz\\ $^{14}$University of California, Davis\\ \end{tabular} } diff --git a/exgal_roadmap.pdf b/exgal_roadmap.pdf index c44b4bee7c4944410b4a8d65f57b09991e56b23a..9fae43262cc381541fb0f786fe18506177c7a978 100644 GIT binary patch delta 206150 zcmZs>V~j3Pv!>m)ZQHhO+qT`kyZdR|wr$(SZrir8+xXsdGV{$ObJnj_N&Q&KN~-F< z?y3((D9l8nBv%rXpl4=ahasO|9$kmw1qP-9 zv}($`ZgC*>ern!J&8Sg91%R#R9mcOKA1<3#-^gVX7(u5gEtNoo;PLkN!J@QKgV#wb z{wab2{`A0fe5H48iE?uD2{7~`m__vW&A*Re8Ua@mNIB|(_Lfl{amA4D6iWHy8lFm>`V_SIR?N{3_$i3s zn&NhtEyb4c#!yc26ecHrO3;Prduj7-4u=?O{yFi~N7LB_Hxi3tx+zXbSCWD{si2vz zq9ULS@{qloDpfWFRpJ(=lmFCmBU?3-5xZs}B)Fj;dgRsv>8UTJ5qV%HBf8?ZwL?4q 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zu)mr?bPU|K`M8;J9@s)W=Z4{1Qq3LQ7aSvH`Elddk|RU~(fL~(uzRn%YKO23?B z9C9(pG11w8tXM%}EV!$whBzSEli+H#cQlV{5MfW>`Q~I{g=JM5u8Q$lQ*@y?TkVE! zmS6owk+uC zQ+$>?sh1VX8M`F4YGPc_<<6mItH73DkjLhasml|fbXtzU^2i@h)ka&d@)Q(14zB1F zE{-V|NJu{ia#6M1wby#|oJF$*j+|?=XRxHb?K9DPLK~d{ zIceFMw{bHr=(*iOCdV?H5kqWlms^oO-AP2yW4VgY8`BuX8&Q5%B4cmP;Kn@6H&)a@ zBuzzBD9vX#s)2A>n!HFoeM*;3+EYmWU_c2_f6tWZ?mso!SoNRd}0M{i*8mIx=4M7ta76CCLh=R%;ie${sB-)lWmjcJ`t`h z+pJ!IBi#GLp3*M1!VO5YmHhV_lkSE!O_f>X!&>j;tQqWQODN8GUQ^k>mpHYlJoy&$ zfrF*h3c@h*_|W$90QVT}>daZ_==bL;$tI+4bahl{22LwUs=_W7nE&(N3;Z)ncO~Am zF$QT^)pcr8mJ9Igvoc&O^*!G+Gc0pFbkSH-R5&*o4C;5cHXR{;Bgku>J9jNa%6LIx}AXZvmGW z5YGHiKT-+0*D>)Q!MKzt5h8{pTuJmhro^;28YBnMl5x{Y$;v@wsRaZy^fjsf0ZvG7 A6aWAK diff --git a/exgal_roadmap.tex b/exgal_roadmap.tex index 548fe1a..ea74b92 100644 --- a/exgal_roadmap.tex +++ b/exgal_roadmap.tex @@ -59,7 +59,7 @@ {\Huge\bfseries\scshape Large Synoptic Survey Telescope} \linebreak \linebreak -{\Huge\bfseries\scshape Galaxies, Dark-Matter and Black Holes: Extragalactic Roadmap} +{\Huge\bfseries\scshape Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} \vspace*{20mm} diff --git a/science_background/black_holes/black_holes.tex b/science_background/black_holes/black_holes.tex index 3b58cd0..b5e2a11 100644 --- a/science_background/black_holes/black_holes.tex +++ b/science_background/black_holes/black_holes.tex @@ -4,7 +4,7 @@ % Section: black_holes % First draft by -\section{XXX}\label{sec:sci:agn:XXX} +\section{Science Background: AGN}\label{sec:sci:agn:bkgnd} diff --git a/science_background/informatics/informatics.tex b/science_background/informatics/informatics.tex index bb40600..5493eeb 100644 --- a/science_background/informatics/informatics.tex +++ b/science_background/informatics/informatics.tex @@ -4,6 +4,6 @@ % Section: informatics % First draft by -\section{XXX}\label{sec:sci:ai:XXX} +\section{Science Background: Astroinformatics}\label{sec:sci:ai:bkgnd} diff --git a/science_background/lss/lss.tex b/science_background/lss/lss.tex index 2a8e22a..8e445e4 100644 --- a/science_background/lss/lss.tex +++ b/science_background/lss/lss.tex @@ -4,6 +4,6 @@ % Section: lss % First draft by -\section{XXX}\label{sec:sci:lss:XXX} +\section{Science Background: Large Scale Structure}\label{sec:sci:lss:bkgnd} diff --git a/science_background/strong_lensing/strong_lensing.tex b/science_background/strong_lensing/strong_lensing.tex index 5801ef7..8b78b7a 100644 --- a/science_background/strong_lensing/strong_lensing.tex +++ b/science_background/strong_lensing/strong_lensing.tex @@ -4,6 +4,6 @@ % Section: strong_lensing % First draft by -\section{XXX}\label{sec:sci:sl:XXX} +\section{Science Background: Strong Lensing}\label{sec:sci:sl:bkgnd} diff --git a/science_background/weak_lensing/weak_lensing.tex b/science_background/weak_lensing/weak_lensing.tex index 2000d7a..8ce16ed 100644 --- a/science_background/weak_lensing/weak_lensing.tex +++ b/science_background/weak_lensing/weak_lensing.tex @@ -4,7 +4,7 @@ % Section: weak_lensing % First draft by -\section{XXX}\label{sec:sci:wl:XXX} +\section{Science Background: Weak Lensing}\label{sec:sci:wl:bkgnd} diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 0969f2a..62bd5a0 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -7,7 +7,7 @@ \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} The LSST design, and to a certain extent the design of the data-management system, is optimized to carry out the core science mission. For measurements -of dark-energy, that generally means treating galaxies as "tracer particles" -- +of dark-energy, that generally means treating galaxies as ``tracer particles'' -- using statistical measures of ellipticity and position provide statistical constraints on large-scale structure and cosmic geometry. While many of the DESC tasks are directly relevant to studying galaxy evolution, they are @@ -23,7 +23,7 @@ \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} LSST survey design and DM optimization, but which will ensure good support for LSST galaxy studies. -\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:precursor} +\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} \begin{tasklist}{T} \tasktitle{Techniques for finding low-surface-brightness features or galaxies} @@ -340,23 +340,15 @@ \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec: \begin{tasklist}{T} \tasktitle{Redshift surveys in the Deep Drilling fields} \begin{task} -\label{task:gal:XXX} +\label{task:gal:redshift_surveys_dd_fields} \motivation{} \activities{} \deliverables{} \end{task} -\tasktitle{Spitzer observations of Deep Drilling fields} +\tasktitle{Ancillary Data in Deep Drilling fields} \begin{task} -\label{task:gal:XXX} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{VLA observations of Deep Drilling fields} -\begin{task} -\label{task:gal:XXX} +\label{task:gal:ancillary_data_dd_fields} \motivation{} \activities{} \deliverables{} @@ -365,7 +357,7 @@ \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec: \tasktitle{Photometric redshift training and calibration} % Emphasize differences in requirements relative to DE \begin{task} -\label{task:gal:XXX} +\label{task:gal:photz_calibration} \motivation{} \activities{} \deliverables{} @@ -373,7 +365,7 @@ \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec: \tasktitle{Joint use of spectroscopic and photometric redshifts} \begin{task} -\label{task:gal:XXX} +\label{task:gal:spec_plus_phot_redshifts} \motivation{} \activities{} \deliverables{} @@ -390,7 +382,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation % Stellar halos % Vary the galaxy-evolution model \begin{task} -\label{task:gal:XXX} +\label{task:gal:image_simulations} \motivation{} \activities{} \deliverables{} @@ -401,7 +393,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation % massive early galaxies % extremely supermassive black holdes \begin{task} -\label{task:gal:XXX} +\label{task:gal:rare_objects} \motivation{} \activities{} \deliverables{} @@ -410,7 +402,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \tasktitle{Cosmic Variance estimators} % Develop simple tools...encourage their use \begin{task} -\label{task:gal:XXX} +\label{task:gal:cv_estimators} \motivation{} \activities{} \deliverables{} @@ -418,7 +410,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \tasktitle{Nearby dwarfs: surface brightness fluctuations} \begin{task} -\label{task:gal:XXX} +\label{task:gal:dwarf_sb_fluctuations} \motivation{} \activities{} \deliverables{} @@ -426,20 +418,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \tasktitle{Testing group and void finders} \begin{task} -\label{task:gal:XXX} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\end{tasklist} - -\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} - -\begin{tasklist}{T} -\tasktitle{Data structures to characterize survey biases and completeness} -\begin{task} -\label{task:gal:XXX} +\label{task:gal:group_finders} \motivation{} \activities{} \deliverables{} @@ -452,7 +431,7 @@ \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} \begin{tasklist}{T} \tasktitle{Data structures to characterize survey biases and completeness} \begin{task} -\label{task:gal:XXX} +\label{task:gal:data_structures} \motivation{} \activities{} \deliverables{} @@ -464,7 +443,7 @@ \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} % nearby dwarf candidates % morphologically disturbed close pairs \begin{task} -\label{task:gal:XXX} +\label{task:gal:queries} \motivation{} \activities{} \deliverables{} @@ -472,7 +451,7 @@ \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} \tasktitle{Compact representations of likelihood functions} \begin{task} -\label{task:gal:XXX} +\label{task:gal:likelihoods} \motivation{} \activities{} \end{task} diff --git a/task_lists/informatics/informatics.tex b/task_lists/informatics/informatics.tex index 2cbb26f..feae3e0 100644 --- a/task_lists/informatics/informatics.tex +++ b/task_lists/informatics/informatics.tex @@ -4,5 +4,5 @@ % Section: informatics % First draft by -\section{XXX}\label{sec:tasks:ai:XXX} +\section{Astroinformatics Task Lists}\label{sec:tasks:ai:intro} diff --git a/task_lists/lss/lss.tex b/task_lists/lss/lss.tex index d224f26..a6eb3b3 100644 --- a/task_lists/lss/lss.tex +++ b/task_lists/lss/lss.tex @@ -4,5 +4,5 @@ % Section: lss % First draft by -\section{XXX}\label{sec:tasks:lss:XXX} +\section{Large Scale Structure Task Lists}\label{sec:tasks:lss:into} diff --git a/task_lists/strong_lensing/strong_lensing.tex b/task_lists/strong_lensing/strong_lensing.tex index b947590..32c2ff9 100644 --- a/task_lists/strong_lensing/strong_lensing.tex +++ b/task_lists/strong_lensing/strong_lensing.tex @@ -4,5 +4,5 @@ % Section: strong_lensing % First draft by -\section{XXX}\label{sec:tasks:sl:XXX} +\section{Strong Lensing Task Lists}\label{sec:tasks:sl:intro} diff --git a/task_lists/weak_lensing/weak_lensing.tex b/task_lists/weak_lensing/weak_lensing.tex index 12626d7..f8afe09 100644 --- a/task_lists/weak_lensing/weak_lensing.tex +++ b/task_lists/weak_lensing/weak_lensing.tex @@ -4,5 +4,5 @@ % Section: weak_lensing % First draft by -\section{XXX}\label{sec:tasks:wl:XXX} +\section{Weak Lensing Task Lists}\label{sec:tasks:wl:intro} From 652309db6c8e4c8a23bb2fb00ef54aa3b747ee04 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 20 Dec 2016 16:13:36 -0800 Subject: [PATCH 02/64] Adding PDF and galaxies.tex. Will probably need to rework all the task list subsections. 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These are the most urgent. Also included are activities that can be reasonably independent of the LSST survey design and DM optimization, but which will ensure good support for -LSST galaxy studies. +LSST galaxy studies. + +\begin{tasklist}{T} +\tasktitle{Example Task List} +\begin{task} +\label{task:label_for_this_task} +\motivation{Put Science Motivation Here} +\activities{Described Activities Here} +\deliverables{ + Deliverables over the next several years from the activities described above include the following: + \begin{enumerate} + \item a deliverable + \item another deliverable + \end{enumerate} +} +\end{task} +\end{tasklist} \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} From 8652da5cb756bc08311b035cc424f66c9353c5ef Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 20 Dec 2016 16:54:53 -0800 Subject: [PATCH 03/64] Moving to Legrange Orange Book format. --- VersionDate.tex | 2 +- authorlist.tex | 45 +-- exgal_roadmap.pdf | Bin 266060 -> 187611 bytes exgal_roadmap.tex | 212 ++++++++------ exgal_roadmap.tmp.tex | 123 ++++++++ old/authorlist.tex | 46 +++ old/exgal_roadmap.tex | 123 ++++++++ structure.tex | 641 ++++++++++++++++++++++++++++++++++++++++++ 8 files changed, 1073 insertions(+), 119 deletions(-) create mode 100644 exgal_roadmap.tmp.tex create mode 100644 old/authorlist.tex create mode 100644 old/exgal_roadmap.tex create mode 100644 structure.tex diff --git a/VersionDate.tex b/VersionDate.tex index 616cf4d..590c876 100644 --- a/VersionDate.tex +++ b/VersionDate.tex @@ -1,4 +1,4 @@ \begin{center} Version -January 6, 2016 +December 20, 2016 \end{center} diff --git a/authorlist.tex b/authorlist.tex index 6d07089..26ace6f 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -1,23 +1,4 @@ -Borne, Kirk$^{1}$, -Brandt, William$^{2}$, -Connolly, Andrew$^{3}$, -Cooper, Michael$^{4}$, -Ferguson, Henry C.$^{5}$, -Gawiser, Eric$^{6}$, -Ho, Shirley$^{7}$, -Ivezi\'{c}, \v{Z}eljko$^{3}$, -Juric, Mario$^{3}$, -Kahn, Steven M.$^{28, 29}$, -Lupton, Robert$^{10}$, -Mandelbaum, Rachel$^{7}$, -Marshall, Philip. J$^{8,9}$, -Newman, Jeffrey A.$^{11}$, -Ptak, Andrew$^{12}$, -Richards, Gordon$^{13}$, -Robertson, Brant$^{14}$, -Strauss, Michael A.$^{10}$, -Tyson, J. Anthony$^{15}$, -... And Many Others, TBD.... +Robertson, Brant$^{1}$, Banerji, M.$^{2}$, Cooper, Michael$^{3}$, Davies, R.$^{4}$, Ferguson, Henry C.$^{5}$, Kaviraj, S.$^{6}$, Lintott, C.$^{4}$, Lotz, J.$^{5}$, Newman, J.$^{7}$, Norman, D.$^{8}$, Padilla, N.$^{9}$, Schmidt, S.$^{10}$, Verma, A.$^{4}$, Working Group Participants, Collaboration Members \vspace*{5mm} @@ -25,22 +6,16 @@ \centering {\renewcommand{\arraystretch}{0.8} \begin{tabular}{p{10cm}} -%\begin{tabular}{p{10cm}p{10cm}} -$^{1}$George Mason University\\ -$^{2}$Penn State University\\ -$^{3}$University of Washington\\ -$^{4}$University of California, Irvine\\ +$^{1}$University of California, Santa Cruz\\ +$^{2}$Cambridge University\\ +$^{3}$University of California, Irvine\\ +$^{4}$Oxford University\\ $^{5}$Space Telescope Science Institute\\ -$^{6}$Rutgers University\\ -$^{7}$Carnegie Mellon University\\ -$^{8}$SLAC National Accelerator Laboratory\\ -$^{9}$Stanford University\\ -$^{10}$Princeton University\\ -$^{11}$University of Pittsburgh\\ -$^{12}$The Johns Hopkins University\\ -$^{13}$Drexel University\\ -$^{14}$University of California, Santa Cruz\\ -$^{14}$University of California, Davis\\ +$^{6}$University of Hertfordshire\\ +$^{7}$University of Pittsburgh\\ +$^{8}$National Optical Astronomical Observatory\\ +$^{9}$Pontifica Universidad Catolica de Chile\\ +$^{10}$University of California, Davis\\ \end{tabular} } \end{table} diff --git a/exgal_roadmap.pdf b/exgal_roadmap.pdf index dbaa388d5ae26aded80892050b7b7cc6a96a3d1b..22c8d778300e23b49b0a09ffa84d3263f041164d 100644 GIT binary patch literal 187611 zcma&MV~{Y-vMoHeZQHhO+qP}nwr$(CZO=So>luFUKIeQlZp7IUch`@KitgyFj?C3- zWo8$tf`}L`BONOg>B7qB1{4PY1A)Df6%-E-6upe8owm%nY@*za(;US(>-3rnO7 zE8BPp~&F(pjv_!-S1q__8qGo$KATCjJmeoIx2||OY z?etik?1W~26ySSD1USKVQeRMCC}?1`nNizbJ##@VnPwpD;_#otKX0vWjlUA%$OAj7 z0L5Yq3vFnLT=#l3#sUI(gV0 z(3L{8G4+mhz;YpKp4(27BNBiW&DwsWISo}WRNqDcWgQ*0JH_v z?mh+F69-xXgsu%Hi8~@BUX;$N*#So0b>j>a{w%bahAe{5cXj|m6#Q~O0JJI!|3d~V 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-% PURPOSE: -% Master latex file for the LSST desc_white_paper -% -% COMMENTS: -% - Includes Title page, Preface and Introduction, then \includes -% all technical material provided by science collaborations. -% - Use make to process, calls pdflatex -% - checkbook.csh can be used to check that all inputs are present -% -% INPUTS: -% Many and varied, via the \include command for bibliographic reasons -% grep '\\include' desc_white_paper.tex -% -% OPTIONAL INPUTS: -% final option to make final version -% -% OUTPUTS: -% desc_white_paper.pdf -% -% DEPENDENCIES: -% - whitepaper.sty, SciBook.bst -% - komascript package, providing the scrbook.cls -% http://www.ctan.org/tex-archive/macros/latex/contrib/koma-script/ -% -% EXAMPLES: -% make produces desc_white_paper.pdf -% -% -%- -% ============================================================================ - -%% LaTeX2e - -\documentclass[11pt,headsepline,cleardoubleempty,twoside,openright]{scrbook} -% 11pt font -% Draw a line under the header -% Don't draw a line or print page numbers when a page is empty -% Pages are two-sided - so margins alternate -% Chapters start on the righthand side of the page - -\usepackage{whitepaper} - -\hyphenation{zero-point zero-points} - -% ============================================================================ -\begin{document} -\begin{titlepage} -\begin{center} +%--------------------------------------------------------------------------------------- +% PACKAGES AND OTHER DOCUMENT CONFIGURATIONS +%---------------------------------------------------------------------------------------- + +\documentclass[11pt,fleqn]{book} % Default font size and left-justified equations +\usepackage{etoolbox} +\makeatletter +\patchcmd{\chapter}{\if@openright\cleardoublepage\else\clearpage\fi}{}{}{} +\makeatother + +\input{structure} % Insert the commands.tex file which contains the majority of the structure behind the template +% media9 is for embedding 3D objects, movies, and animations +%\usepackage{media9} + +\usepackage{booktabs} +\usepackage{pdflscape} +\newcommand{\ra}[1]{\renewcommand{\arraystretch}{#1}} +\usepackage{float} -\vspace*{20mm} +\begin{document} + +%---------------------------------------------------------------------------------------- +% TITLE PAGE +%---------------------------------------------------------------------------------------- + +\begingroup +%\thispagestyle{empty} +%\begin{tikzpicture}[remember picture,overlay] +%\coordinate [below=11cm] (midpoint) at (current page.north); +%\node at (current page.north west) +%{\begin{tikzpicture}[remember picture,overlay] +%\node[anchor=north west,inner sep=0pt] at (0,0) {\includegraphics[]{cover_page.pdf}}; % Background image +%\draw[anchor=north] (midpoint) node [fill=ocre!30!white,fill opacity=0.6,text opacity=1,inner sep=1cm]{\centering\bfseries\sffamily\parbox[c][][t]{\paperwidth}{\centering\color{blue}{\fontsize{70}{80}\selectfont Galaxies}\\[15pt] % Book title +%{\Huge a hands-on introduction}\\[60pt] % Subtitle +%{\Huge Andrey Kravtsov}}}; % Author name +%\end{tikzpicture}}; +%\end{tikzpicture} {\Huge\bfseries\scshape Large Synoptic Survey Telescope} \linebreak \linebreak {\Huge\bfseries\scshape Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} +\input{authorlist} +\input{VersionDate} +\vfill +\endgroup -\vspace*{20mm} +%---------------------------------------------------------------------------------------- +% COPYRIGHT PAGE +%---------------------------------------------------------------------------------------- +\newpage +\thispagestyle{empty} +\noindent +\noindent +\noindent +\\ +\noindent -\input{authorlist} +Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}). +%\newpage -%\vspace*{\stretch{2}}i +%~\vfill +%\thispagestyle{empty} -%Version taken out for published draft -%%% 2012/07/22 - Put in automatic Version Date LatEx for ease of editing -%%% Now the Version and Date of the SVN version used to compile will -%%% be on the front page of the document. -%%% To generate a more formal version one may wish to change the following back to the hardcoded version right below the following line. -\vspace*{5mm} -\input{VersionDate} +%\noindent Copyright \copyright\ 2016 Andrey Kravtsov\\ % Copyright notice + +%\noindent \textsc{KICP Press}\\ % Publisher + +%\noindent \textsc{http://a-kravtsov.github.io/a304s16/}\\ % URL + +%\noindent Licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License (the ``License''). You may not use this file except in compliance with the License. You may obtain a copy of the License at \url{http://creativecommons.org/licenses/by-nc/3.0}. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \textsc{``as is'' basis, without warranties or conditions of any kind}, either express or implied. See the License for the specific language governing permissions and limitations under the License.\\ % License information + +%\noindent \textit{First printing, April 2016} % Printing/edition date -\end{center} -\end{titlepage} +%---------------------------------------------------------------------------------------- +% Table of Contents +%---------------------------------------------------------------------------------------- + +\usechapterimagefalse % If you don't want to include a chapter image, use this to toggle images off - it can be enabled later with \usechapterimagetrue + +\pagestyle{empty} % No headers \include{abstract} -% ---------------------------------------------------------------------------- -\tableofcontents -% ---------------------------------------------------------------------------- +%\chapterimage{simulation_background.png} % Table of contents heading image + +\pagestyle{empty} % No headers + +\tableofcontents % Print the table of contents itself + +%\cleardoublepage % Forces the first chapter to start on an odd page so it's on the right + +\nopagebreak[4] + +\pagestyle{fancy} % Print headers again -% NOTE FROM JAN: The extra white space after each section is due to -% using \Chapter for them all, following the Science Book. +%---------------------------------------------------------------------------------------- +% Chapters +%---------------------------------------------------------------------------------------- + + +% if it ever gets so big as to require Parts +%\part{Part One} \include{introduction/introduction} @@ -99,25 +116,54 @@ %\include{matrix/matrix} -% ---------------------------------------------------------------------------- -\bibliographystyle{SciBook} -\bibliography{references.bib} -% ---------------------------------------------------------------------------- +%\chapterimage{ch2_header.png} % Chapter heading image +%\include{galaxy_formation} -% \appendix +%\appendix +%\chapterimage{uvhudf.PNG} +%\include{cosmology_distances} +%\chapterimage{suppl_header.jpg} +%\include{supplementary} +%\chapterimage{python_xkcd2.PNG} +%\include{python} +%\chapterimage{sdss_data_banner.png} +%\include{data_access}%\appendix{Practical info on accessing various data sets} +%\chapterimage{banner_bookshelf.jpg} +%\printbibliography -% \setboolean{appendix}{true} -% \renewcommand\thechapter{\Alph{chapter}} -% \renewcommand{\chaptermark}[1]{\markboth{Appendix \thechapter: #1}{}} -% \renewcommand{\sectionmark}[1]{\markright{\thesection\ #1}{}} +%---------------------------------------------------------------------------------------- +% INDEX +%---------------------------------------------------------------------------------------- -% Appendix content: +%\cleardoublepage +%\phantomsection +%\setlength{\columnsep}{0.75cm} +%\addcontentsline{toc}{chapter}{\textcolor{ocre}{Index}} +%\printindex -%\include{stuff} +%---------------------------------------------------------------------------------------- \end{document} -% ============================================================================ +%------------------------------------------------ + +%\section{Figure}\index{Figure} +%\begin{figure}[h] +%\centering\includegraphics[scale=0.5]{blanton_moustakas_wordcloud.pdf} +%\caption{Figure caption} +%\end{figure} + + +\begin{figure}[ht] +\includemedia[ +label=LG, +width=0.5\linewidth,height=0.5\linewidth, +activate=pageopen, +3Dtoolbar, 3Dmenu, +3Dviews=dice.vws, +]{}{fig/LG3d.u3d} +\end{figure} +\end{document} diff --git a/exgal_roadmap.tmp.tex b/exgal_roadmap.tmp.tex new file mode 100644 index 0000000..ea74b92 --- /dev/null +++ b/exgal_roadmap.tmp.tex @@ -0,0 +1,123 @@ +% ====================================================================== +%+ +% NAME: +% desc_white_paper.tex +% +% PURPOSE: +% Master latex file for the LSST desc_white_paper +% +% COMMENTS: +% - Includes Title page, Preface and Introduction, then \includes +% all technical material provided by science collaborations. +% - Use make to process, calls pdflatex +% - checkbook.csh can be used to check that all inputs are present +% +% INPUTS: +% Many and varied, via the \include command for bibliographic reasons +% grep '\\include' desc_white_paper.tex +% +% OPTIONAL INPUTS: +% final option to make final version +% +% OUTPUTS: +% desc_white_paper.pdf +% +% DEPENDENCIES: +% - whitepaper.sty, SciBook.bst +% - komascript package, providing the scrbook.cls +% http://www.ctan.org/tex-archive/macros/latex/contrib/koma-script/ +% +% EXAMPLES: +% make produces desc_white_paper.pdf +% +% +%- +% ============================================================================ + +%% LaTeX2e + +\documentclass[11pt,headsepline,cleardoubleempty,twoside,openright]{scrbook} +% 11pt font +% Draw a line under the header +% Don't draw a line or print page numbers when a page is empty +% Pages are two-sided - so margins alternate +% Chapters start on the righthand side of the page + +\usepackage{whitepaper} + +\hyphenation{zero-point zero-points} + +% ============================================================================ + +\begin{document} + +\begin{titlepage} +\begin{center} + +\vspace*{20mm} + +{\Huge\bfseries\scshape Large Synoptic Survey Telescope} +\linebreak +\linebreak +{\Huge\bfseries\scshape Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} + +\vspace*{20mm} + +\input{authorlist} + +%\vspace*{\stretch{2}}i + +%Version taken out for published draft +%%% 2012/07/22 - Put in automatic Version Date LatEx for ease of editing +%%% Now the Version and Date of the SVN version used to compile will +%%% be on the front page of the document. +%%% To generate a more formal version one may wish to change the following back to the hardcoded version right below the following line. +\vspace*{5mm} +\input{VersionDate} + +\end{center} +\end{titlepage} + +\include{abstract} + +% ---------------------------------------------------------------------------- + +\tableofcontents + +% ---------------------------------------------------------------------------- + +% NOTE FROM JAN: The extra white space after each section is due to +% using \Chapter for them all, following the Science Book. + +\include{introduction/introduction} + +\include{science_background/science_background} + +\include{roadmap/roadmap} + +\include{task_lists/task_lists} + +%\include{matrix/matrix} + +% ---------------------------------------------------------------------------- + +\bibliographystyle{SciBook} +\bibliography{references.bib} + +% ---------------------------------------------------------------------------- + +% \appendix + +% \setboolean{appendix}{true} +% \renewcommand\thechapter{\Alph{chapter}} +% \renewcommand{\chaptermark}[1]{\markboth{Appendix \thechapter: #1}{}} +% \renewcommand{\sectionmark}[1]{\markright{\thesection\ #1}{}} + +% Appendix content: + +%\include{stuff} + +\end{document} + +% ============================================================================ + diff --git a/old/authorlist.tex b/old/authorlist.tex new file mode 100644 index 0000000..6d07089 --- /dev/null +++ b/old/authorlist.tex @@ -0,0 +1,46 @@ +Borne, Kirk$^{1}$, +Brandt, William$^{2}$, +Connolly, Andrew$^{3}$, +Cooper, Michael$^{4}$, +Ferguson, Henry C.$^{5}$, +Gawiser, Eric$^{6}$, +Ho, Shirley$^{7}$, +Ivezi\'{c}, \v{Z}eljko$^{3}$, +Juric, Mario$^{3}$, +Kahn, Steven M.$^{28, 29}$, +Lupton, Robert$^{10}$, +Mandelbaum, Rachel$^{7}$, +Marshall, Philip. J$^{8,9}$, +Newman, Jeffrey A.$^{11}$, +Ptak, Andrew$^{12}$, +Richards, Gordon$^{13}$, +Robertson, Brant$^{14}$, +Strauss, Michael A.$^{10}$, +Tyson, J. Anthony$^{15}$, +... And Many Others, TBD.... + +\vspace*{5mm} + +\begin{table}[htp] +\centering +{\renewcommand{\arraystretch}{0.8} +\begin{tabular}{p{10cm}} +%\begin{tabular}{p{10cm}p{10cm}} +$^{1}$George Mason University\\ +$^{2}$Penn State University\\ +$^{3}$University of Washington\\ +$^{4}$University of California, Irvine\\ +$^{5}$Space Telescope Science Institute\\ +$^{6}$Rutgers University\\ +$^{7}$Carnegie Mellon University\\ +$^{8}$SLAC National Accelerator Laboratory\\ +$^{9}$Stanford University\\ +$^{10}$Princeton University\\ +$^{11}$University of Pittsburgh\\ +$^{12}$The Johns Hopkins University\\ +$^{13}$Drexel University\\ +$^{14}$University of California, Santa Cruz\\ +$^{14}$University of California, Davis\\ +\end{tabular} +} +\end{table} diff --git a/old/exgal_roadmap.tex b/old/exgal_roadmap.tex new file mode 100644 index 0000000..ea74b92 --- /dev/null +++ b/old/exgal_roadmap.tex @@ -0,0 +1,123 @@ +% ====================================================================== +%+ +% NAME: +% desc_white_paper.tex +% +% PURPOSE: +% Master latex file for the LSST desc_white_paper +% +% COMMENTS: +% - Includes Title page, Preface and Introduction, then \includes +% all technical material provided by science collaborations. +% - Use make to process, calls pdflatex +% - checkbook.csh can be used to check that all inputs are present +% +% INPUTS: +% Many and varied, via the \include command for bibliographic reasons +% grep '\\include' desc_white_paper.tex +% +% OPTIONAL INPUTS: +% final option to make final version +% +% OUTPUTS: +% desc_white_paper.pdf +% +% DEPENDENCIES: +% - whitepaper.sty, SciBook.bst +% - komascript package, providing the scrbook.cls +% http://www.ctan.org/tex-archive/macros/latex/contrib/koma-script/ +% +% EXAMPLES: +% make produces desc_white_paper.pdf +% +% +%- +% ============================================================================ + +%% LaTeX2e + +\documentclass[11pt,headsepline,cleardoubleempty,twoside,openright]{scrbook} +% 11pt font +% Draw a line under the header +% Don't draw a line or print page numbers when a page is empty +% Pages are two-sided - so margins alternate +% Chapters start on the righthand side of the page + +\usepackage{whitepaper} + +\hyphenation{zero-point zero-points} + +% ============================================================================ + +\begin{document} + +\begin{titlepage} +\begin{center} + +\vspace*{20mm} + +{\Huge\bfseries\scshape Large Synoptic Survey Telescope} +\linebreak +\linebreak +{\Huge\bfseries\scshape Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} + +\vspace*{20mm} + +\input{authorlist} + +%\vspace*{\stretch{2}}i + +%Version taken out for published draft +%%% 2012/07/22 - Put in automatic Version Date LatEx for ease of editing +%%% Now the Version and Date of the SVN version used to compile will +%%% be on the front page of the document. +%%% To generate a more formal version one may wish to change the following back to the hardcoded version right below the following line. +\vspace*{5mm} +\input{VersionDate} + +\end{center} +\end{titlepage} + +\include{abstract} + +% ---------------------------------------------------------------------------- + +\tableofcontents + +% ---------------------------------------------------------------------------- + +% NOTE FROM JAN: The extra white space after each section is due to +% using \Chapter for them all, following the Science Book. + +\include{introduction/introduction} + +\include{science_background/science_background} + +\include{roadmap/roadmap} + +\include{task_lists/task_lists} + +%\include{matrix/matrix} + +% ---------------------------------------------------------------------------- + +\bibliographystyle{SciBook} +\bibliography{references.bib} + +% ---------------------------------------------------------------------------- + +% \appendix + +% \setboolean{appendix}{true} +% \renewcommand\thechapter{\Alph{chapter}} +% \renewcommand{\chaptermark}[1]{\markboth{Appendix \thechapter: #1}{}} +% \renewcommand{\sectionmark}[1]{\markright{\thesection\ #1}{}} + +% Appendix content: + +%\include{stuff} + +\end{document} + +% ============================================================================ + diff --git a/structure.tex b/structure.tex new file mode 100644 index 0000000..19cbbb1 --- /dev/null +++ b/structure.tex @@ -0,0 +1,641 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% The Legrand Orange Book +% Structural Definitions File +% Version 2.0 (9/2/15) +% +% Original author: +% Mathias Legrand (legrand.mathias@gmail.com) with modifications by: +% Vel (vel@latextemplates.com) and Andrey Kravtsov (akravtsov@gmail.com) +% +% This file has been downloaded from: +% http://www.LaTeXTemplates.com +% +% License: +% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/) +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% The Legrand Orange Book +% LaTeX Template +% Version 2.1.1 (14/2/16) +% +% This template has been downloaded from: +% http://www.LaTeXTemplates.com +% +% Original author: +% Mathias Legrand (legrand.mathias@gmail.com) with modifications by: +% Vel (vel@latextemplates.com) +% +% License: +% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/) +% +% Compiling this template: +% This template uses biber for its bibliography and makeindex for its index. +% When you first open the template, compile it from the command line with the +% commands below to make sure your LaTeX distribution is configured correctly: +% +% 1) pdflatex main +% 2) makeindex main.idx -s StyleInd.ist +% 3) biber main +% 4) pdflatex main x 2 +% +% After this, when you wish to update the bibliography/index use the appropriate +% command above and make sure to compile with pdflatex several times +% afterwards to propagate your changes to the document. +% +% This template also uses a number of packages which may need to be +% updated to the newest versions for the template to compile. It is strongly +% recommended you update your LaTeX distribution if you have any +% compilation errors. +% +% Important note: +% Chapter heading images should have a 2:1 width:height ratio, +% e.g. 920px width and 460px height. +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%---------------------------------------------------------------------------------------- +% VARIOUS REQUIRED PACKAGES AND CONFIGURATIONS +%---------------------------------------------------------------------------------------- + +\usepackage[top=3cm,bottom=3cm,left=3cm,right=3cm,headsep=10pt]{geometry} % Page margins + +\usepackage{graphicx} % Required for including pictures +\usepackage{amsmath} +\usepackage{hyperref} +\usepackage{mathptmx} +\usepackage{anyfontsize} +\usepackage{t1enc} + +\graphicspath{{fig/}} % Specifies the directory where pictures are stored + +\usepackage{lipsum} % Inserts dummy text + +\usepackage{tikz} % Required for drawing custom shapes + +\usepackage[english]{babel} % English language/hyphenation + +\usepackage{enumitem} % Customize lists +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists + +\usepackage{booktabs} % Required for nicer horizontal rules in tables + +\usepackage{xcolor} % Required for specifying colors by name +%\definecolor{ocre}{RGB}{243,102,25} % Define the orange color used for highlighting throughout the book +\definecolor{ocre}{RGB}{119,181,254} % Define the orange color used for highlighting throughout the book + +\usepackage{listings} +\usepackage{color} + +\definecolor{dkgreen}{rgb}{0,0.6,0} +\definecolor{gray}{rgb}{0.5,0.5,0.5} +\definecolor{mauve}{rgb}{0.58,0,0.82} + +\lstset{frame=tb, + language=Java, + aboveskip=3mm, + belowskip=3mm, + showstringspaces=false, + columns=flexible, + basicstyle={\small\ttfamily}, + numbers=none, + numberstyle=\tiny\color{gray}, + keywordstyle=\color{blue}, + commentstyle=\color{dkgreen}, + stringstyle=\color{mauve}, + breaklines=true, + breakatwhitespace=true, + tabsize=3 +} + +\include{mydefs} + +%---------------------------------------------------------------------------------------- +% FONTS +%---------------------------------------------------------------------------------------- + +\usepackage{avant} % Use the Avantgarde font for headings +%\usepackage{times} % Use the Times font for headings +\usepackage{mathptmx} % Use the Adobe Times Roman as the default text font together with math symbols from the Sym­bol, Chancery and Com­puter Modern fonts + +\usepackage{microtype} % Slightly tweak font spacing for aesthetics +\usepackage[utf8]{inputenc} % Required for including letters with accents +\usepackage[T1]{fontenc} % Use 8-bit encoding that has 256 glyphs + +%---------------------------------------------------------------------------------------- +% BIBLIOGRAPHY AND INDEX +%---------------------------------------------------------------------------------------- + +%\usepackage[citestyle=authoryear,style=alphabetic,natbib=true,sorting=nyt,sortcites=true,autopunct=true,babel=hyphen,hyperref=true,abbreviate=false,backref=true,backend=biber]{biblatex} +\usepackage[backend=bibtex,style=authoryear,sortcites=true,autopunct=true,babel=hyphen,hyperref=true,abbreviate=false,backref=false,natbib]{biblatex} +%\usepackage{natbib} +%\newcommand{\citep}{\autocite} +%\newcommand{\citet}{\textcite} +%\newcommand{\citealp}{\cite} +\addbibresource{galaxies.bib} % BibTeX bibliography file +%\defbibheading{bibempty}{} + +\usepackage{calc} % For simpler calculation - used for spacing the index letter headings correctly +\usepackage{makeidx} % Required to make an index +\makeindex % Tells LaTeX to create the files required for indexing + +%---------------------------------------------------------------------------------------- +% MAIN TABLE OF CONTENTS +%---------------------------------------------------------------------------------------- + +\usepackage{titletoc} % Required for manipulating the table of contents + +\contentsmargin{0cm} % Removes the default margin + +% Part text styling +\titlecontents{part}[0cm] +{\addvspace{20pt}\centering\large\bfseries} +{} +{} +{} + +% Chapter text styling +\titlecontents{chapter}[1.25cm] % Indentation +{\addvspace{12pt}\large\sffamily\bfseries} % Spacing and font options for chapters +{\color{ocre!60}\contentslabel[\Large\thecontentslabel]{1.25cm}\color{ocre}} % Chapter number +{\color{ocre}} +{\color{ocre!60}\normalsize\;\titlerule*[.5pc]{.}\;\thecontentspage} % Page number + +% Section text styling +\titlecontents{section}[1.25cm] % Indentation +{\addvspace{3pt}\sffamily\bfseries} % Spacing and font options for sections +{\contentslabel[\thecontentslabel]{1.25cm}} % Section number +{} +{\hfill\color{black}\thecontentspage} % Page number +[] + +% Subsection text styling +\titlecontents{subsection}[1.25cm] % Indentation +{\addvspace{1pt}\sffamily\small} % Spacing and font options for subsections +{\contentslabel[\thecontentslabel]{1.25cm}} % Subsection number +{} +{\ \titlerule*[.5pc]{.}\;\thecontentspage} % Page number +[] + +% List of figures +\titlecontents{figure}[0em] +{\addvspace{-5pt}\sffamily} +{\thecontentslabel\hspace*{1em}} +{} +{\ \titlerule*[.5pc]{.}\;\thecontentspage} +[] + +% List of tables +\titlecontents{table}[0em] +{\addvspace{-5pt}\sffamily} +{\thecontentslabel\hspace*{1em}} +{} +{\ \titlerule*[.5pc]{.}\;\thecontentspage} +[] + +%---------------------------------------------------------------------------------------- +% MINI TABLE OF CONTENTS IN PART HEADS +%---------------------------------------------------------------------------------------- + +% Chapter text styling +\titlecontents{lchapter}[0em] % Indenting +{\addvspace{15pt}\large\sffamily\bfseries} % Spacing and font options for chapters +{\color{ocre}\contentslabel[\Large\thecontentslabel]{1.25cm}\color{ocre}} % Chapter number +{} +{\color{ocre}\normalsize\sffamily\bfseries\;\titlerule*[.5pc]{.}\;\thecontentspage} % Page number + +% Section text styling +\titlecontents{lsection}[0em] % Indenting +{\sffamily\small} % Spacing and font options for sections +{\contentslabel[\thecontentslabel]{1.25cm}} % Section number +{} +{} + +% Subsection text styling +\titlecontents{lsubsection}[.5em] % Indentation +{\normalfont\footnotesize\sffamily} % Font settings +{} +{} +{} + +%---------------------------------------------------------------------------------------- +% PAGE HEADERS +%---------------------------------------------------------------------------------------- + +\usepackage{fancyhdr} % Required for header and footer configuration + +\pagestyle{fancy} +\renewcommand{\chaptermark}[1]{\markboth{\sffamily\normalsize\bfseries\chaptername\ \thechapter.\ #1}{}} % Chapter text font settings +\renewcommand{\sectionmark}[1]{\markright{\sffamily\normalsize\thesection\hspace{5pt}#1}{}} % Section text font settings +\fancyhf{} \fancyhead[LE,RO]{\sffamily\normalsize\thepage} % Font setting for the page number in the header +\fancyhead[LO]{\rightmark} % Print the nearest section name on the left side of odd pages +\fancyhead[RE]{\leftmark} % Print the current chapter name on the right side of even pages +\renewcommand{\headrulewidth}{0.5pt} % Width of the rule under the header +\addtolength{\headheight}{2.5pt} % Increase the spacing around the header slightly +\renewcommand{\footrulewidth}{0pt} % Removes the rule in the footer +\fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}} % Style for when a plain pagestyle is specified + +% Removes the header from odd empty pages at the end of chapters +\makeatletter +\renewcommand{\cleardoublepage}{ +\clearpage\ifodd\c@page\else +\hbox{} +\vspace*{\fill} +\thispagestyle{empty} +\pagebreak +\fi} + +%---------------------------------------------------------------------------------------- +% THEOREM STYLES +%---------------------------------------------------------------------------------------- + +\usepackage{amsmath,amsfonts,amssymb,amsthm} % For math equations, theorems, symbols, etc + +\newcommand{\intoo}[2]{\mathopen{]}#1\,;#2\mathclose{[}} +\newcommand{\ud}{\mathop{\mathrm{{}d}}\mathopen{}} +\newcommand{\intff}[2]{\mathopen{[}#1\,;#2\mathclose{]}} +\newtheorem{notation}{Notation}[chapter] + +% Boxed/framed environments +\newtheoremstyle{ocrenumbox}% % Theorem style name +{0pt}% Space above +{0pt}% Space below +{\normalfont}% % Body font +{}% Indent amount +{\small\bf\sffamily\color{ocre}}% % Theorem head font +{\;}% Punctuation after theorem head +{0.25em}% Space after theorem head +{\small\sffamily\color{ocre}\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) +\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries\color{black}---\nobreakspace#3.}} % Optional theorem note +\renewcommand{\qedsymbol}{$\blacksquare$}% Optional qed square + +\newtheoremstyle{blacknumex}% Theorem style name +{5pt}% Space above +{5pt}% Space below +{\normalfont}% Body font +{} % Indent amount +{\small\bf\sffamily}% Theorem head font +{\;}% Punctuation after theorem head +{0.25em}% Space after theorem head +{\small\sffamily{\tiny\ensuremath{\blacksquare}}\nobreakspace\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) +\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries---\nobreakspace#3.}}% Optional theorem note + +\newtheoremstyle{blacknumbox} % Theorem style name +{0pt}% Space above +{0pt}% Space below +{\normalfont}% Body font +{}% Indent amount +{\small\bf\sffamily}% Theorem head font +{\;}% Punctuation after theorem head +{0.25em}% Space after theorem head +{\small\sffamily\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) +\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries---\nobreakspace#3.}}% Optional theorem note + +% Non-boxed/non-framed environments +\newtheoremstyle{ocrenum}% % Theorem style name +{5pt}% Space above +{5pt}% Space below +{\normalfont}% % Body font +{}% Indent amount +{\small\bf\sffamily\color{ocre}}% % Theorem head font +{\;}% Punctuation after theorem head +{0.25em}% Space after theorem head +{\small\sffamily\color{ocre}\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) +\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries\color{black}---\nobreakspace#3.}} % Optional theorem note +\renewcommand{\qedsymbol}{$\blacksquare$}% Optional qed square +\makeatother + +% Defines the theorem text style for each type of theorem to one of the three styles above +\newcounter{dummy} +\numberwithin{dummy}{section} +\theoremstyle{ocrenumbox} +\newtheorem{theoremeT}[dummy]{Theorem} +\newtheorem{problem}{Problem}[chapter] +\newtheorem{exerciseT}{Exercise}[chapter] +\theoremstyle{blacknumex} +\newtheorem{exampleT}{Example}[chapter] +\theoremstyle{blacknumbox} +\newtheorem{vocabulary}{Vocabulary}[chapter] +\newtheorem{definitionT}{Definition}[section] +\newtheorem{corollaryT}[dummy]{Corollary} +\theoremstyle{ocrenum} +\newtheorem{proposition}[dummy]{Proposition} + +%---------------------------------------------------------------------------------------- +% DEFINITION OF COLORED BOXES +%---------------------------------------------------------------------------------------- + +\RequirePackage[framemethod=default]{mdframed} % Required for creating the theorem, definition, exercise and corollary boxes + +% Theorem box +\newmdenv[skipabove=7pt, +skipbelow=7pt, +backgroundcolor=black!5, +linecolor=ocre, +innerleftmargin=5pt, +innerrightmargin=5pt, +innertopmargin=5pt, +leftmargin=0cm, +rightmargin=0cm, +innerbottommargin=5pt]{tBox} + +% Exercise box +\newmdenv[skipabove=7pt, +skipbelow=7pt, +rightline=false, +leftline=true, +topline=false, +bottomline=false, +backgroundcolor=ocre!10, +linecolor=ocre, +innerleftmargin=5pt, +innerrightmargin=5pt, +innertopmargin=5pt, +innerbottommargin=5pt, +leftmargin=0cm, +rightmargin=0cm, +linewidth=4pt]{eBox} + +% Definition box +\newmdenv[skipabove=7pt, +skipbelow=7pt, +rightline=false, +leftline=true, +topline=false, +bottomline=false, +linecolor=ocre, +innerleftmargin=5pt, +innerrightmargin=5pt, +innertopmargin=0pt, +leftmargin=0cm, +rightmargin=0cm, +linewidth=4pt, +innerbottommargin=0pt]{dBox} + +% Corollary box +\newmdenv[skipabove=7pt, +skipbelow=7pt, +rightline=false, +leftline=true, +topline=false, +bottomline=false, +linecolor=gray, +backgroundcolor=black!5, +innerleftmargin=5pt, +innerrightmargin=5pt, +innertopmargin=5pt, +leftmargin=0cm, +rightmargin=0cm, +linewidth=4pt, +innerbottommargin=5pt]{cBox} + +% Creates an environment for each type of theorem and assigns it a theorem text style from the "Theorem Styles" section above and a colored box from above +\newenvironment{theorem}{\begin{tBox}\begin{theoremeT}}{\end{theoremeT}\end{tBox}} +\newenvironment{exercise}{\begin{eBox}\begin{exerciseT}}{\hfill{\color{ocre}\tiny\ensuremath{\blacksquare}}\end{exerciseT}\end{eBox}} +\newenvironment{definition}{\begin{dBox}\begin{definitionT}}{\end{definitionT}\end{dBox}} +\newenvironment{example}{\begin{exampleT}}{\hfill{\tiny\ensuremath{\blacksquare}}\end{exampleT}} +\newenvironment{corollary}{\begin{cBox}\begin{corollaryT}}{\end{corollaryT}\end{cBox}} + +%---------------------------------------------------------------------------------------- +% REMARK ENVIRONMENT +%---------------------------------------------------------------------------------------- + +\newenvironment{remark}{\par\vspace{10pt}\small % Vertical white space above the remark and smaller font size +\begin{list}{}{ +\leftmargin=35pt % Indentation on the left +\rightmargin=25pt}\item\ignorespaces % Indentation on the right +\makebox[-2.5pt]{\begin{tikzpicture}[overlay] +\node[draw=ocre!60,line width=1pt,circle,fill=ocre!25,font=\sffamily\bfseries,inner sep=2pt,outer sep=0pt] at (-15pt,0pt){\textcolor{ocre}{R}};\end{tikzpicture}} % Orange R in a circle +\advance\baselineskip -1pt}{\end{list}\vskip5pt} % Tighter line spacing and white space after remark + +%---------------------------------------------------------------------------------------- +% SECTION NUMBERING IN THE MARGIN +%---------------------------------------------------------------------------------------- + +\makeatletter +\renewcommand{\@seccntformat}[1]{\llap{\textcolor{ocre}{\csname the#1\endcsname}\hspace{1em}}} +\renewcommand{\section}{\@startsection{section}{1}{\z@} +{-4ex \@plus -1ex \@minus -.4ex} +{1ex \@plus.2ex } +{\normalfont\large\sffamily\bfseries}} +\renewcommand{\subsection}{\@startsection {subsection}{2}{\z@} +{-3ex \@plus -0.1ex \@minus -.4ex} +{0.5ex \@plus.2ex } +{\normalfont\sffamily\bfseries}} +\renewcommand{\subsubsection}{\@startsection {subsubsection}{3}{\z@} +{-2ex \@plus -0.1ex \@minus -.2ex} +{.2ex \@plus.2ex } +{\normalfont\small\sffamily\bfseries}} +\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@} +{-2ex \@plus-.2ex \@minus .2ex} +{.1ex} +{\normalfont\small\sffamily\bfseries}} + +%---------------------------------------------------------------------------------------- +% PART HEADINGS +%---------------------------------------------------------------------------------------- + +% numbered part in the table of contents +\newcommand{\@mypartnumtocformat}[2]{% +\setlength\fboxsep{0pt}% +\noindent\colorbox{ocre!20}{\strut\parbox[c][.7cm]{\ecart}{\color{ocre!70}\Large\sffamily\bfseries\centering#1}}\hskip\esp\colorbox{ocre!40}{\strut\parbox[c][.7cm]{\linewidth-\ecart-\esp}{\Large\sffamily\centering#2}}}% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% unnumbered part in the table of contents +\newcommand{\@myparttocformat}[1]{% +\setlength\fboxsep{0pt}% +\noindent\colorbox{ocre!40}{\strut\parbox[c][.7cm]{\linewidth}{\Large\sffamily\centering#1}}}% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +\newlength\esp +\setlength\esp{4pt} +\newlength\ecart +\setlength\ecart{1.2cm-\esp} +\newcommand{\thepartimage}{}% +\newcommand{\partimage}[1]{\renewcommand{\thepartimage}{#1}}% +\def\@part[#1]#2{% +\ifnum \c@secnumdepth >-2\relax% +\refstepcounter{part}% +\addcontentsline{toc}{part}{\texorpdfstring{\protect\@mypartnumtocformat{\thepart}{#1}}{\partname~\thepart\ ---\ #1}} +\else% +\addcontentsline{toc}{part}{\texorpdfstring{\protect\@myparttocformat{#1}}{#1}}% +\fi% +\startcontents% +\markboth{}{}% +{\thispagestyle{empty}% +\begin{tikzpicture}[remember picture,overlay]% +\node at (current page.north west){\begin{tikzpicture}[remember picture,overlay]% +\fill[ocre!20](0cm,0cm) rectangle (\paperwidth,-\paperheight); +\node[anchor=north] at (4cm,-3.25cm){\color{ocre!40}\fontsize{220}{100}\sffamily\bfseries\@Roman\c@part}; +\node[anchor=south east] at (\paperwidth-1cm,-\paperheight+1cm){\parbox[t][][t]{8.5cm}{ +\printcontents{l}{0}{\setcounter{tocdepth}{1}}% +}}; +\node[anchor=north east] at (\paperwidth-1.5cm,-3.25cm){\parbox[t][][t]{15cm}{\strut\raggedleft\color{white}\fontsize{30}{30}\sffamily\bfseries#2}}; +\end{tikzpicture}}; +\end{tikzpicture}}% +\@endpart} +\def\@spart#1{% +\startcontents% +\phantomsection +{\thispagestyle{empty}% +\begin{tikzpicture}[remember picture,overlay]% +\node at (current page.north west){\begin{tikzpicture}[remember picture,overlay]% +\fill[ocre!20](0cm,0cm) rectangle (\paperwidth,-\paperheight); +\node[anchor=north east] at (\paperwidth-1.5cm,-3.25cm){\parbox[t][][t]{15cm}{\strut\raggedleft\color{white}\fontsize{30}{30}\sffamily\bfseries#1}}; +\end{tikzpicture}}; +\end{tikzpicture}} +\addcontentsline{toc}{part}{\texorpdfstring{% +\setlength\fboxsep{0pt}% +\noindent\protect\colorbox{ocre!40}{\strut\protect\parbox[c][.7cm]{\linewidth}{\Large\sffamily\protect\centering #1\quad\mbox{}}}}{#1}}% +\@endpart} +\def\@endpart{\vfil\pagebreak%\newpage +\if@twoside +\if@openright +\null +\thispagestyle{empty}% +%\newpage +\pagebreak +\fi +\fi +\if@tempswa +\twocolumn +\fi} + +%---------------------------------------------------------------------------------------- +% CHAPTER HEADINGS +%---------------------------------------------------------------------------------------- + +% A switch to conditionally include a picture, implemented by Christian Hupfer +\newif\ifusechapterimage +\usechapterimagetrue +\newcommand{\thechapterimage}{}% +\newcommand{\chapterimage}[1]{\ifusechapterimage\renewcommand{\thechapterimage}{#1}\fi}% +\def\@makechapterhead#1{% +{\parindent \z@ \raggedright \normalfont +\ifnum \c@secnumdepth >\m@ne +\if@mainmatter +\begin{tikzpicture}[remember picture,overlay] +\node at (current page.north west) +{\begin{tikzpicture}[remember picture,overlay] +\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; +\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}\thechapter. #1\strut}; +\end{tikzpicture}}; +\end{tikzpicture} +\else +\begin{tikzpicture}[remember picture,overlay] +\node at (current page.north west) +{\begin{tikzpicture}[remember picture,overlay] +\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; +\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; +\end{tikzpicture}}; +\end{tikzpicture} +\fi\fi\par\vspace*{270\p@}}} + +%------------------------------------------- + +\def\@makeschapterhead#1{% +\begin{tikzpicture}[remember picture,overlay] +\node at (current page.north west) +{\begin{tikzpicture}[remember picture,overlay] +\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; +\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; +\end{tikzpicture}}; +\end{tikzpicture} +\par\vspace*{270\p@}} +\makeatother + +%---------------------------------------------------------------------------------------- +% HYPERLINKS IN THE DOCUMENTS +%---------------------------------------------------------------------------------------- + +\usepackage{hyperref} +\hypersetup{hidelinks,backref=true,pagebackref=true,hyperindex=true,colorlinks=false,breaklinks=true,urlcolor= ocre,bookmarks=true,bookmarksopen=false,pdftitle={Title},pdfauthor={Author}} +\usepackage{bookmark} +\bookmarksetup{ +open, +numbered, +addtohook={% +\ifnum\bookmarkget{level}=0 % chapter +\bookmarksetup{bold}% +\fi +\ifnum\bookmarkget{level}=-1 % part +\bookmarksetup{color=ocre,bold}% +\fi +} +} + + +%------------------------------------------------------------------------------% +% Task formatting: + +% PJM: description environment for tasks, needs(?) +% item heading macros, to allow global editing, and italic headings. + +% \renewcommand\descriptionlabel[1]{\hspace{\labelsep}{\textsl{#1}}} +% \def\motivation{Motivation:} +% \def\activities{Activities:} +% \def\deliverables{Deliverables:} + +% Example usage: +% +% \begin{description} +% \item[\motivation] Currently things are bad. +% \item[\activities] We will work to make them better. +% \item[\deliverables] Code to solve all problems. +% \end{description} + + +% PJM: The following macro works, but is not very transparent to the writer... +% \def\task#1#2#3% +% {\begin{description} +% \item[Motivation]{#1} +% \item[Activities]{#2} +% \item[Deliverables]{#3} +% \end{description}} + +% Example usage: +% +% \task +% {Currently things are bad.} +% {We will work to make them better.} +% {Code to solve all problems.} + + +% PJM: OK, this is better - now only task items are italicised, and we have +% control over all tasks: + +\def\motivation#1{\item[Motivation:] #1} +\def\activities#1{\item[Activities:] #1} +\def\deliverables#1{\item[Deliverables:] #1} + +\newenvironment{task}% +{\renewcommand\descriptionlabel[1]{\hspace{\labelsep}\textit{##1}} + \begin{description}\setlength{\itemsep}{0.15\baselineskip}} +{\end{description}} + +% Example usage: +% +% \begin{task} +% \motivation{Currently things are bad}. +% \activities{We will work to make them better}. +% \deliverables{Code to solve all problems}. +% \end{task} + +% PJM: here's a tasklist environment to take care of Michael's enumeration: + +\def\tasktitle#1{\item{\bf #1}} + +\newenvironment{tasklist}[1]% +{\begin{enumerate}[label=#1-\arabic{*}.,ref=\thesubsection:#1-\arabic{*},font=\bf]} +{\end{enumerate}} + +% Example usage: +% +% \begin{tasklist}{H} +% \tasktitle{Automated Lens Candidate Detection in the LSST Catalogs [Lupton]} +% \label{task:sl:detection} +% \begin{task} +% \motivation{Currently things are bad}. +% \activities{We will work to make them better}. +% \deliverables{Code to solve all problems}. +% \end{task} +% \end{tasklist} From e6b040d909a7171f4ac97d330cbb33ab23ba3282 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 20 Dec 2016 20:36:46 -0800 Subject: [PATCH 04/64] Revising task list. Added AGN task list. --- authorlist.tex | 27 +- exgal_roadmap.pdf | Bin 187611 -> 145035 bytes exgal_roadmap.tex | 25 +- old/black_holes/black_holes.tex | 228 +++++++++ .../chapter_intro.tex | 2 +- old/chapterintro.tex | 8 + old/galaxies/galaxies.tex | 475 +++++++++++++++++ old/galaxies/galaxies.tex.save | 479 ++++++++++++++++++ old/informatics/informatics.tex | 8 + old/lss/lss.tex | 8 + old/strong_lensing/strong_lensing.tex | 8 + old/task_lists.tex | 22 + old/weak_lensing/weak_lensing.tex | 8 + structure.tex | 17 +- task_lists/agn/agn.tex | 127 +++++ task_lists/task_lists.tex | 23 +- 16 files changed, 1420 insertions(+), 45 deletions(-) create mode 100644 old/black_holes/black_holes.tex rename task_lists/chapter_intro.tex~ => old/chapter_intro.tex (89%) create mode 100644 old/chapterintro.tex create mode 100644 old/galaxies/galaxies.tex create mode 100644 old/galaxies/galaxies.tex.save create mode 100644 old/informatics/informatics.tex create mode 100644 old/lss/lss.tex create mode 100644 old/strong_lensing/strong_lensing.tex create mode 100644 old/task_lists.tex create mode 100644 old/weak_lensing/weak_lensing.tex create mode 100644 task_lists/agn/agn.tex diff --git a/authorlist.tex b/authorlist.tex index 26ace6f..723b2ad 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -2,20 +2,15 @@ \vspace*{5mm} -\begin{table}[htp] -\centering -{\renewcommand{\arraystretch}{0.8} -\begin{tabular}{p{10cm}} -$^{1}$University of California, Santa Cruz\\ -$^{2}$Cambridge University\\ -$^{3}$University of California, Irvine\\ -$^{4}$Oxford University\\ -$^{5}$Space Telescope Science Institute\\ -$^{6}$University of Hertfordshire\\ -$^{7}$University of Pittsburgh\\ -$^{8}$National Optical Astronomical Observatory\\ -$^{9}$Pontifica Universidad Catolica de Chile\\ -$^{10}$University of California, Davis\\ -\end{tabular} +{\centering\it\small +$^{1}$University of California, Santa Cruz, +$^{2}$Cambridge University, +$^{3}$University of California, Irvine, +$^{4}$Oxford University, +$^{5}$Space Telescope Science Institute, +$^{6}$University of Hertfordshire, +$^{7}$University of Pittsburgh, +$^{8}$National Optical Astronomical Observatory, +$^{9}$Pontifica Universidad Catolica de Chile, +$^{10}$University of California, Davis, } -\end{table} diff --git a/exgal_roadmap.pdf b/exgal_roadmap.pdf index 22c8d778300e23b49b0a09ffa84d3263f041164d..77152c9102f8ced6a8d1ca542d4df624cdda0762 100644 GIT binary patch delta 129227 zcmZs?LzphG5-r-;ZQHhO+qTW!w*R(m+qP}nwr%fs&bi+k-8)GtgH$Fft7@exTOBY_ zH<0lppp0xxNkpEMfEo=s=Ph=`o-d7i$yrUxUIDMDn_(&JF?=0c1Y3l9$tg)vWl-VD zB!fLNp^0SSDdkd#EmFwtH@Am+%_Gyy{o}_!ci((CdEbxn4Z%*u&BPP$L`1qIp>o76 z!pf1R*%W}1yz04d`7$x~LXa}|y-91N?P718Pc?B-ZPvbCz(|8*se|@(q?a;Xhyq+Jcc`@d1O zSc{>gB+&br68CKi16x+)%7hs<%e(6Ad0S#lm2f$Rru9}L1Xw|&3I2tM?A(Rh>Te+k zu4-<=v)yz<0P_}M@dLMpLrI53MpIK=$xuqp!%QJ~_NLYHR@!fjwI00!U=Sii3_hPv zWPXBvfjUEi&yQ}WBnh4AP>_Hhi%N;%Sg7McbJVh`Grk_YXfXfg3&(pC&Rw*Hn5i>8 zPlM#%rri(30$>Bf9TLVr@JK!5!Z$zZ=!DUU}j 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zru-t#t1by|+tfz|;`rfTXGo0N3LdNYk&auir|soI-eLdY(F)SC_E92Hyk_`RS$_g( z+MbxDx2-BkIvsj$`W+9f{rwpji|z{C%yI;_W7zI@@ diff --git a/exgal_roadmap.tex b/exgal_roadmap.tex index ec8bde9..185a851 100644 --- a/exgal_roadmap.tex +++ b/exgal_roadmap.tex @@ -27,7 +27,7 @@ %---------------------------------------------------------------------------------------- \begingroup -%\thispagestyle{empty} +\thispagestyle{empty} %\begin{tikzpicture}[remember picture,overlay] %\coordinate [below=11cm] (midpoint) at (current page.north); %\node at (current page.north west) @@ -38,12 +38,18 @@ %{\Huge Andrey Kravtsov}}}; % Author name %\end{tikzpicture}}; %\end{tikzpicture} -{\Huge\bfseries\scshape Large Synoptic Survey Telescope} +%{\Huge\bfseries\scshape Large Synoptic Survey Telescope} +{\Huge Large Synoptic Survey Telescope} \linebreak \linebreak -{\Huge\bfseries\scshape Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} +{\Huge Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} +\linebreak +\linebreak +%{\paperwidth}{\centering\color{blue}{\fontsize{70}{80}\selectfont Galaxies} +{\centering \input{authorlist} \input{VersionDate} +} \vfill \endgroup @@ -92,11 +98,12 @@ \tableofcontents % Print the table of contents itself -%\cleardoublepage % Forces the first chapter to start on an odd page so it's on the right +\cleardoublepage % Forces the first chapter to start on an odd page so it's on the right \nopagebreak[4] -\pagestyle{fancy} % Print headers again +%\pagestyle{fancy} % Print headers again +\pagestyle{empty} % Print headers again %---------------------------------------------------------------------------------------- % Chapters @@ -105,13 +112,13 @@ % if it ever gets so big as to require Parts %\part{Part One} - +\pagestyle{empty} \include{introduction/introduction} - +\pagestyle{empty} \include{science_background/science_background} - +\pagestyle{empty} \include{roadmap/roadmap} - +\pagestyle{empty} \include{task_lists/task_lists} %\include{matrix/matrix} diff --git a/old/black_holes/black_holes.tex b/old/black_holes/black_holes.tex new file mode 100644 index 0000000..249a5e7 --- /dev/null +++ b/old/black_holes/black_holes.tex @@ -0,0 +1,228 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: black_holes +% First draft by + +\section{Black Hole Science Preparations}\label{sec:tasks:agn:task_list} + +This document is a draft road-map for Black Hole science with LSST. Here we describe the broad ``to do'' list that defines the roadmap for all BH science, in addition to focusing on tasks needed for certain science cases and also areas where the needs of this group may overlap with roadmap plans from other groups. In composing it, I have followed the organization of the LSST Science Book, specifically Chapter 10 on AGNs. That way the authors of the sub-sections can clearly identify any issues that we have (so far) failed to address herein. + +\subsection{AGN Selection and Census} + +Black Hole (BH) science will be a major theme for LSST covering science topics ranging from the BH-fueled evolution of galaxies, to lensed black holes as tools for cosmology, to small-scale physics of the BHs themselves using variability and tidal disruptions as probes. For all BH science with LSST the first step that must be taken is to find the BHs themselves, whether through short-lived transient events or longer-lived fueling. In that sense the primary goal for this roadmap for BH science is seemingly straightforward: identify efficient and complete ways to pinpoint the location of black holes on the sky, and, ideally, their redshifts. In practice the devil is in the details and the optimal solution to this problem may be different for each of the LSST's BH science goals. + +In the past, BH science could afford low efficiency in candidate +selection because of spectroscopy: even if the majority of targets +were not BHs, at least that was known. Today, while we can hope for a +significant amount of spectroscopy from DESI and/or similar projects, +it is clear that we will not obtain spectroscopy for tens of millions +of candidate BHs. Thus we need to concentrate on going it alone. In +simplest terms this means identifying BHs with both high completeness +and high efficiency. + +Unfortunately the optimal methods for doing so are not expected to be +generic for all BH science. Broadly speaking LSST BH science can be +divided into the need to identify four types of BHs: unobscured +quasars, obscured quasars/AGNs, lower-luminosity AGNs, and transient BH +fueling events. This is further complicated by the fact that objects +in each category may require somewhat different methods as a function +of redshift and/or by (close) spatial separation. + +For example, selection of unobscured quasars can take full advantage +of the LSST data set: multi-band, multi-epoch optical photometry and +astrometry, whereas selection of obscured quasars necessarily relies +on supporting data from outside LSST. Lower-luminosity AGNs will +further need to be weeded from (the far more abundant) inactive +galaxies, and identification of transient-fueled BHs will be limited +by the number of epochs of detection. Each of these cases do have a +similar task need: developing new tools and applying them to simulated +data. + +For unobscured quasars we must optimize the identification of BHs using +\begin{itemize} +\item colors +\item variability +\item astrometry +\end{itemize} +---ideally all three simultaneously. Moreover, we will have to +consider the impact of star-galaxy separation (can we use the same +algorithm(s) regardless of morphology?) and the evolution of these +properties with redshift. + +For obscured quasars, we will necessarily be reliant upon information +from other sources to confirm the ``active'' nature of what will +otherwise appear as normal galaxies (or not appear at all) in LSST. + +Without a doubt one of the single most important to do items in terms of LSST AGN selection is to run simulations that use all 6 LSST bands, covering as much area and as many epoch as possible. Such simulations should also include as much physics and empirical correlation as possible. This includes: luminosity-dependence of emission features, magnitude-color correlations, variability physics, astrometric errors, differential chromatic refraction, nuclear vs. host galaxy luminosity correlation [and its relationship to morphology], star-galaxy separation, lensing probability, broad absorption lines and dust reddening (intrinsics, host galaxy, and intervening). These simulations already exist and are relatively mature, but new simulated data has not been produced in a number of years and the simulations have not been fully vetted by the science collaborations. One or more groups will need to begin running the simulation code and conducting various tests (e.g., comparing to real data). + +Lastly, a goal for LSST should be for every science working group to give a probability for {\em every} LSST object. This information can then be fed back into the classification schemes developed by each group. E.g., an object that the AGN group gives a 30\% chance of being an AGN might be downgraded if the SNe group flags it as an SN at 99\%. + +\subsubsection{Color Selection} + +Color-selection by itself is certainly the most mature of the avenues +for identifying AGNs. Any application of modern statistical +techniques such as described by [take REFS from Tina's paper] will be +a major first step in the process. + +Specific to do items in this regard are to establish an agreed-upon +test bed of color data and have a ``bake off'' to determine which +methods are the most effective. This could include (or be completely +based upon) simulated data. + +Moreover, it is unlikely that any final method(s) adopted for LSST AGN +selection will be completely color based, thus it will be important to +extend such efforts to multi-parameter selection methods using the +information from the next sections. + +Isolation of {\em nuclear} colors through difference imaging may be +crucial for low-luminosity systems (which will provide the bulk of new +LSST discoveries). + +\subsubsection{Lack of Proper Motion/Astrometry} + +As certain quasars and stars can have very similar colors, the fact +that quasars do not have proper motions as do Galactic stars has long +been used as a discriminant. That will be no different for LSST. +However, even with its precise astrometry, LSST will need to +distinguish between objects that are only apparently moving and those that +are truly moving and do so as a function of apparent magnitude. +Simulated data can be used to start this process. + +Another task that can begin now is to extend algorithms that use USNO +data as a time baseline extension to new data from GAIA. Stripe 82 +data can be used as an LSST-like testbed for this. + +A more recent approach has been to take advantage of differential +chromatics refraction of AGNs (Kaczmarczik et al. 2009). In short +this procedure makes use of the astrometric offset of an emission line +object from that expected (in the astrometric solution) for a +power-law source. Peters et al. (2015) have developed a formalism for +including this information with color information, but more work is +needed to fully leverage this resource. + +\subsubsection{Selection by Variability} + +In many ways variability will be the cornerstone of object +classification for LSST. However, variability by itself is unlikely +to be a panacea. Even for luminous quasars, it has been shown that +variablity combined with colors works better for selection than +variability alone (Peters et al. 2015). + +Moreover, for low-luminosity AGNs which are expected to have the most +variable nuclei, increasing contamination from the host galaxy will +compromise variability-selection methods if insufficient care is +taken. Thus one clear to do item for variability selection is to team +up with other groups with more expertise in difference imaging in +order to isolate the variability properties of the {\em nuclear} +emission. + +The next most crucial step for variability analysis may well be +determining how to make use of {\em all} of the data. Specifically, +most current investigations looking at variability only use one +photometric bandpass, whereas LSST will have 6. For the $gri$ data, +it may be sufficient to apply a median-color based offset and treat +the (non-simultaneous) data as one (e.g., by kriging the data +together) with better time resolution than would be available with +just a single band. The fact that quasars are systematically bluer +when brighter will add a complication to such efforts, however. For +the $z$ and $y$ data, low S/N may make it difficult to treat these +measurements equivalently to $gri$. Moreover, the spatial (and thus +time) separation of $g$ and $y$ could actually degrade the accuracy of +a merged light curve. For the $u$-band data, low S/N and sampling of +the Ly-$\alpha$ forest rather than the quasar continuum at +high-redshift will add complications. These are issues that can be +further investigated with existing (and ongoing) data sets such as +Stripe 82, DES, and Pan-STARRS. + +Lastly, unlike magnitudes which are uniformly measured for all +objects, light curves are difficult to analyze in a non-parametric +fashion. A functional form (or forms) must be agreed upon and it must +be realized that without an accurate redshift, comparison of +variability parameters often compares very different rest frames. +$A$-$\gamma$ is certainly the simplest parameterization, but the +damped random walk (DRW) is currently the most popular. Further work +is needed to determine if these are sufficiently accurate to use or if +a different parameterization might be more effective. + +Work with SDSS Stripe 82 has allowed some early work in this +direction. More still needed, possibly taking advantage also of +Kepler, SDSS-RM, and/or OzDES data. + + +\subsubsection{Combination with Multiwavelength Data} + +The last way that LSST will identify BHs is by combining with multiwavelength data. This can be considered more generally as ``combination with data from other facilities'' as some data (e.g., Euclid) may also be in the optical. + +We will largely concentrate on the tasks needed for obscured quasars and low-luminosity AGNs as multi-wavelength data will likely add only episilon to our efforts robust selection of luminous type 1 quasars. This is particularly true at high reshift since combining with multiwavelength data generally means focusing on the brightest objects given how much deeper (for a given SED) LSST will reach than the typical IR and X-ray limits of large-area surveys. In nearly all cases we will have tiered multiwavelength data to contend with: shallow over a large area to deep over a small area. + +For unobscured AGNs multiwavelength data can be used to modify the AGN probabilities for objects on the border; this will be most useful within the context of a probabilistic redshift distribution (see next subsection). Objects detected in the X-ray or IR with sufficiently high predicted luminosity will have increased AGN probability. Objects detected in the UV will have significantly decreased AGN probability. + +For obscured and low-luminosity AGNs, the optical data from LSST may not be sufficient to identify the object as an AGN. Some low-luminosity AGNs may be identified as having nuclear variability, but for the faintest objects the errors on the variability will be insufficient for robust classification. As such, for these classes of objects will we be completely dependent upon multiwavelenth SED fitting and X-ray and/or IR luminosity and radio morphology to identify as AGNs what LSST sees as a galaxy. + +Crucial for these endeavors will be the Deep Drilling Fields (DDFs). Here is where there exists the most multiwavelength coverage. The DDFs will serve as a testbed for multiwavelength analysis in larger areas (by allowing us to understand what the brightest objects will look like). They will also provide the greatest depth (for a given completeness and efficiency) for AGN selection. Moreover they will have (outside of Stripe 82) the greatest density of spectral coverage and will essentially {\em define} the completeness and efficiency of AGN selection for the full survey area by providing small-area ``truth tables''. Such work will be crucial for the science efforts discussed below but also for early ``reverberation mapping'' work. + +One of the biggest challenges will be conducting a sort of VO-like cataloging of the multiwavelength imaging data that will be used for these efforts. There may be no practical way to include {\em all} of the multiwavelength data and that task may fall on individual PIs of those programs. However, LSST should, at the very least identify key deep and wide data sets that should be matched in the course of pre-planned LSST analysis. Currently the greatest depth of the full sky is 2MASS in the near-IR, {\em WISE} in the mid-IR, {\em ROSAT} in the X-ray, and NVSS in the radio (soon to be replaced by EMU/Wodan). Somewhat deeper, but with less coverage we have UKIDSS and VHS in the near-IR; SpIES, SSDF, SERVS, SDWFS, and SWIRE in the mid-IR; the XMM Slew Survey and ChAMP in the X-ray; and GALEX in the UV. The key deep fields will be located within the DDFs. [GTR: Add any crucial missing data sets.] + +It is with the multiwavelength data that true bandmerging will be required. That is the nearest positional match in another wavelength may not be the correct match to the LSST source. We must perform an astrophysically based SED matching using a suite of templates to determine the best matches. Such efforts have already received attention in the literature (e.g., Budavari \& Szalay 2008) and preliminary work can proceed in earnest in the coming years. + +\subsubsection{Photometric Redshifts} + +Photo-z methods for AGNs can generally be broken into two methodologies: template-fitting (e.g., Salvato) and empirical (e.g., Richards et al.\ 2001). Template fitting is the method of choice for objects that exhibit a spectral break that can be used to broadly (perhaps even narrowly) isolate the redshift. A number of algorithms are in existence: EAZY, LePhare, ZEBRA, to name a few. Arguably more important that the algorithm is the suite of templates used. There is no lack of data to test these algorithms and work to chose an optimal algorithm and templates can and should proceed in the next few years. Indeed, this may not be a separate task from the broader galaxy photo-z efforts. + +However, it is known that template fitting algorithms break down for luminous quasars as such objects exhibit no strong spectral break in the LSST filters (with the exception of high-redshift quasars where template fitting can still be effective); see Assef et al.\ 2010. In these cases empirical methods will be more effective. Thus one of the short-term tasks for LSST should be an attempt to merge these algorithms or learn how to smoothly morph between them as a function of luminosity should it be found that a single algorithm (and set of templates) is not sufficient. + +Regardless of the algorithm LSST astronomers will need to become comfortable with working with photo-z probability distribution functions (PDFs). That is photo-z's will not consist of single predicted redshifts with errors, but rather will be a vector of probabilities at {\em every} redshift. Di Pompeo et al.\ 2015 provides an example of analysis performed with photo-z PDFs. + + +\subsubsection{Expected Number of AGNs} + +Currently the prediction for the number of AGNs that LSST will observe is largely based on Hopkins, Richards, \& Hernquist (2007). That work combined all of the best multiwavelength quasar luminosity functions (across all redshifts) that were available in 2007 and provided code to determine the expected number of {\em all} AGNs at any redshift and luminosity. However, since that time new work has revealed significant changes in the best-fit luminosity function. The most obvious is the slope of the bright-end of the QLF at high redshift, which for many years has been thought to be quite flat. Jiang et al. 20??, McGreer et al.\ 2013, and Ross et al.\ 2013 have subsequently shown that what we thought was the bright end of the QLF at high-z was really the faint end and that the break luminosity is much brighter than expected. Graphically this can be understood as Figure 10.8 in the LSST Science Book as showing a high-z decline of Lstar (the solid black line) that is too steep. Practically this means that the number of high-redshift AGNs will change. Further changes may come from modification of the type 2 to type 1 ratio as a function of luminosity. + +What is needed here is for someone to take on the (relatively) thankless task of updating HRH07. As encouragement, the 500+ citations for HRH07 may mean that this task won't be quite so thankless! + + +\subsection{Luminosity Function} + +Despite countless dedicated efforts, it remains true that our understanding of the luminosity function of AGNs is incomplete and a much-improved LF will be a major result from LSST. Updating HRH07 as noted above is one task that is needed here in the short-term. Largely this is to ensure that the LF that serves as an {\em input} to LSST simulations is as accurate as possible. + +We emphasize that this task is absolutely {\em not} something that needs to wait for data. LSST should endeavor to publish a LF paper {\em before} any data are taken---using the simulated data. Such a paper will serve as a template for data-based analysis in the future, but more importantly will serve as a guide for the expected errors as a function of redshift and magnitude. Differences between the predicted and observed LFs will guide understanding of differences in BH physics from the predicted model. + +Such work will also serve as a guideline for how LSST will determine the completeness, efficiency and total volume searched for a necessarily probabilistic sample. As already discussed above, precursor spectroscopy, especially in the DDFs and/or Stripe 82 will be needed to serve as truth tables in this analysis. + +\subsection{Clustering} + +Some of the greatest gains on BH physics will come from an array of clustering analyses that LSST will uniquely be able to perform. In large part this comes about because high densities and accurate redshifts are needed to robust clustering analysis. Currently high densities are not being achieved over sufficient area at high redshift (and interesting depth) and photometric redshift accuracy (largely due to catastrophic errors) is a limiting factor at lower redshifts. + +Most needed here is preliminary work in Stripe 82 where the depth (both in the mid-IR and optical), areal coverage, and existing spectral density provide an excellent testbed. Stripe 82 also serves as an excellent testbed for photometric redshift testing. + +As with the LF, a series of preliminary clustering papers can be produced in advance of LSST by taking advantage of simulated data. Particularly interesting will clustering of faint sources at high-redshift, clustering of obscured vs. unobscured AGN, and clustering of hard- vs. soft-spectrum AGNs. The latter is of interest as even bona-fide quasars are expected to exhibit a large range of masses and accretion rates. + + +\subsection{Multiwavelength Physics} + +Much of the work needed here has already been discussed above. The most challenging will be the fact that some AGNs will be invisible in the optical alone but will be discoverable through combination with multi-wavelength data. LSST needs to develop formalism for doing this. + +\subsection{Variability} + +Again, much of the work needed here has been described above. However, we emphasize that variability analysis for AGN {\em selection} will necessarily be different from variability analysis for AGN {\em physics}. The obvious different being the need to work in the rest frame vs.\ the observed frame. Thus photometric redshifts will play a key role. Similarly, work needs to be done to determine if the variabiltiy parameterization for selection and physics should be the same or different. + +Early work can be done with simulated data on nearly all of the areas of variability science, including characterization of AGN variability, power density spectra, photometric reverberation mapping, accretion disk sizes, and lensing time delays. + +\subsection{Transient Fueling Events} + +The above text has largely concentrated on identification of relatively long-lived BH fueling events. Someone should fill in to do items for identification of transient fueling events and for doing BH physics with such events. + +\subsection{Gravitational Lenses} + +The strong lens working group will have their own road map task list, but beyond robust AGN identification and photometric redshift estimation, gravitational lensing work will also be concerned with morphology, deblending, and lensing galaxy identification. + + +\subsection{Miscellaneous} + +Other to do items not covered above include the need to build a database of existing spectroscopic identifications, obtaining additional spectroscopy in the DDFs and Stripe 82, pre-planning for follow-up observations, and announcing LSST observing schedule to other facilities. + + + + + diff --git a/task_lists/chapter_intro.tex~ b/old/chapter_intro.tex similarity index 89% rename from task_lists/chapter_intro.tex~ rename to old/chapter_intro.tex index 8cf9748..fbb729e 100644 --- a/task_lists/chapter_intro.tex~ +++ b/old/chapter_intro.tex @@ -2,7 +2,7 @@ prepare for LSST science. Tasks are categorized as (1) {\it techniques algorithms, techniques, or software}, (2) {\it -precursor observations or synergy with other facilities, (3) +precursor observations or synergy with other facilities}, (3) {\it LSST-targeted theory or simulations} and (4) {\it Databases, science queries and data services}. For convenience in preparing the Appendix, these are divided by science topic along the science collaboration boundaries. diff --git a/old/chapterintro.tex b/old/chapterintro.tex new file mode 100644 index 0000000..e355294 --- /dev/null +++ b/old/chapterintro.tex @@ -0,0 +1,8 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: galaxies +% First draft by + +\section{XXX}\label{sec:tasks:gal:XXX} + diff --git a/old/galaxies/galaxies.tex b/old/galaxies/galaxies.tex new file mode 100644 index 0000000..6e4b057 --- /dev/null +++ b/old/galaxies/galaxies.tex @@ -0,0 +1,475 @@ +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: galaxies +% First draft by + +\section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} + +The LSST design, and to a certain extent the design of the data-management +system, is optimized to carry out the core science mission. For measurements +of dark-energy, that generally means treating galaxies as ``tracer particles'' -- +using statistical measures of ellipticity and position provide statistical +constraints on large-scale structure and cosmic geometry. While many of the +DESC tasks are directly relevant to studying galaxy evolution, they are +incomplete. In particular, studies of galaxy evolution require more attention to +optimizing multi-wavelength supporting data, different kinds of spectroscopy, different +kinds of simulations and theoretical support, and greater attention to detection +and characterization of low-surface brightness features or unusual morphologies. + +The task list presented here highlights the preparation work needed in the next 3-4 +years. Of primary importance are tasks that might influence the detailed survey +design or the algorithms used in the DM to construct catalogs. These are the most +urgent. Also included are activities that can be reasonably independent of the +LSST survey design and DM optimization, but which will ensure good support for +LSST galaxy studies. + +\begin{tasklist}{T} +\tasktitle{Example Task List} +\begin{task} +\label{task:label_for_this_task} +\motivation{Put Science Motivation Here} +\activities{Described Activities Here} +\deliverables{ + Deliverables over the next several years from the activities described above include the following: + \begin{enumerate} + \item a deliverable + \item another deliverable + \end{enumerate} +} +\end{task} +\end{tasklist} + +\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} + +\begin{tasklist}{T} +\tasktitle{Techniques for finding low-surface-brightness features or galaxies} +% Tidal streams +% Intracluster diffuse light +\begin{task} +\label{task:gal:lsb} +\motivation{ +A huge benefit of LSST relative to prior large-area surveys will be its ability to detect +low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and +other features associated with past and ongoing mergers, it includes intra-cluster and +intra-group light, and it includes relatively nearby, extended low-surface-brightness galaxies. +Prior to LSST, typical studies of the low-surface-brightness universe have focused +on relatively small samples, often selected by criteria that are difficult to quantify +or reproduce in theoretical models. Measurements of the LSB features themselves themselves +are challenging, often requiring hand-tuning and interactive scientific judgment. This is +important for accurately quantifying what we observe, but such interactive tuning +of the measurements (a) is not something that can be applied on the LSST scale and (b) +is difficult to apply to theoretical models. For LSST it is crucial that we automate +the detection and characterization of LSB features, at least to the point where samples +for further study can be selected via database queries, and where the completeness of +samples returned from such queries can be quantified. +} + +\activities{ +Several activities are of crucial importance: (1) simulating realistic LSB features, (2) +using the simulations to optimize detection and measurement, (3) ensuring that LSST +level-2 processing strategies and observing strategies are at least cognizant +of needs of LSB science and (4) developing a strategy for finding and measuring LSB features through +some combination of level 2 measurements, database queries, and level 3 processing.\\ +It is important to insert realistic low-surface-brightness +features into LSST simulated images and try to extract and measure them, exploring +different techniques or algorithms for doing the detection and measurement. Because the LSB objects +are sparse on the sky, making realistic LSST sky images is probably not the most efficient +way to accomplish this; more targeted simulations with a higher density of +LSB objects are needed. The simulated observations need to be realistic in their +treatment of scattered light, particularly scattering from bright stars which +may or may not be in the actual field of view of the telescope. +Scattering from bright stars is likely to be the primary source of contamination +when searching for extended LSB features. Ideally, the LSST scattered-light model, +tuned by repeated observations, will be sufficiently good that these contaminants +can be removed or at least flagged at level 2. Defining the metrics for ``sufficiently good,'' +based on analysis of simulations, is an important activity that needs early work to +help inform LSST development. Including Galactic cirrus in the simulations is important +for very large-scale LSB features. Including a cirrus model as part of the LSST background +estimation is worth considering, but it is unclear yet whether the science benefit +can justify the extra effort. \\ +Because the LSST source extraction is primarily +optimized for finding faint, barely-resolved galaxies, it is going to be challenging to +optimize simultaneously for finding large LSB structures and cataloging them as +one entity in the database. For very large structures, analysis of the LSST ``sky background'' +map, might be the most productive approach. We need to work with the LSST project +to make sure the background map is stored in a useful form, and that background +measurements from repeated observations can be combined to separate the fluctuating +foreground and scattered light from the astrophysically interesting signal from extended +LSB structures. Then, we need strategies for measuring these background maps, characterizing +structures, and developing value-added catalogs to supplement the level 2 database.\\ +For smaller structures, it is likely that the database will contain pieces +of the structure, either as portions of a hierachical +family of deblended objects, or cataloged as separate objects. Therefore, we need to +develop strategies for querying the database to find such structures and either extract +the appropriate data for customized processing, or develop ways to put back together +the separate entries in the database. A possible value-added catalog, for example, from +the galaxies collaboration might be an extra set of fields for the database to indicate +which separate objects are probably part of the same physical entity. This would +be sparsely populated in the first year or two of LSST, but by the end of the survey +could be a useful resource for a wide variety of investigations. +} + +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item realistic inputs of LSB galaxies or LSB features for the LSST image simulations; +\item custom simulations; +\item algorithms for finding and measuring LSB features; +\item input to the Project on scattered-light mitigation and modeling strategies; +\item input to the project on photometric and morphological parameters to measure/store at level 2; +\item query strategies and sample queries for finding LSB structures; and +\item a baseline concept for a value-added database of LSB structures +\end{enumerate} +} +\end{task} + +\tasktitle{Techniques for identifying and deblending overlapping galaxies} +\begin{task} +\label{task:gal:deblending} +\motivation{ +The Level 2 data products are the most relevant starting point +for galaxy-evolution science. In the LSST nomenclature, {\tt Objects} +represent astrophysical entities (stars, galaxies, quasars, etc.), while +{\tt Sources} represent their single-epoch observations. +The master list of Objects in Level 2 will be generated by associating +and deblending the list of single-epoch source detections and the +lists of sources detected on coadds. The exact strategies for doing +this are still under active development by the LSST project, and +engagement with the science community is essential. While each +data release will have unique object IDs, it will be a huge impediment +for LSST science if the first few generations of catalogs turn out +severely the limit the science that can be done via database queries. \\ +For galaxies science, the issue of deblending is of critical importance. +For example, searches for high-redshift galaxies via color selection +or photometric redshifts involve model or template spectra that make +the prior assumption that the object in question is a single object at +one redshift, not a blend of two objects at two different redshifts. +Therefore to get a reliable estimate of the evolution of classes of galaxies +over redshift, we need to (a) have reasonably clean catalogs to start with +and (b) be able to model the effects of blending on the sample selection +and derivation of redshift and other parameters. This is critical +not just for galaxy-evolution science, but for lensing and large-scale +structure studies. This is just one example. Another is the evolution +of galaxy morphologies, where the effects of blending and confusion +may well be the dominant source of uncertainty. \\ +The plan for the level-2 catalogs is that sources are hierarchically +deblended and that this hierarchy is maintained in the catalog. +Scientifically important decisions are still to be made about whether +and how to use color information in the deblending, and how to divide +the flux between overlapping components. Even if the Project is doing +the development work, engagement with the community is important for +developing tests and figures of merit to optimize the science return. +} +\activities{ +Preparations for LSST in this area involve working both with simulations +and real data. The current LSST image simulations already have realistic source densities, +redshift distributions, sizes, and color distributions. However, the +input galaxies do not have realistic morphologies. At least some simulations +with realistic morphologies are needed, especially for the Deep Drilling Fields. +Inputs should come both from hydrodynamical simulations (where ``truth'' is known), +{\it Hubble} images, and images from precursor surveys such as CFHTLS, DES and HyperSuprimeCam. +The science collaborations should help provide and vet inputs. \\ +More challenging is to come up with techniques and algorithms to improve the +deblending. When two galaxies at different redshifts overlap, using observations +from all the LSST filters and perhaps even EUCLID and WFIRST might +help to disentangle them. Some attempts have been made over the past few years +to incorporate color information into the deblending algorithm, but this needs +much more attention, not only for developing and testing algorithms, but for +deciding on figures-of-merit for their performance. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item providing realistic galaxy image inputs to the ImSim team; +\item developing tests and figures of merit to quantify the effects on several science objectives; +\item assessing the current baseline plan for level-2 deblending and for parameter estimation for blended objects; and +\item developing prototype implementations of deblending algorithms that take advantage of the LSST color information. +\end{enumerate} +} +\end{task} + +\tasktitle{Optimizing Galaxy Morphology Measurements} +% techniques for identifying mergers +% Bayesian techniques for inference from large data sets +% Merging human classification and machine learning +\begin{task} +\label{task:gal:morphology} +\motivation{ +Measurements of galaxy morphologies are an important tool for constraining models +of galaxy evolution. While fairly simple measures of galaxy ellipticity and position +angles may be sufficient for the Dark Energy science goals, other kinds of +measurements are needed for galaxy-evolution science. The ``multifit'' approach of +fitting simple parametric models to galaxy profiles has been the baseline plan. +This will be useful but insufficient. For well-resolved galaxies it is desirable +to have separate measures of bulge and disk, and spiral-arm structure, measures of +concentration, asymmetry, and clumpiness. These ought to be measured as part of +the level 2 processing, to enable database queries to extract subclasses of galaxies. +Both parametric and non-parametric measures are desirable. +While there will no doubt be optimization in level 3 processing, it is important +to have enough information in the level 2 output products to pick reasonable subsets +of galaxies. +} +\activities{The preparation work, therefore, focuses on defining measures to enable +these queries. Two aspects of LSST data make this a significant research project: +the fact that LSST provides multi-band data with a high degree of uniformity, and the +fact that the individual observations will have varying point-spread functions. +The former offers the opportunity to use much more information than has been +generally possible. The latter means that it will take some effort to optimize and +calibrate the traditional non-parametric measure of morphology (e.g. the CAS, GINI and M20 parameters), +develop new LSST-optimized parameters, and optimize their computation to avoid +taxing the level-2 pipeline.\\ +Given the very large data set and the uncertainty in how to use specific morphological +parameters to choose galaxies in certain physical classes (e.g. different merger +stages or stages of disk growth), it is important to have extensive +training both from hydrodynamical simulations +with dust (where physical truth is known, even if the models are imperfect) and +from observations where kinematics or other information provide a good +understanding of the physical nature of the object. These training sets ought to +be classified by humans (still the gold-standard for image classification) and via +machine-learning techniques applied to the morphological measurements. A series +of ``classification challenges'' prior to the LSST survey could help to refine the techniques. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item providing realistic galaxy image inputs for classification tests to the ImSim team; +\item human classification of the images; +\item machine-learning algorithms to be tested and developed into suitable SQL queries; +\item developing a menu of candidate morphological measurements for level 2 and level 3 processing; and +\item developing tests and figures of merit to quantify the effects on several science objectives. +\end{enumerate} +} +\end{task} + +\tasktitle{Optimizing Galaxy Photometry} +% background subtraction +% optimal co-adds +% best flux estimator +% image quality metrics +% forced photometry with separate central point source (important for AGN) +% Using high-resolution priors where available +\begin{task} +\label{task:gal:photometry} +\motivation{ +Systematic uncertainties will dominate over random uncertainties for almost any +research question one can imagine addressing with LSST. The most basic measurement +of a galaxy is its flux in each band, but this is a remarkably subtle measurement +for a variety of reasons: galaxies do not have well-defined edges, their shapes +vary, they have close neighbors, they cluster together, and lensing affects both +their brightness and clustering. These factors all affect photometry in systematic +ways, potentially creating spurious correlations that can obscure or masquerade as +astrophysical effects. For example, efforts to measure the effect of neighbors +on galaxy star-formation rates can be thrown off if the presence of a neighbor +affects the basic photometry. Measurements of galaxy magnification or measurements +of intergalactic dust can be similarly affected by systematic photometric biases. +It is thus important to hone the photometry techniques prior to the survey to +minimize and characterize the biases. Furthermore, there are science topics that +require not just photometry for the entire galaxy, but well-characterized photometry +for sub-components, such as a central point-source or a central bulge. +} +\activities{ +The core photometry algorithms will end up being applied in level 2 processing, +so it is important that photometry be vetted for a large number of potential +science projects before finalizing the software. Issues include the following. +(1) Background estimation, which, for example, can greatly affect the photometry +for galaxies in clusters or dwarfs around giant galaxies. (2) Quantifying the +biases of different flux estimators vs. (for example) distances to and fluxes +of their neighbors. (3) Defining optimal strategies to deal with the varying +image quality. (4) Defining a strategy for forced photometry of a central point +source. For time-varying point-sources, the image subtractions will give a +precise center, but will only measure the AC component of the flux. Additional +measurements will be needed to give the static component. (5) Making use +of high-resolution priors from either Euclid or WFIRST, when available. +Because photometry is so central to much of LSST science, there will need to +be close collaboration between the LSST Project and the community. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item developing metrics for various science cases to help evaluate the level 2 photometry; +\item providing realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies); +\end{enumerate} +Deliverables over the longer term include develping optimal techniques for forced photometry +using priors from the space missions. +} +\end{task} + +\tasktitle{Optimizing Measurements of Stellar Population Parameters} +% Strategies for dealing with strong covariance of parameter estmates +\begin{task} +\label{task:gal:stellarpops} +\motivation{ +The colors of galaxies carry information about their star-formation histories, +each interval of redshift being a snapshot of star-formation up until that time. +Unfortunately, estimates of star-formation rates and star-formation histories +for a single galaxy based on only the LSST bands will be highly uncertain, +due largely to degeneracies between age, dust extinction and metallicity. +Strategies for overcoming the degeneracies include hierarchical modeling -- using +ensembles of galaxies to constrain the hyper-parameters that govern +the star-formation histories of sets of galaxies rather than individuals, +and using ancillary data from other wavelengths. +} +\activities{ +Activities in this area include developing scalable techniques for +hierarchical Bayesian inference on very large data sets. These can be +tested on semi-analytical or hydrodynamical models, where the answer is known, +even if it does not correctly represent galaxy evolution. The models should +also be analyzed to find simple analytical expressions for star-formation +histories, chemical evolution and the evolution and behavior of dust to +make the Bayesian inference practical.\\ +Another important activity is to identify the ancillary data sets and +observing opportunities, especially for the deep fields. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item developing and refining techniques for constraining star-formation histories of large ensembles of galaxies; +\item providing model inputs to guide in developing these techniques; +\item refining the science requirements for ancillary multi-wavelength data to support LSST. +\end{enumerate} +} +\end{task} + +\tasktitle{Software Integration} +% Level 2 and Level 3 software +\begin{task} +\label{task:gal:integration} +\motivation{ +The LSST Project is responsible for level 2 data processing, and the community +is expected to any processing beyond that as level 3. Furthermore, some algorithms developed +as part of the level 3 effort are expected to migrate to level 2. There needs +to be strong coordination between the Project and the community for this concept +to work. This includes training in developing level 3 software and community engagement in +defining the requirements and interfaces. +} +\activities{ +The most urgent activity is to develop some early prototypes of level 3 software +so that the interfaces can be worked out on realistic use cases. +} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{Precursor Observations or Synergy with Other Facilities} \label{sec:tasks:gal:precursor} + +\begin{tasklist}{T} +\tasktitle{Redshift surveys in the Deep Drilling fields} +\begin{task} +\label{task:gal:redshift_surveys_dd_fields} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Ancillary Data in Deep Drilling fields} +\begin{task} +\label{task:gal:ancillary_data_dd_fields} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Photometric redshift training and calibration} +% Emphasize differences in requirements relative to DE +\begin{task} +\label{task:gal:photz_calibration} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Joint use of spectroscopic and photometric redshifts} +\begin{task} +\label{task:gal:spec_plus_phot_redshifts} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulations} + +\begin{tasklist}{T} +\tasktitle{Image simulations of galaxies with complex morphologies} +% Mergers +% Tidal features +% Stellar halos +% Vary the galaxy-evolution model +\begin{task} +\label{task:gal:image_simulations} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Rare objects} +% extreme over/underdensities +% massive early galaxies +% extremely supermassive black holdes +\begin{task} +\label{task:gal:rare_objects} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Cosmic Variance estimators} +% Develop simple tools...encourage their use +\begin{task} +\label{task:gal:cv_estimators} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Nearby dwarfs: surface brightness fluctuations} +\begin{task} +\label{task:gal:dwarf_sb_fluctuations} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Testing group and void finders} +\begin{task} +\label{task:gal:group_finders} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} + +\begin{tasklist}{T} +\tasktitle{Data structures to characterize survey biases and completeness} +\begin{task} +\label{task:gal:data_structures} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Queries to find unusual class of objects} +% mergers +% tidal streams +% nearby dwarf candidates +% morphologically disturbed close pairs +\begin{task} +\label{task:gal:queries} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Compact representations of likelihood functions} +\begin{task} +\label{task:gal:likelihoods} +\motivation{} +\activities{} +\end{task} + +\end{tasklist} diff --git a/old/galaxies/galaxies.tex.save b/old/galaxies/galaxies.tex.save new file mode 100644 index 0000000..d4932b2 --- /dev/null +++ b/old/galaxies/galaxies.tex.save @@ -0,0 +1,479 @@ +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: galaxies +% First draft by + +\section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} + +The LSST design, and to a certain extent the design of the data-management +system, is optimized to carry out the core science mission. For measurements +of dark-energy, that generally means treating galaxies as "tracer particles" -- +using statistical measures of ellipticity and position provide statistical +constraints on large-scale structure and cosmic geometry. While many of the +DESC tasks are directly relevant to studying galaxy evolution, they are +incomplete. In particular, studies of galaxy evolution require more attention to +optimizing multi-wavelength supporting data, different kinds of spectroscopy, different +kinds of simulations and theoretical support, and greater attention to detection +and characterization of low-surface brightness features or unusual morphologies. + +The task list presented here highlights the preparation work needed in the next 3-4 +years. Of primary importance are tasks that might influence the detailed survey +design or the algorithms used in the DM to construct catalogs. These are the most +urgent. Also included are activities that can be reasonably independent of the +LSST survey design and DM optimization, but which will ensure good support for +LSST galaxy studies. + +\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:precursor} + +\begin{tasklist}{T} +\tasktitle{Techniques for finding low-surface-brightness features or galaxies} +% Tidal streams +% Intracluster diffuse light +\begin{task} +\label{task:gal:lsb} +\motivation{ +A huge benefit of LSST relative to prior large-area surveys will be its ability to detect +low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and +other features associated with past and ongoing mergers, it includes intra-cluster and +intra-group light, and it includes relatively nearby, extended low-surface-brightness galaxies. +Prior to LSST, typical studies of the low-surface-brightness universe have focused +on relatively small samples, often selected by criteria that are difficult to quantify +or reproduce in theoretical models. Measurements of the LSB features themselves themselves +are challenging, often requiring hand-tuning and interactive scientific judgment. This is +important for accurately quantifying what we observe, but such interactive tuning +of the measurements (a) is not something that can be applied on the LSST scale and (b) +is difficult to apply to theoretical models. For LSST it is crucial that we automate +the detection and characterization of LSB features, at least to the point where samples +for further study can be selected via database queries, and where the completeness of +samples returned from such queries can be quantified. +} + +\activities{ +Several activities are of crucial importance: (1) simulating realistic LSB features, (2) +using the simulations to optimize detection and measurement, (3) ensuring that LSST +level-2 processing strategies and observing strategies are at least cognizant +of needs of LSB science and (4) developing a strategy for finding and measuring LSB features through +some combination of level 2 measurements, database queries, and level 3 processing.\\ +It is important to insert realistic low-surface-brightness +features into LSST simulated images and try to extract and measure them, exploring +different techniques or algorithms for doing the detection and measurement. Because the LSB objects +are sparse on the sky, making realistic LSST sky images is probably not the most efficient +way to accomplish this; more targeted simulations with a higher density of +LSB objects are needed. The simulated observations need to be realistic in their +treatment of scattered light, particularly scattering from bright stars which +may or may not be in the actual field of view of the telescope. +Scattering from bright stars is likely to be the primary source of contamination +when searching for extended LSB features. Ideally, the LSST scattered-light model, +tuned by repeated observations, will be sufficiently good that these contaminants +can be removed or at least flagged at level 2. Defining the metrics for ``sufficiently good,'' +based on analysis of simulations, is an important activity that needs early work to +help inform LSST development. Including Galactic cirrus in the simulations is important +for very large-scale LSB features. Including a cirrus model as part of the LSST background +estimation is worth considering, but it is unclear yet whether the science benefit +can justify the extra effort. \\ +Because the LSST source extraction is primarily +optimized for finding faint, barely-resolved galaxies, it is going to be challenging to +optimize simultaneously for finding large LSB structures and cataloging them as +one entity in the database. For very large structures, analysis of the LSST ``sky background'' +map, might be the most productive approach. We need to work with the LSST project +to make sure the background map is stored in a useful form, and that background +measurements from repeated observations can be combined to separate the fluctuating +foreground and scattered light from the astrophysically interesting signal from extended +LSB structures. Then, we need strategies for measuring these background maps, characterizing +structures, and developing value-added catalogs to supplement the level 2 database.\\ +For smaller structures, it is likely that the database will contain pieces +of the structure, either as portions of a hierachical +family of deblended objects, or cataloged as separate objects. Therefore, we need to +develop strategies for querying the database to find such structures and either extract +the appropriate data for customized processing, or develop ways to put back together +the separate entries in the database. A possible value-added catalog, for example, from +the galaxies collaboration might be an extra set of fields for the database to indicate +which separate objects are probably part of the same physical entity. This would +be sparsely populated in the first year or two of LSST, but by the end of the survey +could be a useful resource for a wide variety of investigations. +} + +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item realistic inputs of LSB galaxies or LSB features for the LSST image simulations; +\item custom simulations; +\item algorithms for finding and measuring LSB features; +\item input to the Project on scattered-light mitigation and modeling strategies; +\item input to the project on photometric and morphological parameters to measure/store at level 2; +\item query strategies and sample queries for finding LSB structures; and +\item a baseline concept for a value-added database of LSB structures +\end{enumerate} +} +\end{task} + +\tasktitle{Techniques for identifying and deblending overlapping galaxies} +\begin{task} +\label{task:gal:deblending} +\motivation{ +The Level 2 data products are the most relevant starting point +for galaxy-evolution science. In the LSST nomenclature, {\tt Objects} +represent astrophysical entities (stars, galaxies, quasars, etc.), while +{\tt Sources} represent their single-epoch observations. +The master list of Objects in Level 2 will be generated by associating +and deblending the list of single-epoch source detections and the +lists of sources detected on coadds. The exact strategies for doing +this are still under active development by the LSST project, and +engagement with the science community is essential. While each +data release will have unique object IDs, it will be a huge impediment +for LSST science if the first few generations of catalogs turn out +severely the limit the science that can be done via database queries. \\ +For galaxies science, the issue of deblending is of critical importance. +For example, searches for high-redshift galaxies via color selection +or photometric redshifts involve model or template spectra that make +the prior assumption that the object in question is a single object at +one redshift, not a blend of two objects at two different redshifts. +Therefore to get a reliable estimate of the evolution of classes of galaxies +over redshift, we need to (a) have reasonably clean catalogs to start with +and (b) be able to model the effects of blending on the sample selection +and derivation of redshift and other parameters. This is critical +not just for galaxy-evolution science, but for lensing and large-scale +structure studies. This is just one example. Another is the evolution +of galaxy morphologies, where the effects of blending and confusion +may well be the dominant source of uncertainty. \\ +The plan for the level-2 catalogs is that sources are hierarchically +deblended and that this hierarchy is maintained in the catalog. +Scientifically important decisions are still to be made about whether +and how to use color information in the deblending, and how to divide +the flux between overlapping components. Even if the Project is doing +the development work, engagement with the community is important for +developing tests and figures of merit to optimize the science return. +} +\activities{ +Preparations for LSST in this area involve working both with simulations +and real data. The current LSST image simulations already have realistic source densities, +redshift distributions, sizes, and color distributions. However, the +input galaxies do not have realistic morphologies. At least some simulations +with realistic morphologies are needed, especially for the Deep Drilling Fields. +Inputs should come both from hydrodynamical simulations (where ``truth'' is known), +{\it Hubble} images, and images from precursor surveys such as CFHTLS, DES and HyperSuprimeCam. +The science collaborations should help provide and vet inputs. \\ +More challenging is to come up with techniques and algorithms to improve the +deblending. When two galaxies at different redshifts overlap, using observations +from all the LSST filters and perhaps even EUCLID and WFIRST might +help to disentangle them. Some attempts have been made over the past few years +to incorporate color information into the deblending algorithm, but this needs +much more attention, not only for developing and testing algorithms, but for +deciding on figures-of-merit for their performance. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item providing realistic galaxy image inputs to the ImSim team; +\item developing tests and figures of merit to quantify the effects on several science objectives; +\item assessing the current baseline plan for level-2 deblending and for parameter estimation for blended objects; and +\item developing prototype implementations of deblending algorithms that take advantage of the LSST color information. +\end{enumerate} +} +\end{task} + +\tasktitle{Optimizing Galaxy Morphology Measurements} +% techniques for identifying mergers +% Bayesian techniques for inference from large data sets +% Merging human classification and machine learning +\begin{task} +\label{task:gal:morphology} +\motivation{ +Measurements of galaxy morphologies are an important tool for constraining models +of galaxy evolution. While fairly simple measures of galaxy ellipticity and position +angles may be sufficient for the Dark Energy science goals, other kinds of +measurements are needed for galaxy-evolution science. The ``multifit'' approach of +fitting simple parametric models to galaxy profiles has been the baseline plan. +This will be useful but insufficient. For well-resolved galaxies it is desirable +to have separate measures of bulge and disk, and spiral-arm structure, measures of +concentration, asymmetry, and clumpiness. These ought to be measured as part of +the level 2 processing, to enable database queries to extract subclasses of galaxies. +Both parametric and non-parametric measures are desirable. +While there will no doubt be optimization in level 3 processing, it is important +to have enough information in the level 2 output products to pick reasonable subsets +of galaxies. +} +\activities{The preparation work, therefore, focuses on defining measures to enable +these queries. Two aspects of LSST data make this a significant research project: +the fact that LSST provides multi-band data with a high degree of uniformity, and the +fact that the individual observations will have varying point-spread functions. +The former offers the opportunity to use much more information than has been +generally possible. The latter means that it will take some effort to optimize and +calibrate the traditional non-parametric measure of morphology (e.g. the CAS, GINI and M20 parameters), +develop new LSST-optimized parameters, and optimize their computation to avoid +taxing the level-2 pipeline.\\ +Given the very large data set and the uncertainty in how to use specific morphological +parameters to choose galaxies in certain physical classes (e.g. different merger +stages or stages of disk growth), it is important to have extensive +training both from hydrodynamical simulations +with dust (where physical truth is known, even if the models are imperfect) and +from observations where kinematics or other information provide a good +understanding of the physical nature of the object. These training sets ought to +be classified by humans (still the gold-standard for image classification) and via +machine-learning techniques applied to the morphological measurements. A series +of ``classification challenges'' prior to the LSST survey could help to refine the techniques. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item providing realistic galaxy image inputs for classification tests to the ImSim team; +\item human classification of the images; +\item machine-learning algorithms to be tested and developed into suitable SQL queries; +\item developing a menu of candidate morphological measurements for level 2 and level 3 processing; and +\item developing tests and figures of merit to quantify the effects on several science objectives. +\end{enumerate} +} +\end{task} + +\tasktitle{Optimizing Galaxy Photometry} +% background subtraction +% optimal co-adds +% best flux estimator +% image quality metrics +% forced photometry with separate central point source (important for AGN) +% Using high-resolution priors where available +\begin{task} +\label{task:gal:photometry} +\motivation{ +Systematic uncertainties will dominate over random uncertainties for almost any +research question one can imagine addressing with LSST. The most basic measurement +of a galaxy is its flux in each band, but this is a remarkably subtle measurement +for a variety of reasons: galaxies do not have well-defined edges, their shapes +vary, they have close neighbors, they cluster together, and lensing affects both +their brightness and clustering. These factors all affect photometry in systematic +ways, potentially creating spurious correlations that can obscure or masquerade as +astrophysical effects. For example, efforts to measure the effect of neighbors +on galaxy star-formation rates can be thrown off if the presence of a neighbor +affects the basic photometry. Measurements of galaxy magnification or measurements +of intergalactic dust can be similarly affected by systematic photometric biases. +It is thus important to hone the photometry techniques prior to the survey to +minimize and characterize the biases. Furthermore, there are science topics that +require not just photometry for the entire galaxy, but well-characterized photometry +for sub-components, such as a central point-source or a central bulge. +} +\activities{ +The core photometry algorithms will end up being applied in level 2 processing, +so it is important that photometry be vetted for a large number of potential +science projects before finalizing the software. Issues include the following. +(1) Background estimation, which, for example, can greatly affect the photometry +for galaxies in clusters or dwarfs around giant galaxies. (2) Quantifying the +biases of different flux estimators vs. (for example) distances to and fluxes +of their neighbors. (3) Defining optimal strategies to deal with the varying +image quality. (4) Defining a strategy for forced photometry of a central point +source. For time-varying point-sources, the image subtractions will give a +precise center, but will only measure the AC component of the flux. Additional +measurements will be needed to give the static component. (5) Making use +of high-resolution priors from either Euclid or WFIRST, when available. +Because photometry is so central to much of LSST science, there will need to +be close collaboration between the LSST Project and the community. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item developing metrics for various science cases to help evaluate the level 2 photometry; +\item providing realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies); +\end{enumerate} +Deliverables over the longer term include develping optimal techniques for forced photometry +using priors from the space missions. +} +\end{task} + +\tasktitle{Optimizing Measurements of Stellar Population Parameters} +% Strategies for dealing with strong covariance of parameter estmates +\begin{task} +\label{task:gal:stellarpops} +\motivation{ +The colors of galaxies carry information about their star-formation histories, +each interval of redshift being a snapshot of star-formation up until that time. +Unfortunately, estimates of star-formation rates and star-formation histories +for a single galaxy based on only the LSST bands will be highly uncertain, +due largely to degeneracies between age, dust extinction and metallicity. +Strategies for overcoming the degeneracies include hierarchical modeling -- using +ensembles of galaxies to constrain the hyper-parameters that govern +the star-formation histories of sets of galaxies rather than individuals, +and using ancillary data from other wavelengths. +} +\activities{ +Activities in this area include developing scalable techniques for +hierarchical Bayesian inference on very large data sets. These can be +tested on semi-analytical or hydrodynamical models, where the answer is known, +even if it does not correctly represent galaxy evolution. The models should +also be analyzed to find simple analytical expressions for star-formation +histories, chemical evolution and the evolution and behavior of dust to +make the Bayesian inference practical.\\ +Another important activity is to identify the ancillary data sets and +observing opportunities, especially for the deep fields. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item developing and refining techniques for constraining star-formation histories of large ensembles of galaxies; +\item providing model inputs to guide in developing these techniques; +\item refining the science requirements for ancillary multi-wavelength data to support LSST. +\end{enumerate} +} +\end{task} + +\tasktitle{Software Integration} +% Level 2 and Level 3 software +\begin{task} +\label{task:gal:integration} +\motivation{ +The LSST Project is responsible for level 2 data processing, and the community +is expected to any processing beyond that as level 3. Furthermore, some algorithms developed +as part of the level 3 effort are expected to migrate to level 2. There needs +to be strong coordination between the Project and the community for this concept +to work. This includes training in developing level 3 software and community engagement in +defining the requirements and interfaces. +} +\activities{ +The most urgent activity is to develop some early prototypes of level 3 software +so that the interfaces can be worked out on realistic use cases. +} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{Precursor Observations or Synergy with Other Facilities} \label{sec:tasks:gal:precursor} + +\begin{tasklist}{T} +\tasktitle{Redshift surveys in the Deep Drilling fields} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Spitzer observations of Deep Drilling fields} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{VLA observations of Deep Drilling fields} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Photometric redshift training and calibration} +% Emphasize differences in requirements relative to DE +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Joint use of spectroscopic and photometric redshifts} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulations} + +\begin{tasklist}{T} +\tasktitle{Image simulations of galaxies with complex morphologies} +% Mergers +% Tidal features +% Stellar halos +% Vary the galaxy-evolution model +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Rare objects} +% extreme over/underdensities +% massive early galaxies +% extremely supermassive black holdes +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Cosmic Variance estimators} +% Develop simple tools...encourage their use +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Nearby dwarfs: surface brightness fluctuations} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Testing group and void finders} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} + +\begin{tasklist}{T} +\tasktitle{Data structures to characterize survey biases and completeness} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + + +\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} + +\begin{tasklist}{T} +\tasktitle{Data structures to characterize survey biases and completeness} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Queries to find unusual class of objects} +% mergers +% tidal streams +% nearby dwarf candidates +% morphologically disturbed close pairs +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Compact representations of likelihood functions} +\begin{task} +\label{task:gal:XXX} +\motivation{} +\activities{} +\end{task} + +\end{tasklist} diff --git a/old/informatics/informatics.tex b/old/informatics/informatics.tex new file mode 100644 index 0000000..feae3e0 --- /dev/null +++ b/old/informatics/informatics.tex @@ -0,0 +1,8 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: informatics +% First draft by + +\section{Astroinformatics Task Lists}\label{sec:tasks:ai:intro} + diff --git a/old/lss/lss.tex b/old/lss/lss.tex new file mode 100644 index 0000000..a6eb3b3 --- /dev/null +++ b/old/lss/lss.tex @@ -0,0 +1,8 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: lss +% First draft by + +\section{Large Scale Structure Task Lists}\label{sec:tasks:lss:into} + diff --git a/old/strong_lensing/strong_lensing.tex b/old/strong_lensing/strong_lensing.tex new file mode 100644 index 0000000..32c2ff9 --- /dev/null +++ b/old/strong_lensing/strong_lensing.tex @@ -0,0 +1,8 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: strong_lensing +% First draft by + +\section{Strong Lensing Task Lists}\label{sec:tasks:sl:intro} + diff --git a/old/task_lists.tex b/old/task_lists.tex new file mode 100644 index 0000000..683ce8c --- /dev/null +++ b/old/task_lists.tex @@ -0,0 +1,22 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% First draft by + +\chapter[Task Lists by Science Area]{Task Lists by Science Area} +\label{ch:task_lists} + +\input{task_lists/chapter_intro.tex} + +\input{task_lists/black_holes/black_holes.tex} + +\input{task_lists/galaxies/galaxies.tex} + +\input{task_lists/informatics/informatics.tex} + +\input{task_lists/lss/lss.tex} + +\input{task_lists/strong_lensing/strong_lensing.tex} + +\input{task_lists/weak_lensing/weak_lensing.tex} + diff --git a/old/weak_lensing/weak_lensing.tex b/old/weak_lensing/weak_lensing.tex new file mode 100644 index 0000000..f8afe09 --- /dev/null +++ b/old/weak_lensing/weak_lensing.tex @@ -0,0 +1,8 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: weak_lensing +% First draft by + +\section{Weak Lensing Task Lists}\label{sec:tasks:wl:intro} + diff --git a/structure.tex b/structure.tex index 19cbbb1..c883372 100644 --- a/structure.tex +++ b/structure.tex @@ -80,7 +80,9 @@ \usepackage{xcolor} % Required for specifying colors by name %\definecolor{ocre}{RGB}{243,102,25} % Define the orange color used for highlighting throughout the book -\definecolor{ocre}{RGB}{119,181,254} % Define the orange color used for highlighting throughout the book +%\definecolor{ocre}{RGB}{119,181,254} % Define the orange color used for highlighting throughout the book +\definecolor{ocre}{RGB}{3,22,168} % Define the orange color used for highlighting throughout the book + \usepackage{listings} \usepackage{color} @@ -514,7 +516,8 @@ \node at (current page.north west) {\begin{tikzpicture}[remember picture,overlay] \node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; -\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +%rounded box +%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; \draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}\thechapter. #1\strut}; \end{tikzpicture}}; \end{tikzpicture} @@ -523,7 +526,8 @@ \node at (current page.north west) {\begin{tikzpicture}[remember picture,overlay] \node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; -\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +%rounded box +%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; \draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; \end{tikzpicture}}; \end{tikzpicture} @@ -536,11 +540,14 @@ \node at (current page.north west) {\begin{tikzpicture}[remember picture,overlay] \node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; -\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +%rounded box +%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; \draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; \end{tikzpicture}}; \end{tikzpicture} -\par\vspace*{270\p@}} +%\par\vspace*{270\p@}} +\par\vspace*{170\p@}} +%\par\vspace*{100\p@}} \makeatother %---------------------------------------------------------------------------------------- diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex new file mode 100644 index 0000000..6cb2abf --- /dev/null +++ b/task_lists/agn/agn.tex @@ -0,0 +1,127 @@ +\section{Active Galactic Nuclei Task Lists}\label{sec:tasks:agn:intro} + +AGN are phenomena that enable us to understand the growth of BHs, understand aspects of galaxy evolution, probe the high redshift universe and study other physical activity, including accretion physics, jets, magnetic fields, etc. There are distinct aspects of the study of AGN that can best be explored by considering AGN as an evolutionary stage of galaxies rather than a distinct type of source. The tasks listed here explore aspects of AGN study that are particularly important AGN as a stage in galaxy evolution. + +\begin{tasklist}{T} +\tasktitle{AGN feedback in clusters} +\begin{task} +\label{task:agn:feedback_in_clusters} +\motivation{ +Brightest Cluster/Group Galaxies (hereafter BCGs) are the most massive galaxies in the local Universe residing at/near the centres of galaxy clusters/groups. They will therefore contain the largest supermassive black holes. These black holes can influence their host BCG, the cluster gas and other cluster members via the mechanical energy produced by their 100s kpc scale jets (AGN feedback). +\\ +For low redshift galaxy clusters it is possible to perform detailed studies of the star, gas and AGN jets to analyse the details of AGN feedback. LSST will provide a large sample of moderate to high redshift clusters in which we can measure AGN feedback statistically. By combining X-ray, radio and optical observations we can assess the average influence of the BCG's AGN on the hot Intra-cluster medium (ICM) for different sub-populations [e.g. Stott et al. 2012]. +} +\activities{ +By assembling a multi-wavelength dataset (optical, X-ray, Radio) we can obtain the BCG mass, cluster mass and ICM temperature, and the mechanical power injected into the ICM. We can use this to study the interplay between the BCG, its black hole and the cluster gas, to assess the balance of energies involved and for direct comparison with theoretical models of AGN feedback. This has been done with a few hundred clusters at z<0.3 using SDSS but we may well be able to reach z=1 and therefore look for an evolution in their interplay and therefore AGN feedback. There are also implications for cosmology too as this will help with the selection of clusters for which the X-ray properties better represent the mass of the cluster rather than the complex interplay of baryonic physics. } + +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Investigate the number of BCGs and the mass range of their clusters with redshift that LSST is likely to be able to observe. +\item Assess radio and X-ray data available for AGN Feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS etc). +\item Assess the theoretical predictions expected for the above (e.g. cosmological simulations such as EAGLE or more detailed single cluster studies). +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{AGN Selection from LSST Data} +\begin{task} +\label{task:agn:selection} +\motivation{ +Active Galactic Nuclei are selected using a variety of different methods. At optical and infrared wavelengths, photometric selection of AGN candidates is driven by their distinctive colors at particular redshifts. X-ray and radio observations can also be efficient selectors of candidates for additional follow-up. With spectral data, AGN can be selected using the ratios of their emission lines. LSST will also open up, in a more practical way, the identification of AGN based on their variability. +Each of these samples probes aspects of the AGN phenomena and a better understanding of the AGN role in galaxy evolution requires that we understand how and why each of these selection methods includes or excludes particular sources. Furthermore, currently each of these methods for identifying AGN candidates requires spectral follow-up to cull these samples to positively identify the most reliably clean AGN sample. +} +\activities{ +For us to use LSST as a single way to identify the diversity of AGN, we must develop selection criteria that take advantage of the source parameters available with just LSST imaging, that is, color, morphology and variability. Already there are a number of AGN surveys with input from multiple wavelength observation and spectra. Precursor work needs to be done using these surveys to determine if AGN not easily identified using optical color selection can be selected using the additional parameters of morphology, variability and/or the additional filter that LSST provides. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Cross-matched catalog of known AGN selected and verified using different methods +\item Development of morphology parameters beyond just star/galaxy separation and an understanding of the morphology parameters to be provided by LSST level 2 products. +\item Development of color selection criteria that takes into account the morphology of the source +\item Understanding of how AGN variability looks given the nominal LSST cadence +\item Development of algorithms for color selection that take into account the variability of an AGN source +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{AGN Host Galaxy Properties from LSST Data} +\begin{task} +\label{task:agn:host_galaxies} +\motivation{ +We are requesting that basic morphological parameters (e.g., CAS, G-M20, etc.) be measured in the pipeline and made available as products to help in the identification of merging galaxies in LSST data. The issue here is how well this can be done when the host galaxies contain AGN that are likely identified via their variability. In other words, how well can we determine the host morphology of galaxies with variable AGN? This would be interesting for models of AGN fueling during mergers. +} +\activities{ +Simulations of the accuracy by which the pipeline (deblender) can measure the defined morphology parameters in host galaxies as a function of AGN brightness and wavelength. We could then ``vary'' the central source by expected levels in certain filters to see the effect on the morphological params. To constrain this it would be helpful to add in central sources with reasonable SEDs across the LSST bands, and a limited set of frequencies/amplitudes (based on real data - perhaps Pan-STARRS?). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Plots of the accuracy of the measured basic morphology parameters as a function of AGN brightness and wavelength. +\item Effect of AGN brightness on classification diagrams. +\end{enumerate} +} +\end{task} +\end{tasklist} + +\begin{tasklist}{T} +\tasktitle{AGN Variability Selection in LSST Data} +\begin{task} +\label{task:agn:variability} +\motivation{ +Most AGN exhibit broad-band aperiodic, stochastic variability across the entire EM spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, making it a powerful probe of accretion physics. The main LSST WFD survey will obtain $\sim10^8$ AGN light curves (i.e. flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. The deep drilling fields will give us AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will critically depend on the interval between observations in individual filter bands. It is of crucial importance to determine guidelines for an optimal survey strategy (from an AGN variability perspective) and determine what biases and uncertainties are introduced into AGN variability science as a result of the chosen survey strategy.} +\activities{ +Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate \& study simulations using parameters selected from these models with the observationally determined constraints to determine goodness of simulations for carrying out various types of AGN variability science - PSD models, QPO searches, binary AGN models, etc. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Observational constraints on AGN variability models. +\item MAF metrics quantifying the goodness of different survey strategies for AGN variability science. +\end{enumerate} +} +\end{task} +\end{tasklist} + +\begin{tasklist}{T} +\tasktitle{AGN Photometric Redshifts from LSST Data} +\begin{task} +\label{task:agn:photoz} +\motivation{ +Given the large number of AGN that will be observed with LSST, many of these will not be followed up with spectral observations. However, understanding the large scale structure of the universe, requires a 3-D understanding of the distribution of these galaxies in the universe. Photometric redshifts can provide relatively accurate redshifts for large numbers of galaxies. However, it is harder to obtain accurate photometric redshifts for galaxies that contain AGN compared to those that do not. We must understand how to get accurate photometric redshifts of galaxies with AGN. +} +\activities{ +An initial activity for this need to include comprehensive review of the state of the art in obtaining photo-z’s for AGN host galaxy populations and how those compare to non-AGN galaxies. A comparison of model and/or observed AGN host SEDs with a matched set of non-host galaxies at a variety of redshifts will be used to determine color selection criteria for identifying AGN hosts. Explore whether variability can be used to break degeneracies. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Plots that show AGN host color selection criteria and where that color selection might become ambiguous (be degenerate) for non-host galaxies with different parameters. +\item Plots that show if other parameters might break degeneracies. +\end{enumerate} +} +\end{task} +\end{tasklist} + +\begin{tasklist}{T} +\tasktitle{AGN Merger Signature from LSST Data} +\begin{task} +\label{task:agn:mergers} +\motivation{ +Understanding the role AGN play in galaxy evolution requires identifying the phenomenon at all stages and in all types of galaxies. AGN host galaxies are often found to be disturbed suggesting that the galaxy merger process is an important trigger of AGN activity. While the ‘trainwrecks’ may be easier to find, galaxies in other merger stages can be difficult to identify and those experiencing ‘pre-merger’ harassment may be particularly hard to recognize. Preliminary work needs to be done to understand how to identify mergers from the LSST data products and whether galaxy deblending and segmentation methods and procedures are adequate or mask galaxy mergers. +} +\activities{ +Create or Identify simulated and real images that contain known galaxy mergers, these images should contain mergers with and without AGN. +Run LSST detection and identification software on these images. +Identify metrics that describe/quantify the accurate detection of galaxy mergers (with and without AGN). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Give feedback to LSST software teams about metrics and detection of galaxy mergers +\item Give feedback on structure or galaxy type that do and do not work well with current versions of LSST software +\end{enumerate} +} +\end{task} +\end{tasklist} \ No newline at end of file diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index 683ce8c..54e214f 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -6,17 +6,12 @@ \chapter[Task Lists by Science Area]{Task Lists by Science Area} \label{ch:task_lists} -\input{task_lists/chapter_intro.tex} - -\input{task_lists/black_holes/black_holes.tex} - -\input{task_lists/galaxies/galaxies.tex} - -\input{task_lists/informatics/informatics.tex} - -\input{task_lists/lss/lss.tex} - -\input{task_lists/strong_lensing/strong_lensing.tex} - -\input{task_lists/weak_lensing/weak_lensing.tex} - +%\input{task_lists/chapter_intro.tex} +%\input{task_lists/black_holes/black_holes.tex} +%\input{task_lists/informatics/informatics.tex} +%\input{task_lists/lss/lss.tex} +%\input{task_lists/strong_lensing/strong_lensing.tex} +%\input{task_lists/weak_lensing/weak_lensing.tex} + +\input{task_lists/agn/agn.tex} +%\input{task_lists/galaxies/galaxies.tex} From eb86caa6c64bfe42f42cc0d88f26cbeec6a034f4 Mon Sep 17 00:00:00 2001 From: Brant Robertson 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Variations in the telescope system, particularly the broad-band ugrizy filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of local environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane. Such corrections will be SED dependent, and may leave residuals, particularly for specific populations with unusual SEDs. Tests of the amplitude of these residuals, and the impact on photo-z as a whole, and for particular object classes, is an important consideration. Beyond this, if the variations turn out to be very well calibrated, they could potentially be used to further improve, rather than degrade, photo-z performance. The variations in filter response can offer up additional a small amount of extra information on the object SED, given the slight variation in effective filter wavelength, particularly for objects with strong narrow features, i.e. emission lines. Tests of how much information is gained can inform whether or not the extra computational effort used in computing photo-z’s from many slightly different filters as opposed to measurements corrected to the six fiducial filters of the survey. +} +\activities{ +XXX} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} +\end{tasklist} + +\begin{tasklist}{T} +\tasktitle{Photometric Reshifts in the LSST Deep Drilling Fields} +\begin{task} +\label{task:photo_z:ddf} +\motivation{ +The LSST Deep Drilling Fields present different challenges than the main survey, including more confusion between sources, and the ability to use the best subsets of the images due to their being many repeat observations. These properties allow investigations of galaxies of brightness close to the noise in the main survey at higher signal to noise. +} +\activities{ +Assessing robustness of photo-zs with spectroscopic surveys will be difficult at the faintest fluxes, relationship to clustering redshifts important. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} +\end{tasklist} + +\begin{tasklist}{T} +\tasktitle{Multivariate Physical Properties of Galaxies from Photometric Redshifts} +\begin{task} +\label{task:photo_z:physical_properties} +\motivation{ +The knowledge of the derived physical properties underlies much of the work involving galaxies and their evolution. Derived physical properties include, among others: star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity. When it comes to scientific analysis, in recent years the derived physical properties have largely supplanted fluxes and luminosities in the UV, optical and near-IR bands. This is because derived properties require no redshift (K) corrections, are dust-corrected, and are therefore easier to relate across surveys and studies and to compare with the models. Stellar mass has emerged as a parameter of choice for selecting galaxy types and making apple-to-apple comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a rough estimate of galaxy’s SF history. Dust attenuation and stellar metallicity are also indicative of various processes important for understanding galaxy evolution. +} +\activities{ +Deriving physical properties, usually accomplished by spectral energy distribution (SED) fitting, is an involved process and the results depend on the number of factors, including: underlying population models, assumed dust attenuation law, assumed star formation histories, choice of model priors, choice of IMF, emission line corrections, choice of input fluxes, type of flux measurements, treatment of flux errors, SED fitting methodology, interpretation of the resulting probability distribution functions (PDF) (e.g., Salim et al. 2016). In the case of LSST, the additional challenge is that the redshifts are for the most part photometric, and carry a PDF (a measure of uncertainty) of their own. In principle, the redshifts could be determined as part of the SED fitting (and vice versa, physical parameters can be obtained from some photo-z codes), but it is not clear whether this joint approach is the best. Alternatives are to use empirical training sets to obtain the photo-z (some “best” estimate or a PDF) and then feed it into the SED fitting code. +\\ +Activities will consist of testing whether the determination of physical parameters and photo-z should be performed jointly or not, based on training sets with spectroscopic redshifts, at a range of redshifts. Furthermore, testing should be performed on mock galaxies to understand which choices of methods and assumptions (specifically related to LSST data) produces the best results in the sense of retrieving the “known” properties. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-z and properties, together with the software to be used. +\item With LSST data: the production of catalogs of properties to be used by the collaboration. +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Identifying Spectroscopic Redshift Training Sets for LSST} +\begin{task} +\label{task:photo_z:specz_training_sets} +\motivation{ +Require deep spectroscopic redshift data in order to help train algorithms, improve algorithms with clustering etc, and also provide a basis for determining accuracy of photo-z algorithms. +} +\activities{Collate existing spectroscopic redshift data over both DDF and wider fields, along with selection biases for each spectroscopic data set. Assess robustness of existing data, determine colour space where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Develop Techniques to Identify Specific Sub-Populations of Galaxies} +\begin{task} +\label{task:photo_z:subpops} +\motivation{ Studying properties related with the star formation activity of galaxies, such as color and specific star formation rate (sSFR), as a function of mass, environment and redshift is relevant for understanding the different physical processes in galaxy formation and evolution. The aim is to develop techniques in order to identify specific sub-populations with the aforementioned properties (e.g. blue/star-forming and red/quenched galaxies) based on photometric data. Another interesting sub-population is galaxies which contain an active nucleus. The identification of AGN candidates will also be explored. +\\ +This task is potentially cross-cutting with the theory/mock catalogs, machine learning, clusters, lss, AGN, and DESC working groups and collaborations. +} +\activities{ +We can use simulations and mock catalogs to obtain prior estimates of the calibrations used to identify specific galaxy sub-populations. These calibrations will depend on mass and redshift (z). One technique to explore is fitting two Gaussians to the corresponding color and sSFR distributions in different mass and redshift bins to identify populations of red and blue galaxies. It is important that the mass definition assumed in the mocks be comparable to that estimated for observations. Note that the stellar mass would be used as the alpha parameter in the joint probability distribution functions, p(z,alpha). +\\ +Furthermore, we will make efforts to identify AGNs to obtain a sample of AGN candidates and, also, isolate them from “normal” galaxy samples without AGNs. The information of color and star formation described above can be used for this aim. +\\ +The techniques can be probed as a function of environment, which can be defined using different approaches at both small and large scales (e.g. number of neighbor galaxies, location in large-scale structures such as filaments, voids, knots, or Voronoi tessellation techniques). This would enable the characterization of galaxy sub-populations according to the environment. The resulting galaxy sub-populations can be used as training sets to be implemented on machine learning models. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Obtaining mass from mock catalogs compatible with the mass used in p(z,mass). +\item Developing techniques that depend on this mass and redshift using mock catalogs for selecting samples with red/blue colors. +\item Developing multiple techniques that depend on this mass and redshift using mock catalogs for selecting star-forming/quenched samples. +\item Developing techniques that may depend on star formation, color and redshift for selecting AGN samples. +\item Defining several environment estimators in simulated datasets. +\item Probing techniques in b), c) and d) as a function of the environments defined in e). +\item Obtaining training sets to be implemented on machine learning models. +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Simulations with Realistic Galaxy Colors and Physical Properties} +\begin{task} +\label{task:photo_z:color_simulations} +\motivation{ +As representative samples of spectroscopic redshifts will be very difficult to compile for LSST, simulations will play a key role in calibrating estimates of physical properties such as galaxy stellar mass, star formation rate, and other properties. This is particularly problematic for photometric surveys, where photometric redshift and physical property estimates must be calculated jointly. In addition, we must include prominent effects that will influence the expected photometric performance, for example the presence of an active galactic nucleus can significantly impact the color of a galaxy and the inferred values for the physical parameters, so models of AGN components of varying strength must be included in the simulations. Many current generation simulations cannot or do not simultaneously match observed color distributions and physical property characteristics for the galaxy population at high redshift. As photo-z algorithms are highly dependent on accurate photometry, realistic color distributions are required to test the bivariate redshift-physical property estimates. Working with the galaxy simulations and high redshift galaxy working groups to develop new simulations with more accurate high redshift colors is a priority. These photo-z needs are not unique, and the improved simulations will benefit the wider Collaboration as a whole. +} +\activities{ +The main activity for this task is to bring together the knowledge gained from observational studies of high redshift galaxies to act as input for improved simulation metrics. This will require expertise from the photo-z group, the high redshift galaxies group, the AGN group, and the simulations group. In order to test whether mock high-z populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions. Assuming that the simulations are valid beyond the test intervals, we can then test bivariate photo-z/physical process determinations to develop improved algorithms. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Determination of a list of which physical parameters are important for galaxy science. +\item Compiling observable datasets that can be used as comparators for simulated datasets. +\item Developing a set of metrics to compare simulations to the observational data. +\item Use the metrics in deliverable B to create updated simulations with more realistic parameter distributions. +\item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc…). +\end{enumerate} +} +\end{task} +\end{tasklist} + +\begin{tasklist}{T} +\tasktitle{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} +\begin{task} +\label{task:photo_z:size_and_sb_priors} +\motivation{ +Photometric redshift algorithms traditionally use galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information in the form of the galaxy’s size/shape/surface brightness (SB) profile adds additional information that can aid in constraining both the redshift and type of the galaxy, breaking potential degeneracies that using colors alone would miss. Adding type information beyond just the rest frame SED may help to constrain bivariate galaxy properties that correlate with morphological type as well. If sufficient training samples are available, a Bayesian prior on colors and SB profile, p(z|C,SB), can be constructed that should lead to improved photometric redshifts. +} +\activities{ +The primary activity in this task is to develop an algorithm to compute a parameterized SB profile fit (e.g. Sersic index, though other measures may be appropriate) for a large number of galaxies. The algorithm must be fast enough to compute SB profiles for large numbers of galaxies. Simulated datasets may be necessary to calibrate this code in the limits of galaxy sizes approaching the size of the PSF, and in the limit of low signal-to-noise ratios. With SB measurements in hand, the computation of a Bayesian prior on redshift given galaxy photometry and SB. This can be done with either simulated datasets, or real observations with spectroscopic redshifts. Tests will then show the performance of such a prior relative to using galaxy photometry alone. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A fast, scalable algorithm for measuring the surface brightness profile of galaxies. +\item A cross matched catalog with objects at known redshifts and measured surface brightness profiles. +\item A Bayesian prior $p(z|C,SB)$ that can be used to improve photo-z measurements. +\end{enumerate} +} +\end{task} +\end{tasklist} + + + diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index 54e214f..7eeae7e 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -14,4 +14,5 @@ %\input{task_lists/weak_lensing/weak_lensing.tex} \input{task_lists/agn/agn.tex} +\input{task_lists/photo_z/photo_z.tex} %\input{task_lists/galaxies/galaxies.tex} diff --git a/task_lists/template.tex b/task_lists/template.tex new file mode 100644 index 0000000..e2c6d0d --- /dev/null +++ b/task_lists/template.tex @@ -0,0 +1,44 @@ +\section{Section Title}\label{sec:tasks:title} + +Summary + +\begin{tasklist}{T} +\tasktitle{Task Title} +\begin{task} +\label{task:section:title} +\motivation{ +XXX +\\ +XXX +} +\activities{ +XXX} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Task Title} +\begin{task} +\label{task:section:title} +\motivation{ +XXX +\\ +XXX +} +\activities{ +XXX} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} +\end{tasklist} From 0a0f306c970717c37b083f155a6cf0d7255419f3 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 20 Dec 2016 21:48:23 -0800 Subject: [PATCH 06/64] Adding High-Z 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are phenomena that enable us to understand the growth of BHs, understand aspects of galaxy evolution, probe the high redshift universe and study other physical activity, including accretion physics, jets, magnetic fields, etc. There are distinct aspects of the study of AGN that can best be explored by considering AGN as an evolutionary stage of galaxies rather than a distinct type of source. The tasks listed here explore aspects of AGN study that are particularly important AGN as a stage in galaxy evolution. @@ -124,4 +124,4 @@ \section{Active Galactic Nuclei Task Lists}\label{sec:tasks:agn:intro} \end{enumerate} } \end{task} -\end{tasklist} \ No newline at end of file +\end{tasklist} diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex new file mode 100644 index 0000000..3b7b037 --- /dev/null +++ b/task_lists/high_z/high_z.tex @@ -0,0 +1,51 @@ +\section{High-Redshift Galaxies}\label{sec:tasks:high_z} + +Summary + +\begin{tasklist}{T} +\tasktitle{Optimizing Galaxy Photometry for High-Redshift Sources} +\begin{task} +\label{task:high_z:photometry} +\motivation{ +The identification and study of high-redshift galaxies with LSST hinges on reliable, accurate and optimal measurements of the galaxy flux in all LSST passbands. +Galaxies at redshifts above 7 will only be detected in the LSST y-band and will be non-detections or ``drop-outs'' in the other LSST filters. Galaxies at redshifts above 8 will not be detected at all in the LSST filters but combining LSST with infrared surveys such as Euclid and WFIRST would enable this population to be identified. It is particularly important to have robust flux measurements and robust flux limits for the undetected high-redshift galaxies in the blue LSST filters so this information can be utilized in the high-redshift galaxy selection. Since Euclid and WFIRST are space-based missions with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogenous flux measurements for sources across the different surveys. +\\ +It is not clear if the current Level 2 data products package will meet all the requirements for high-redshift science with LSST and this therefore needs to be investigated before the start of the survey. +} +\activities{ +Firstly, we need to get a clearer picture of what constitutes the LSST Level 2 data products so we can assess whether these will be adequate for the high-redshift science. Issues that we need to understand are: 1) Will photometric catalogues be produced using the reddest LSST (e.g. y-band) images as the detection image? This is critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. 2) When computing model galaxy fluxes, will negative fluxes be stored? Negative fluxes for undetected galaxies together with their corresponding errorbars, provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. + \\ +The second major activity will be determining the best approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection. We will need to determine the optimal measure of an optical-IR colour for sources from these two datasets. There is the additional complication that sources that are resolved in the Euclid/WFIRST data could be blended in LSST and will therefore need to be accurately de-blended, perhaps using the high-resolution IR data as a prior, before a reliable flux and colour measurement can be made. Tests can be run using existing datasets e.g. from the Dark Energy Survey (DES) and HST.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Determine what constitutes LSST Level 2 data products and document what additional data products will be required for high-redshift science. +\item Develop tools to produce optimal combined photometry from ground and space-based surveys and test these on existing datasets. +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{High-Redshift Galaxies and Interlopers in LSST Simulations} +\begin{task} +\label{task:high_z:interlopers} +\motivation{ + Before the start of LSST operations, it is important that we are able to test our selection methods for high-redshift galaxies on high-fidelity simulations. Given the wide-field coverage of LSST, it will be uniquely positioned to uncover large samples of the most luminous and massive high-redshift galaxies at the Epoch of Reionisation and beyond. The most significant obstacle to selecting clean samples of such sources from the photometric data, is the presence of significant populations of interlopers e.g. cool stars in our own Milky Way and low-redshift, dusty and/or red galaxies, both of which can mimic the colours of high-redshift sources. Using the LSST simulations, we want to be able to devise the most effective way of separating these different populations, and utilising both photometric and morphological information for the sources. Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA infrared surveys, we expect at least some of the most luminous z > 6 galaxies to be spatially resolved in the LSST images. +} +\activities{ +Liaise with the LSST simulations working group to ensure that high-redshift galaxies have been incorporated into the simulations with a representative set of physical properties (e.g. star formation histories, UV-slopes, emission line equivalent widths, dust extinction, metallicity). It is also important that the high-redshift galaxies have the correct number density and size distribution in the simulations. The latter will allow us to investigate how effectively we can use morphology to separate these galaxies from interlopers. +\\ +In addition to the high-redshift galaxies, it is equally important from a high-redshift science perspective, that interlopers have been incorporated into the simulations with the correct number densities and colours. Interlopers of particular relevance to the high-redshift searches will be cool stars in our own Milky Way (e.g. L and T-dwarf stars) as well as populations of very red, massive and/or dusty galaxies at lower redshifts of $z\sim2$. +\\ +Finally, we may want to consider whether to include colour information in the infrared filters (e.g. those from Euclid/WFIRST) in the simulations as this information will undoubtedly help with the high-redshift selection. + } +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Incorporate high-z galaxies into LSST simulations with a realistic and representative set of properties. +\item Incorporate brown dwarfs into LSST simulations +\item Extend simulations to other datasets beyond LSST (e.g. Euclid/WFIRST filters). +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex new file mode 100644 index 0000000..d60b8c7 --- /dev/null +++ b/task_lists/lsb/lsb.tex @@ -0,0 +1,169 @@ +\section{Low-Surface Brightness Science}\label{sec:tasks:lsb} + +Summary + +\begin{tasklist}{T} +\tasktitle{Techniques for Finding Low-Surface Brightness Tidal Features} +\begin{task} +\label{task:lsb:tidal_features} +\motivation{ +A key advantage of LSST over previous large-area surveys (e.g. the SDSS) is its ability to detect low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and other features associated with past and ongoing interactions, intra-cluster and intra-group light, and nearby, extended low- surface-brightness galaxies. +\\ +Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected by criteria that are difficult to quantify (e.g. visual inspection that can somewhat subjective) or reproduce in theoretical models. Automated (algorithmic) measurements of the LSB features themselves can be challenging and many past studies have relied on visual inspection for the identification and characterization of features (which may not easily applied on the LSST scale). For LSST it is highly desirable that we automate the detection and characterization of LSB features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. +} +\activities{ +Several activities are of crucial importance: +\begin{enumerate} +\item Simulating realistic LSST images and LSB features (using, e.g., high-resolution hydro simulations) +\item Identifying precursor datasets that can be used as proxies for developing LSB tools for use on LSST data +\item Using the simulations to develop algorithms for detection and measurement of LSB features +\item Applying these algorithms to the precursor datasets to test their suitability +\item Ensuring that LSST level-2 processing strategies and observing strategies are aligned with the needs of LSB science +\item Developing a strategy for finding and measuring LSB features through a combination of level 2 measurements, database queries, and level 3 processing +\end{enumerate} +It is important to produce realistic LSST images from e.g. the current generation of hydro-dynamical cosmological simulations (which faithfully incorporate both the evolution of large-scale structure and the interplay between baryons and dark matter during interactions). Scattering from bright stars (which may or may not be in the actual field of view of the telescope) is likely to be the primary source of contamination when searching for extended LSB features. Ideally, the LSST scattered-light model, tuned by repeated observations, will be sufficiently good that these contaminants can be removed or at least flagged at level 2. Defining the metrics for “sufficiently good,” based on analysis of simulated images, is an important activity that needs early work to help inform LSST development. +\\ +Including Galactic cirrus in the simulations will be important when developing strategies for detecting for large-scale LSB features. Including a cirrus model as part of the LSST background estimation is worth considering, but it is unclear yet whether the science benefit can justify the extra effort. +\\ +Because the LSST source extraction is primarily optimized for finding faint, barely-resolved galaxies, it will be challenging to optimize simultaneously for finding large LSB structures and cataloging them as one entity in the database. For very large structures, analysis of the LSST “sky background” map, might be the most productive approach. We need to work with the LSST project to make sure the background map is stored in a useful form, and that background measurements from repeated observations can be combined to separate the fluctuating foreground and scattered light from the astrophysically interesting signal from extended LSB structures. Then, we need strategies for measuring these background maps, characterizing structures, and developing value-added catalogs to supplement the level 2 database. +\\ +For smaller structures, it is likely that the database will contain pieces of the structure, either as portions of a hierarchical family of deblended objects, or catalogued as separate objects. Therefore, we need to develop strategies for querying the database to identify galaxies which are likely to have such structures. E.g. in galaxies that have LSB tidal features around them, the main body of the galaxy is likely to be disturbed and therefore asymmetric. Measures of asymmetry will therefore be useful for flagging such systems. We then need to have a strategy for either extracting the appropriate data for customized processing, or develop ways to put back together the separate entries in the database. A possible value-added catalog, for example, from the galaxies collaboration might be an extra flag in the database to indicate that a galaxy is likely to have LSB tidal features and an extra set of fields for the database to indicate which separate objects are probably part of the same physical entity. +\\ +This would be relatively sparsely populated in the initial stages of LSST. Estimates from the Stripe 82, indicate that 15\% of galaxies carry LSB tidal features (LSST will reach Stripe 82 in a single shot) but by the end of the survey will become a key resource for a wide variety of investigations. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Realistic mock LSST images from hydro cosmological simulations (including re-simulations of individual objects were necessary) with spatial resolutions of tens of parsecs. +\item Algorithms for finding galaxies with LSB features and for measuring the properties of these features. +\item Input to the Project on scattered-light mitigation and modeling strategies from the simulations. +\item Input to the Project on photometric and morphological parameters (e.g. asymmetry, residual flux fractions etc) to measure and store in the level 2 database. +\item Query strategies and sample queries for finding LSB structures. +\item A baseline concept for a value-added database of LSB structures. +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Low-Surface Brightness Galaxies} +\begin{task} +\label{task:lsb:galaxies} +\motivation{ +Our objective is to investigate the most relevant and challenging aspects of the Low Surface Brightness (LSB) Universe. This has a direct baring on the range of galaxies initially formed, the properties that they have during and after their assembly, their connection to the cosmic web and ultimately to the nature of dark matter, which plays a large part in all of these processes. +\\ +By LSB we mean objects that have surface brightnesses much less than that of the background night sky and that which is typical of the Milky Way galaxy we live within. Many authors have previously shown how difficult it is to detect objects of LSB and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to the spiral galaxy that we live within. Thus the Universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? +\\ +The problem is that astronomical observations always include a signal from a background, a level we need to detect our sources above. For ground based observations the background arises locally from the atmosphere and our proximity to the Sun, scattered light from the solar system, diffuse star light from the Galaxy and a small contribution from other galaxies in the Universe. For an astronomical object to be detected it must stand out above the noise level in this background. If this noise was purely due to photon statistics then very simply all we would need to do is collect as many photons as possible and the signal would gradually appear out of the noise. However, we currently know that it is nowhere near this simple because of scattered light across the field of view (FOV), instrumental calibration uncertainties and real fluctuations in the cosmic background. For these reasons there has previously been little progress in making a definitive study of the extent and brightness limits of the LSB Universe. +\\ +Additionally, this LSB universe include a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model. The galaxy mass function at masses less than Mh ~ 1010 Msun systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via HI surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies are still quite easy to detect in LSST images. +\\ +The challenge is to identify them as nearby dwarfs and estimate their distances and hence luminosities. The dwarfs in question are low-surface-brightness galaxies, so many of the source-detection issues are common to the more general problem of detecting LSB features. LSST data allow us to focus on different issues. For certain distances and luminosities, typical dwarf spheroidal galaxies will be distinct from the vast majority of background galaxies in the radius vs apparent magnitude plane. However, there will often be overlapping background galaxies, so it is important that the de-blending and cataloging steps try to remove the overlaps and allow one to query for galaxies in the right portion of the color-size-brightness manifold. Once candidates are identified, it should be possible to tease out approximate distances for many dwarf galaxies via surface-brightness fluctuations (SBF). Once again this requires careful treatment of the background galaxies, but this step is now Level 3 processing, so can be customized much more than the detection step. More ambitiously, it is conceivable that machine-learning techniques could be trained to identify semi-resolved nearby dwarf galaxies given a suitable training set from LSST-precursor observations. +\\ +On the other extreme of LSB objects, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disc of stars and an impressive system of spiral arms only revealed in 2015. The central bulge of the galaxy is prominent, but the stellar disc and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB discs? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting SB of the LSST combined with the large FOV make this instrument unique to probe the existence of large LSBs, similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant discs like Malin 1 only make this problem worse. This is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. In addition we will be exploring the very outer regions of galaxies and so will be able to explore the connection between the decreasing surface density of baryons and the increasing significance of the dark matter component of galaxies. +\\ +One reason why this subject has made little progress over the last few years is because of the limited amount of deep large area data available. Most previous deep (CCD) surveys have been specifically designed to investigate the distant Universe and so, like the Hubble Deep Field, have concentrated on long exposures over small areas of sky. The extensive sky survey that LSST will carry out will become the state-of-the-art for years to come and offers a new and enormous LSB discovery potential. As a pointer to these exciting discoveries there have recently been relatively small-scale observations that indicate that a hidden LSB galaxy population does exit. An example is the population of LSB galaxies recently detected in the Coma and Fornax clusters, galaxies not only with astonishing LSB (>27 B mag arcsec-2), but also with some of them exhibiting effective radii similar to that of the Milky Way. This is despite both Coma and Fornax being two of the previously most studies regions of the nearby Universe. +\\ +To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5\mathrm{mag}~\mathrm{arcsec}^2$ and that from a space telescope typically an order of magnitude fainter $\approx25.0\mathrm{mag}~\mathrm{arcsec}^2$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0\mathrm{mag}~\mathrm{arcsec}^2$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28\mathrm{mag}~\mathrm{arcsec}^2$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32\mathrm{mag}~\mathrm{arcsec}^2$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into high surface brightness stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26\mathrm{mag}~\mathrm{arcsec}^2$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the Universe using LSST to at least a surface brightness level of $30\mathrm{mag}~\mathrm{arcsec}^2$. +} +\activities{ +\begin{enumerate} +\item Production of simulated data that can be passed through the LSST data reduction pipeline. +\item Analysis of simulated images to ensure that LSB features can be accurately preserved and measured. +\item The development of new object detection software specifically designed for the detection of LSB features, in particular: +\begin{itemize} +\item Objects with large size. +\item Objects near or melted with large size, bright galaxies. +\item Objects with patterns similar to galaxy streams. +\item Highly irregular and distorted objects. +\end{itemize} +\item Identification of precursor data sets that can be used to test our methods. We can use data generated using numerical simulations to look at the types of galaxies produced that have sufficient angular momentum to become LSB discs. These discs can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. We will develop new methods of detecting LSB objects. These will include pixel clustering methods and the labeling of pixels with certain properties i.e. surface brightness level, SED shape, proximity to other similar pixels etc. We will trial our methods on other currently available data sets (KIDS, CFHT etc). +\item Simulate realistic LSST images of nearby dwarf galaxies. +\item Identify nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools. +\item Develop and test the database search queries for finding candidates of several shapes and sizes. +\item Develop and test a measurement of semi-resolved ``texture'' as a candidate level 2 measurement. +\end{enumerate} +The use of ``texture'' as a means of identifying candidate nearby dwarf galaxies is something that needs near-term attention if it is to make it into level 2 processing early in the survey. This can be developed and tested on the semi- resolved-galaxy simulations, but it is also essential to test it on precursor data sets from DES, CFHTLS or HSC. +\\ +As a natural consequence of the effort that the members of this team are going to invest on the discovery and catalogue, we can foresee a long-term group effort for continuing the research once deliverables are available. A natural strategy, will be to perform several follow ups with large aperture telescopes available in Chile, with powerful instruments capable of obtaining optical, near-IR spectra, sub-mm, mm and IFU data for LSB objects. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Realistic mock LSST images. +\item An assessment of the influence of the PSF, scattered light and other instrument signals that may affect our ability to detect LSB features +\item An assessment of the effect of proposed pipeline on the detection and measurement of LSB features. +\item A baseline concept for the construction of a database of LSB features detected using LSST data. +\begin{itemize} +\item Realistic inputs of dwarf galaxies for the LSST image simulations. +\item Realistic postage-stamp simulations of semi-resolved dwarf galaxies. +\item Training set of nearby dwarfs from LSST precursor data. +\item Figures of Merit for detection and selection algorithms +\item Run LSST pipeline on both simulations and precursor data and assess performance. +\end{itemize} +\item Optimized algorithms measuring surface brightness fluctuation distances. +\item A new LSB object detection package, friendly adapted for the user. +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Probing the Faint Outskirts of Galaxies with LSST} +\begin{task} +\label{task:lsb:faint_outskirts} +\motivation{ +The outskirts of nearby galaxies, loosely defined as the regions below $25-26\mathrm{mag}~\mathrm{arcsec}^2$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). +\\ +The main science driver here is understanding the assembly, formation, and evolution of galaxies. This can be studied through imaging and subsequent parametrization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar haloes. From numerical modelling we know that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo, are tightly related to the accretion and merging history. This is illustrated by the imaging of the stars in the outskirts of M31 and other local group galaxies, which show detailed structure. +\\ +Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to local group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams may be less affected by overall PSF, but more by foreground cirrus. +} +\activities{ +Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modelling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyse the outskirts. Dithering and rotation of individual imaging will need to be modelled before stacking multiple imaging. +\\ +Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} +\end{tasklist} + + +\begin{tasklist}{T} +\tasktitle{Low-Surface Brightness Intracluster Light} +\begin{task} +\label{task:lsb:icl} +\motivation{ +The Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. It is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. +\\ +Some outstanding scientific questions, which LSST could solve: +\begin{itemize} +\item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? +\item Does it contain significant substructure? +\item What is its surface brightness profile and does it have a colour dependence, which would indicate age/metallicity gradients? +\item Where does the ICL begin and the large diffuse cD halo of the Brightest Cluster Galaxy (BCG) end and do they have the same origin? +\end{itemize} +} +\activities{ +The preparation work for the ICL component of the LSB case involves investigating LSST specific issues for large LSB features and the known properties of the ICL itself. +\\ +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce low surface brightness signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for the LSB team to liaise with LSST strategy, telescope, instrument and data reduction teams. +\\ +The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Investigate any telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. +\item Investigate observation specific issues that affect the measurement of large LSB features: dither pattern strategy. +\item Investigate image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. +\item Feasibility: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? +\item Investigate stacking clusters to obtain faint ICL - this is difficult as will require very strong masking of even the faintest observable cluster members. +\end{enumerate} +} +\end{task} +\end{tasklist} \ No newline at end of file diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index 7eeae7e..5c3e1f3 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -14,5 +14,7 @@ %\input{task_lists/weak_lensing/weak_lensing.tex} \input{task_lists/agn/agn.tex} +\input{task_lists/high_z/high_z.tex} +\input{task_lists/lsb/lsb.tex} \input{task_lists/photo_z/photo_z.tex} %\input{task_lists/galaxies/galaxies.tex} From e2244acc2d645e7c367873dcd65cfd309f5724d6 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 20 Dec 2016 22:07:17 -0800 Subject: [PATCH 07/64] Removing empty sections. --- exgal_roadmap.pdf | Bin 199284 -> 221989 bytes exgal_roadmap.tex | 5 +++++ 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We want to thank the LSST Corporation for their support in developing this Roadmap and for supporting LSST-related science more broadly. We also wish to thank the LSST Galaxies Science Collaboration members for their efforts -over the years in developing the case for extragalactic science with LSST.\\\\ +over the years in developing the case for extragalactic science with LSST. Lastly, we +wish to thank Harry Ferguson for his continued efforts to organize this document.\\\\ Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}). %\newpage From 847bd4d054888db94b46a8e9bcc5366347efc47a Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 22 Dec 2016 15:37:01 -0800 Subject: [PATCH 11/64] Adding CLSS and DDF sections. --- exgal_roadmap.pdf | Bin 229212 -> 262099 bytes task_lists/clss/clss.tex | 324 ++++++++++++++++++++++++++++++++++++++ task_lists/ddf/ddf.tex | 73 +++++++++ task_lists/task_lists.tex | 2 + 4 files changed, 399 insertions(+) create mode 100644 task_lists/clss/clss.tex create mode 100644 task_lists/ddf/ddf.tex diff --git a/exgal_roadmap.pdf b/exgal_roadmap.pdf index f25baaf7a184e116ecc730c2a25bb7ccf51f23f4..8b56d3f99d0550b6fafaafeacbcdcd690284dee0 100644 GIT binary patch delta 199971 zcmZs?1B@h)x2!P)Gtq zemK*lINA8~cjH$EIQ8MmDW*Iz3vy(U^_CrcA4uz!GX*aTq#5B;WoJCjrQeFFY&Q$$ z6!8=;(%Q!I`+q+H9v#u{+kVtR6jmjLYXBeky=e^r-;15m%$17?+Tw;(f8q-a3#9piBYlZdhF@qw_{G- z){*Ls1mCRhjemW3uuohjAKlTxE;WdK=+|=9|1x!vA8fh<@O9--rP<}}@{5f()T?LE zW(z7kT~p7m*MEFb9kyM4*_qOz(w#NoCCJrGoum^o0 z5Hf8cK>7xft${_zRiHA2YgiOPc!Z~piF&0pkGRL66&CE|0Dj#(gJ|~w+Li%@t?vjtgYVI6jE~| z(yP2IM=Py9vk99rUu3&<8jP&|*L_OY$YO(*d{q3g@&jLP$8qheOD{}|_H@n%3|8Z^ zW%K|F)_;bhwXrI24E=#2u>NBsfF($E`2RKE-7i&ObsLEnWgz}AU2=rs2*DYdIty4X zDo12`d}!AP*Fh4RW}%kKLp|MA>!lv%t#Lp0Y-mpTV>Xo$Pbyzq7vHetGHT{nho{Z>W9g$+2GY2XbkY|Pdo z{HRs52uk$ml9rRWd=@ady!9`9y5J77G&jRtOxOL;!ndCNy=^^bwtKz2|jf8`TQUj=1;5fiRwXD>g#=VFTB(BVk`GY)mQGkDzV#k?#~*rt#K6$7Lz@QkS(qfmC_fr$P;D?f=EqoWMl56pJ*joulQF4V2>kwc)WYBpqG8`pKV|wcD@!+--HMyB_}gyL0Hb z(vzMf=y{DaT+Ke50slXKF6I2+2H}`W1pe2K63puYMGYR$?+IdtZcV*9;~fL&@9wWR zQFjjo{X1;04t`l$0(^QeR47tmF#_iTw}U@LI- zh7p10??zbR=d?Wk(ag-FH&O)PM^+*Ph-jmx8jv~~A$kWyjZ2vqr7>t6hsk#;CM6hr zDKuCtcOeYhV@%>F?y_biIQh=&{tKQiti4(BScvp{%Pgv3OdYOR-%O|_<1p)cd%P;V z|8{7TUVLWt>y+Poi94r=wsM<`@O10B8FJq6TiTKte#*WwS8uZBe5?bQeQvyr#&u|; zW%J2*0=)ldn7IgPj8I(xh1@gS`aQHE|iO3E2nPfZMTfnuGLWb zL~v~M-Lz?7(2)iy&0BhjAWqAdHVj4{VZ_P@>%P3-vZBg5irE$S%Bl5kFIQNn$I9MN ztF`6iCt@>8EQJ3bO#q<>)|PjK6(di+i0i?tb5Hm#M&olqm!?+#h-^phzj13yflY zUJPSqZ|dUeY-VKlKhpn14Q}p6075Wyq7xKaBPJFxI0!RSBM-hbBnUHmV+ffTA_xmh z<0LCI;(rRLji(}J@F1*AjS5Ovu)ti6yt+~#|24t-e83>=tc?Q(fl&W-#VrqD5m}l4 zpJ2qv&i228(X{rsJsu}g_pIh!n(kUv2(BU49SS!vN?)Ci6v-LUWRO^RK64TC-j}aF zyO~a5JiD4K|5$mdr)jU3I-Q2o5_oD>TxDz;9=N2mt~=h6vg^PV6)!no`J$y@TUz1Z zXVODp#Uxf@1+6Zgq?}U1Ve~i?u8B&-;Zsp^HkA1&Ko*$6!Wl%D+)0JmZYjhVYWYYF z4;F&Drx1Gf%@*bWt*wd(NOyc)91b3fP&la|5DUu0XNXd5f@B}H-k-oRJwdh)9Zsfi z8Ak{|CBW8Pm(_8Y8nrXB5{eG7zr2A5s|v=2wkRA}1H4PBE)Aq)Y~G$pvb==o4NRd8 zSU3^_0Kqz9GcZQQku@ehd0xLUA#AC{N^BR%NeP?msZr@l|T$qh7v8K%nZL3uM+5;|92u!$C2JpXK&va zsvfsY+|i&S&=Wj}mTRz`0TLEhDqa%7*!s^Lps!RLi3bc|CXE4Hr$~%PU8VGvuy(by6c_He1IHhosWS{5j9*H$PY*3KFvft03!n% z>26XZbcDvNNu(B;;b!gx)~wtXjto{aT!5AznMrpTNwsbppg^8U&xF2lc`%O3iPy0Y zSiZQPfM?uR9&q+L3=L|0uJ`^x6J!i+{q@uB*nb{3m>j+{cI(m4sb$n--ZJ)R?9%n^ z;L_7K9*$x3)9Df9_3Zh$iVdWfV*xzggA6h3XGx)8exdOEY_%(_vvXX~U!;V0O zSv{NfYqpV3ygm0qTPJ62UXypKQItE%kyi%D;^RiW)V$;l z>rW;`qb)XAdK6f51_h#PQ|fD@e<_B<4qe);d}v;o{XE?LdItC;TZpj{XRcWQGM1h5 z9#%fZ!bSg4)Bhpkpdp9|cobYR4k_!nC8Ba+m7pypL(?uS1i@~df3v+g*}sigIkgNs zjEoXGgZFojcawJq;Ukc!r)UKz>QzQpaq2#OVPy~oc^Dkj|9nB)EN&!XKlYz)6aU>+ zmJ&`2|C1#xuU*>%XsyGtG+?}}{oEAwv(C+3k?X_@3&ij?*CsibIYk6mRJzPIjuGEM zkVM5hVRHlHB6uw0i=7|^Com4f)Ly}|jHB0YM)-LBjhUot0J~RLVj%egBO|$_Z;0u= zHkB7+IIf0PJ#Y{|sFV_r^%574J$4j`7BfcgsMRu&CZym6SUZEWMZ*QJU`BWYk|C8| z56imIopA{tsEe(t_Ajk-h(I$)zb#@8!wHWLtVm1tVPfa zTBz8sE<|@t#4@;GbhL`%X!fA8oWX)b%Nst0M2r`2n8=<7{vI`QcmS{`_ zSD2R#;8-I{ZVH=*GZHOB9BGUNvWmug&^^ZA$Fue?^DRPl{bOMR`A=ea27gnXpt%-}mboA*q>CPO zn5Aw}wkbXSWo0J63aZMoCf;|(Yj^uEal$b~wpXTA-BZV|+{)c1< zpK@)N?>m zwqC@Id8=GRjyicdv&zcDFN8MA4d`>z?)28D6DDl9d#2X=&xz_4ahKvyT5L{XicnW zX2xyUFkb(Z=DK!gtSf|+TfidO)bqx^LF^1~XR2C-l9vzN5Y@(NI#R3LyD2>00IyEG z9*0MJF|SZN9A-i1 z!_OyCk|)6dv!q+J_U$&%Fb@DK;eH7=BlIDzY*^Vc!04JbIGdc+MtCN11i}8ia<>=)Kv%4z$^R032*9mJpiydn%1fZSB zF0g}8XP4{QmdJVBm%Kr{KCj}@d+5q0|Ls^XGy;Zy`UkwPC{D;HMaBHYa9KhLj(q1fB_ zuJ^(U-hK)A6-*pdWyiy;>U4b~16*dlu8YjI?V6vC+Gp+Kkk>frz%7?r_xbJCU@)*B zb?O_gOM|S6GD?$hPNik)BmmI3)q}d#rtw3%TZNB&Dq4D2`B0hN2{vLS!%UW4D(9;T zrO2c<(Vn%eZ{l!xeV617;_C$MzSrXO6&`;!tby4`Y4F(g<_b?Z*f`GK0ZjO{+S05e zRXN79(<1eJ%fiq3sl2Af`KjF3IaAfv2yz@5o8LdyxRMI9WP>E~-P@t<^%56-SEiJe zLl*1#{QsJ9Dq7AxOX?YL(yO9)j9Zt`22a-G*4YIHmf%_HTTATRQ$NMtw~`DWB61Hp zI_KKp$s{4wd^edQf+cJe0Cwdz6#EIBp^9;vzO}q7vg3tOiNP*SH#^BAoD|J-^cM!|~T-PF{9j%;*zxES^$qVR@>EmL>Aapg|E71sM!=%5}vKr zU~gS0v5j)&=BVcZMgErGuGRBc0HhzxG@)xDuR4~^$16$PEb>`(O{HQR&5P3Khruv$ z6N`5(TRsAZbGKF%AedtlA_6R8#x`8XD`F7^{Ah^T7}$(y9ykW##opu1&Jg6wwncJ! 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The output databases can be +analyzed to determine the depth LSST is expected to reach in its final +detection image at each sky location, and Awan et al.~2016 +(http://adsabs.harvard.edu/abs/2016ApJ...829…50A) turns these depths +into predicted numbers of galaxies as a function of redshift and +brightness. +\\ +To predict galaxy sample sizes as a function of physical parameters, +the ``raw'' predicted galaxy numbers from Awan et al.~(2016) will be +interfaced with semi-analytical models painted on large N-body +simulations by Risa Wechsler and collaborators. This will extend the +predictions to include observed properties of color, size, morphology +and physical properties of halo mass, stellar mass, and star formation +rate. +\\ +To predict group/cluster sample sizes as a function of physical +parameters, the properties such as temperature, richness, etc., will +be painted on to dark matter halos drawn from a numerical simulation. +The properties will be based on simple scaling laws, with the user +allowed freedom to choose the parameters of the scaling laws, +including how they evolve. This will then be interfaced with the +``raw'' predicted galaxy numbers from Awan et al.~(2016), to determine +which of the groups and clusters should be detectable in the LSST +data.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Create a public LSST Extragalactic Sample Emulator with a +simple GUI. Enable user input of a range of redshift, and +physical parameters (e.g.~galaxy magnitudes, colors, size, morphology, +cluster richness, mass, temperature, etc.) to estimate the size of a +given sample detected by LSST. +\end{enumerate} +} +\end{task} + + +\tasktitle{Identifying and Characterizing Clusters} +\begin{task} +\label{task:clss:clusters} +\motivation{ +LSST photometry will make it possible to +search for and study the galaxy populations of distant clusters and +proto-clusters over huge volumes of the high-$z$ Universe. These +clusters are testbeds for cosmology, hierarchical structure formation, +intergalactic medium heating and metal enrichment, as well as +laboratories for studying galaxy evolution. +However, standard approaches for identifying clusters, such as the red +sequence method, will be hampered by the limited wavelength coverage +of LSST. +For example, at $z \gtrsim 1.5$, near-IR photometry is required to +identify systems with Balmer/$4000$\AA\ breaks. +To maximize cluster science with LSST, we must devise new techniques +for cluster identification as well as incorporate complementary data +from projects such as \emph{Euclid}, \emph{eROSITA}, etc. +} +\activities{ +Using existing imaging datasets and simulations, algorithms need to be +developed and optimised to identify clusters at intermediate +and high redshift within the LSST footprint. +Specifically, this work should characterize the selection +function, completeness, and contamination rate for different cluster +identification algorithms. +This requires realistic light-cone simulations spanning extremely +large volumes, so as to capture significant numbers ($\gg10,000$) of +simulated galaxy clusters at high $z$. +Potential algorithms to be tested include adaptations of RedMaPPer +(Rykoff et al.~2014) as well as methods that search for galaxy +overdensities over a range of scales (e.g.~Chiang et al.~2014; Wang et +al.~2016). +In parallel, a comprehensive search for multiwavelength data +(specifically IR and X-ray imaging) is needed to aid in the search for +high-$z$ clusters and in the confirmation and characterization of +systems at all redshifts.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item The primary product of this analysis will be improved cluster +identification algorithms that can be applied to LSST data once +science operations commence. +\item In addition, this work will produce a compilation of ancillary data +that will be helpful in cluster identification and characterization, +such as X-ray (e.g.~XCS, eROSITA, etc.), SZ (Planck, SPT, ACT) and +radio (SKA and its pathfinders, SUMSS), within the LSST footprint. +\end{enumerate} +} +\end{task} + + + + +\tasktitle{Developing and Optimizing Measurements of Galaxy Environment} +\begin{task} +\label{task:clss:environment} +\motivation{ +Over the past decade, many studies have +shown that ``environment'' plays a important role in shaping galaxy +properties. For example, satellite galaxies in the local Universe +exhibit lower star formation rates, more bulge-dominated morphologies, +as well as older and more metal-rich stellar populations when compared +to isolated (or ``field'') systems of equivalent stellar mass (Baldry +et al.~2006; Cooper et al.~2010; Pasquali et al.~2010). +Unlike spectroscopic surveys, LSST will lack the precise line-of-sight +velocity measurements to robustly identify satellite galaxies in +lower-mass groups, where the expected photo-$z$ precision will greatly +exceed the velocity dispersion of the host halo. +Instead, LSST will likely be better suited to measuring environment by +tracing the local galaxy density (and identifying filaments). However, +LSST is unlike any previous photometric survey and may require new +approaches to measuring environment. +The challenge remains to find the measure(s) of local galaxy density +with the greatest sensitivity to the true underlying density field (or +to host halo mass, etc.), so as to enable analyses of environment's +role in galaxy evolution with LSST. +} +\activities{ +Using mock galaxy catalogs created via +semi-analytic techniques, we will compare different tracers of local +galaxy density (i.e.~''environment'') measured on mock LSST +photometric samples to the underlying real-space density of galaxies +(or to host halo mass). In addition to testing existing density +measures, such as $N^{\rm th}$-nearest-neighbor distance and counts in +a fixed aperture, we will explore new measures that may be better +suited to LSST. For each measure, we will examine the impact of +increasing survey depth and photo-$z$ precision over the course of the +survey.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item With an improved understanding of the +strengths and weaknesses of different environment measures as applied +to LSST, this effort will yield code to measure local galaxy density +(likely in multiple ways) within the LSST dataset. +\item Create a Level 3 data product for use by the entire project. +\end{enumerate} +} +\end{task} + +\tasktitle{Enabling and Optimizing Measurements of Galaxy Clustering} +\begin{task} +\label{task:clss:clustering} +\motivation{ +Contemporary galaxy surveys have +transformed the study of large-scale structure, enabling high +precision measurements of clustering statistics. The correlation +function provides the most fundamental way to characterize the galaxy +distribution. The dependence of clustering on galaxy properties and +the evolution of clustering provide fundamental constraints on +theories of galaxy formation and evolution. Interpreting these +measurements provides crucial insight into the relation between +galaxies and dark matter halos. Understanding how galaxies relate to +the underlying dark matter is also essential for optimally utilizing +the large-scale distribution of galaxies as a cosmological probe. +} +\activities{ +Preparatory work will be along two main +tracks. The first one will be support work to define and characterize +the upcoming galaxy samples from LSST to enable clustering +measurements from them. Several distinct sets of information need to +be made available or be calculable from pipeline data. Such +requirements include a detailed understanding of any selection effects +impacting the observed galaxies, the angular and radial completeness +of the samples, and the detailed geometry of the survey (typically +provided in terms of random catalogs that cover the full survey area). +\\ +The second track will be the development, testing, and optimization of +algorithms for measuring galaxy clustering using LSST data. One aspect +to address is how best to handle the large data sets involved +(e.g.~the ``gold'' galaxy sample will include about $4$~billion +galaxies over $20$,$000$~square degrees). Another is to develop the +methodology to optimally incorporate the LSST photo-$z$ estimates with +the angular data to obtain ``2.5-dimensions'' for pristine clustering +measurements. +\\ +These algorithms will be tested on realistic LSST mock catalogs, which +will also later serve as a tool for obtaining error estimates on the +measurements. +This endeavor overlaps with DESC-LSS working group efforts, and +requires cooperation of the DESC-PhotoZ working group and the Galaxies +Theory and Mock Catalogs working group.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Ensuring LSST galaxy pipelines include all the necessary +information for measurements of the correlation function and related +statistics to take place once data is available +\item Developing and refining techniques for measuring galaxy clustering of +large LSST galaxy samples. Together these will enable realizing the +full potential of LSST data for large-scale structure studies and +galaxy formation inferences thereof. +\end{enumerate} +} +\end{task} + + +\tasktitle{Disentangling Complicated Lines of Sight} +\begin{task} +\label{task:clss:los} +\motivation{ +Lines of sight through galaxy clusters and groups are the most +challenging lines of sight along which to measure reliable photometric +redshifts because crowding of galaxies complicates the basic process +of galaxy photometry, and the presence of significant correlated +large-scale structure (LSS) complicates interpretation of the P(z) of +the galaxies that has been computed by an algorithm that ignores the +presence of the LSS. Numerous science goals require the most robust +probabilistic statements possible as to the location of galaxies along +lines of sight through clusters, for example, identification of +background galaxies for weak-lensing, identification of faint cluster +members to study the evolution of the luminosity function in clusters, +identification of star-forming galaxies in clusters and their infall +regions to probe the physics of quenching of star formation. +} +\activities{ +The LSST will deliver the most information rich dataset ever in +relation to the masses and internal structures of clusters and their +infall regions. Moreover, the dataset can be enhanced significantly +via the addition of data at other wavelengths, including X-ray, +millimeter, and near-infrared. +\\ +A tool is therefore envisaged, that can take an input catalogue of +cluster centres that has been obtained from LSST or any other dataset +(e.g.~\emph{Planck}, \emph{eROSITA}). The tool will pull out the +basic L2 LSST photometry of objects within a cone centred on the +cluster centre, and compute the $p(z)$ of each galaxy based on a +cluster-specific algorithm. This algorithm will take account of the +following where they are available: brightness and extent of X-ray +emission, over-density of galaxies as a function of magnitude and +colour, any available spectroscopic redshifts, amplitude and extent of +any SZ decrement/increment. The algorithm will likely adopt a Bayesian +hierarchical modelling approach to forward model the problem. The +algorithm can be tested on existing datasets from surveys such as the +Local Cluster Substructure Survey (LoCuSS), XXL, HSC data processed by +DM Stack within LSST, and any others that would like to join in. +\\ +This work has links with the work on deblending/ICL, forward modelling +of cluster and groups, environmental measures, cluster detection, +complementary data, and also work in the DESC Clusters WG via $p(z)$ +of background galaxies.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A new cluster-specific photometric redshift algorithm that can be +applied to a list of cluster detections that is itself based on LSST +or external data. +\end{enumerate} +} +\end{task} + + + + +\tasktitle{Forward Modeling LSST Clusters and Groups} +\begin{task} +\label{task:clss:cluster_fm} +\motivation{ +Most of the interesting cluster and group physics from LSST and its +union with complementary surveys will be derived from studies that +explore the full range of halo mass relevant to groups and clusters: +$M_{200}\simeq10^{13}-10^{15}M_\odot$. This is a wider range than +cluster cosmologists (e.g. colleagues in DESC, with whom we +collaborate) aim to incorporate into their cosmological inference -- +they restrict attention to $M_{200}>10^{14}M_\odot$. +\\ +Another important difference between the cluster/group physics +explored here, and the dark energy-motivated DESC work, is that the +requirement on controlling systematic biases is roughly an order of +magnitude less stringent here than in DESC. Arguably, $\sim10\%$ +control of systematic biases in weak-lensing measurements of low +redshift clusters ($\gtrsim2\times10^{14}M_\odot$) has already been +achieved (Okabe et al. 2013; Applegate et al. 2014; Hoekstra et +al. 2015; Okabe \& Smith 2016). Therefore in this Science +Collaboration we have the challenge of maintaining that level of +control down to smaller masses and out to higher redshifts. +\\ +A growing number of studies are adopting an approach of forward +modelling the cluster population simultaneously with the cosmological +model to obtain constraints on scaling relations and cosmological +parameters. Here, the idea is to borrow this same approach, but adopt +a fixed cosmological model, broaden the mass range of systems +considered, and expand the forward modeling to include additional +relationships of interest. For example, simultaneously fitting +density profile models to the shear profiles, the mass-concentration +relation, and the star-formation rates of clusters and groups. +Overall, this will provide a robust Bayesian inference code with which +to constrain the physics of galaxies and hot gas in groups and +clusters, tied directly to the halo mass function via weak-lensing. +} +\activities{ +Key activities include: +% +\begin{itemize} +\item Select the elements of the cluster population to include in the model +\item Write the first version of the code, and test on simulated (toy model and n-body) data +\item Improve code and consider extending range of physics explored by adding more relations +\item Test code on existing datasets from pointed surveys (e.g. LoCuSS, others) and wide area surveys (e.g. LoCuSS, DES, others) +\item Combine this development work other work packages within Galaxies and DESC +\end{itemize} +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Bayesian inference code to simultaneously model cluster shear +profiles, scaling relations (including and beyond cosmological scaling +relations, across the full range of halo mass of groups and clusters, +to $\sim10\%$ control on systematics. +\end{enumerate} +} +\end{task} + + + +\end{tasklist} diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex new file mode 100644 index 0000000..90ce8ab --- /dev/null +++ b/task_lists/ddf/ddf.tex @@ -0,0 +1,73 @@ +\section{Deep Drilling Fields}\label{sec:tasks:ddf} + +The LSST Drilling-Fields (DDF) are areas that have a higher cadence and deeper observations than the Deep-Wide survey. Many of the details of the observing strategy have yet to be finalized. Four Deep-Drilling fields have been selected. Whether to include any others will be part of a complex trade involving other special projects that depart from the Deep-Wide survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy are all still under study, and the Project needs input from the science collaborations to inform these decisions. The tasks outlined in this section are intended to help optimize the LSST observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy-evolution science. + +\begin{tasklist}{DDF} +\tasktitle{Coordinating Ancillary Observations} +\begin{task} +\label{task:ddf:ancillary_obs} +\motivation{ +It is crucial that the LSST deep-drilling fields be supported by observations from other facilities. While the LSST data by themselves will be unique in having deep and accurate photometry, good image quality, and time-series sampling, the amount of information in six bands of relatively broad optical imaging is quite limited. Estimates of photometric redshifts and stellar-population parameters (e.g. mass and star-formation rate) are greatly improved with long-wavelength data. Combining these quantities with information on dust and gas from far-IR, mm and radio observations allows one to build and test models that track the flow of gas in and out of galaxies. Deep and dense spectroscopy is essential both providing precise redshifts, calibrating photometric redshifts, and measuring physical properties of galaxies. Properly supported by this additional data, the LSST DDFs will become the most valuable areas of the sky for galaxy-evolution science. The central regions of the four fields already selected are already in this category; the main challenge is filling out the much larger area subtended by the LSST field of view. +} +\activities{ +The major challenge in supporting the Deep Drilling Fields is the huge investment of telescope time. There is a need for coordination across facilities and collaborations to make the most efficient use of this time. Coordination is certainly happening somewhat haphazardly, but there has not to date been a dedicated effort to get all the potential stakeholders involved in developing a coherent plan. The LSST science collaborations can and should be taking the lead here. The SERVS program to observe the already-designated DDFs with Spitzer is a good example of where this has happened (Manduit et al. 2012), but there is much more to be done. Activities include: +\begin{itemize} +\item Workshops to discuss LSST DDF coordination +\item Proposals for major surveys or even new instrumentation to provide supporting data +\item Executing those supporting programs +\item Working to integrate the data from those programs with the LSST data +\item Working to enable DDF support through policies and strategic planning at major observatories +\end{itemize} +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Workshops on LSST DDF supporting observations +\item Annually updated roadmap of supporting observations (conceived, planned or executed) +\item Public Release of data from supporting observations +\item Level 3 software to enable use of LSST data with supporting data +\end{enumerate} +} +\end{task} + +\tasktitle{Observing Strategy “Cadence”} +\begin{task} +\label{task:ddf:cadence} +\motivation{ +The LSST DDF observing strategy will need to serve diverse needs. For galaxy-evolution science, the time series aspect of the observation is less important than the depth, image quality, and mix of filters. Optimizing the observing strategy (including timing) is influenced by non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data. For example, for many science goals, completing the observations of one DDF to the final 10-year depth in the first year could be very beneficial. But there is work to be done to justify that, select the field, and find synergies with other science areas (e.g. DESC, AGN, transients). +} +\activities{ +The LSST observing strategy is optimized using the Operations Simulator (OpsSim). The Project works with the community to develop both strawman observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpsSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Figures of Merit via MAF for use by OpSim +\item Proposed observing strategies for DDFs with rationale +\item Proposing and/or helping to assess selection of additional DDFs +\end{enumerate} +} +\end{task} + + +\tasktitle{Data Processing} +\begin{task} +\label{task:ddf:data_processing} +\motivation{ +Getting the most out of the DDFs may require data processing beyond that required for the Deep-Wide Survey. There are a variety of issues that ought to be considered in trying to optimize the science output. These include different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features , deblending overlapping objects, or estimating photometric redshifts. The fields are small enough that it is conceivable to process or reprocess them making use of data from supporting observations. It will clearly be advantageous to have one “official” LSST-released catalog, but defining such a catalog to support a very broad range of science is challenging. This does not preclude having additional special-purpose catalogs, but it is clearly beneficial to the advancement of extragalactic research to have a high-quality official catalog that has “buy in” from the LSST Science Collaborations. This requires time and effort both in the Project and in the Collaborations. +} +\activities{ +A major activity here is to identify the most important DDF-specific science drivers and identify any processing requirements that are distinct from the Deep-Wide survey. This ought to be coordinated with the Project and the other Science Collaborations to provide a coherent set of specifications and priorities. +\\ +Another major activity is to develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection) This may stress the inputs to the image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low-surface brightness features. Use of the supporting data sets in level 2 or level 3 processing requires careful thought. For example, source identification and photometry can be improved using pixel-level information for either Euclid or WFIRST. However, this will not be available for all the DDFs and is not in the baseline plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The collaborations need to work with the various projects to identify a clear path forward.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Science drivers and input to the development of level 2 processing of the DDFs. +\item Specifications for galaxy-evolution oriented level-3 DDF processing +\item Specifications for data-processing using supporting data from other facilities +\item Simulations tailored to the DDFs +\item Level 3 processing code +\end{enumerate} +} +\end{task} + +\end{tasklist} + + \ No newline at end of file diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index d6a10a2..8031f30 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -14,6 +14,8 @@ %\input{task_lists/weak_lensing/weak_lensing.tex} \input{task_lists/agn/agn.tex} +\input{task_lists/clss/clss.tex} +\input{task_lists/ddf/ddf.tex} \input{task_lists/galaxies/galaxies.tex} 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--git a/.gitignore b/.gitignore index e4e3b17..151b8f3 100644 --- a/.gitignore +++ b/.gitignore @@ -13,7 +13,6 @@ # these rules might exclude image files for figures etc. # *.ps # *.eps -# *.pdf ## Bibliography auxiliary files (bibtex/biblatex/biber): *.bbl diff --git a/Makefile b/2016/Makefile similarity index 100% rename from Makefile rename to 2016/Makefile diff --git a/README.md b/2016/README.md similarity index 100% rename from README.md rename to 2016/README.md diff --git a/SciBook.bst b/2016/SciBook.bst similarity index 100% rename from SciBook.bst rename to 2016/SciBook.bst diff --git a/VersionDate.begin b/2016/VersionDate.begin similarity index 100% rename from VersionDate.begin rename to 2016/VersionDate.begin diff --git a/VersionDate.end b/2016/VersionDate.end similarity index 100% rename from VersionDate.end rename to 2016/VersionDate.end diff --git a/2016/VersionDate.tex b/2016/VersionDate.tex new file mode 100644 index 0000000..590c876 --- /dev/null +++ b/2016/VersionDate.tex @@ -0,0 +1,4 @@ +\begin{center} +Version +December 20, 2016 +\end{center} diff --git a/2016/abstract.tex b/2016/abstract.tex new file mode 100644 index 0000000..d37ca9f --- /dev/null +++ b/2016/abstract.tex @@ -0,0 +1,9 @@ +\begin{center} + +\vspace*{30mm} + +{\bf Abstract.} + +TBD + +\end{center} diff --git a/2016/apj.bst b/2016/apj.bst new file mode 100644 index 0000000..71f0966 --- /dev/null +++ b/2016/apj.bst @@ -0,0 +1,1615 @@ + +%% 1998/08/12 J Baker +%% Tweaked by hand to get correct results for ApJ. Added functions from +%% astrobib. + +%% $Log: apj.bst,v $ +%% Revision 1.3 2000/04/20 22:17:50 jbaker +%% Fixed INBOOK bug, now works essentially like BOOK. +%% +%% Revision 1.2 1998/08/30 22:35:45 jbaker +%% Added RCS keywords. +%% + +%% +%% This is file `apj.bst', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% merlin.mbs (with options: `,ay,nat,nm-rev,nmdash,dt-beg,yr-per,note-yr,atit-u,jtit-x,jttl-rm,thtit-a,vnum-x,volp-com,jpg-1,pp-last,btit-rm,add-pub,pub-par,pre-edn,edby,edbyx,blk-com,fin-bare,ppx,ed,abr,ord,jabr,amper,em-x') +%% ---------------------------------------- +%% *** Bibliographic Style for ApJ *** +%% + %------------------------------------------------------------------- + % The original source file contains the following version information: + % \ProvidesFile{merlin.mbs}[1998/02/25 3.85a (PWD)] + % + % NOTICE: + % This file may be used for non-profit purposes. + % It may not be distributed in exchange for money, + % other than distribution costs. + % + % The author provides it `as is' and does not guarantee it in any way. + % + % Copyright (C) 1994-98 Patrick W. Daly + %------------------------------------------------------------------- + % For use with BibTeX version 0.99a or later + %------------------------------------------------------------------- + % This bibliography style file is intended for texts in ENGLISH + % This is an author-year citation style bibliography. As such, it is + % non-standard LaTeX, and requires a special package file to function properly. + % Such a package is natbib.sty by Patrick W. Daly + % The form of the \bibitem entries is + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Smith]{key}... + % The essential feature is that the label (the part in brackets) consists + % of the author names, as they should appear in the citation, with the year + % in parentheses following. There must be no space before the opening + % parenthesis! + % With natbib v5.3, a full list of authors may also follow the year. + % In natbib.sty, it is possible to define the type of enclosures that is + % really wanted (brackets or parentheses), but in either case, there must + % be parentheses in the label. + % The \cite command functions as follows: + % \citet{key} ==>> Jones et al. (1990) + % \citet*{key} ==>> Jones, Baker, and Smith (1990) + % \citep{key} ==>> (Jones et al., 1990) + % \citep*{key} ==>> (Jones, Baker, and Smith, 1990) + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.][]{key} ==>> (e.g. Jones et al., 1990) + % \citep[e.g.][p. 32]{key} ==>> (e.g. Jones et al., p. 32) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Smith + % \citeyear{key} ==>> 1990 + %--------------------------------------------------------------------- + +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ duplicate$ empty$ + 'pop$ + 'write$ + if$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {add.blank} +{ " " * before.all 'output.state := +} + +FUNCTION {date.block} +{ + skip$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ skip$ } + +FUNCTION {capitalize} +{ "u" change.case$ "t" change.case$ } + +FUNCTION {space.word} +{ " " swap$ * " " * } + + % Here are the language-specific definitions for explicit words. + % Each function has a name bbl.xxx where xxx is the English word. + % The language selected here is ENGLISH +FUNCTION {bbl.and} +{ "and"} + +FUNCTION {bbl.editors} +{ "eds." } + +FUNCTION {bbl.editor} +{ "ed." } + +FUNCTION {bbl.edby} +{ "edited by" } + +FUNCTION {bbl.edition} +{ "edn." } + +FUNCTION {bbl.volume} +{ "Vol." } + +FUNCTION {bbl.of} +{ "of" } + +FUNCTION {bbl.number} +{ "no." } + +FUNCTION {bbl.nr} +{ "no." } + +FUNCTION {bbl.in} +{ "in" } + +FUNCTION {bbl.pages} +{ "" } + +FUNCTION {bbl.page} +{ "" } + +FUNCTION {bbl.chapter} +{ "Ch." } +%{ "chap." } + +FUNCTION {bbl.techrep} +{ "Tech. Rep." } + +FUNCTION {bbl.mthesis} +{ "Master's thesis" } + +FUNCTION {bbl.phdthesis} +{ "PhD thesis" } + +FUNCTION {bbl.first} +{ "1st" } + +FUNCTION {bbl.second} +{ "2nd" } + +FUNCTION {bbl.third} +{ "3rd" } + +FUNCTION {bbl.fourth} +{ "4th" } + +FUNCTION {bbl.fifth} +{ "5th" } + +FUNCTION {bbl.st} +{ "st" } + +FUNCTION {bbl.nd} +{ "nd" } + +FUNCTION {bbl.rd} +{ "rd" } + +FUNCTION {bbl.th} +{ "th" } + +MACRO {jan} {"Jan."} + +MACRO {feb} {"Feb."} + +MACRO {mar} {"Mar."} + +MACRO {apr} {"Apr."} + +MACRO {may} {"May"} + +MACRO {jun} {"Jun."} + +MACRO {jul} {"Jul."} + +MACRO {aug} {"Aug."} + +MACRO {sep} {"Sep."} + +MACRO {oct} {"Oct."} + +MACRO {nov} {"Nov."} + +MACRO {dec} {"Dec."} + +FUNCTION {eng.ord} +{ duplicate$ "1" swap$ * + #-2 #1 substring$ "1" = + { bbl.th * } + { duplicate$ #-1 #1 substring$ + duplicate$ "1" = + { pop$ bbl.st * } + { duplicate$ "2" = + { pop$ bbl.nd * } + { "3" = + { bbl.rd * } + { bbl.th * } + if$ + } + if$ + } + if$ + } + if$ +} + +MACRO {acmcs} {"ACM Comput. Surv."} + +MACRO {acta} {"Acta Inf."} + +MACRO {cacm} {"Commun. ACM"} + +MACRO {ibmjrd} {"IBM J. Res. Dev."} + +MACRO {ibmsj} {"IBM Syst.~J."} + +MACRO {ieeese} {"IEEE Trans. Softw. Eng."} + +MACRO {ieeetc} {"IEEE Trans. Comput."} + +MACRO {ieeetcad} + {"IEEE Trans. Comput.-Aided Design Integrated Circuits"} + +MACRO {ipl} {"Inf. Process. Lett."} + +MACRO {jacm} {"J.~ACM"} + +MACRO {jcss} {"J.~Comput. Syst. Sci."} + +MACRO {scp} {"Sci. Comput. Programming"} + +MACRO {sicomp} {"SIAM J. Comput."} + +MACRO {tocs} {"ACM Trans. Comput. Syst."} + +MACRO {tods} {"ACM Trans. Database Syst."} + +MACRO {tog} {"ACM Trans. Gr."} + +MACRO {toms} {"ACM Trans. Math. Softw."} + +MACRO {toois} {"ACM Trans. Office Inf. Syst."} + +MACRO {toplas} {"ACM Trans. Prog. Lang. Syst."} + +MACRO {tcs} {"Theoretical Comput. Sci."} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}{, jj}{, f.}" format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.names.ed} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{f.~}{vv~}{ll}{, jj}" + format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", " * bbl.editors * } + { ", " * bbl.editor * } + if$ + } + if$ +} + +FUNCTION {format.in.editors} +{ editor empty$ + { "" } + { editor format.names.ed + } + if$ +} + +FUNCTION {format.note} +{ note empty$ + { "" } + { note #1 #1 substring$ + duplicate$ "{" = + 'skip$ + { output.state mid.sentence = + { "l" } + { "u" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title + } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.key.full} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.key.full} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {editor.key.full} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.full + { type$ "proceedings" = + 'editor.key.full + 'author.key.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[{" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "}]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {word.in} +{ bbl.in + " " * } + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * "; set to ????" * warning$ + pop$ "????" } + 'skip$ + if$ + extra.label * + before.all 'output.state := + after.sentence 'output.state := +} + +FUNCTION {format.btitle} +{ title +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { bbl.volume volume tie.or.space.connect + series empty$ + 'skip$ + { bbl.of space.word * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { bbl.number } + { bbl.number capitalize } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { bbl.in space.word * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {is.num} +{ chr.to.int$ + duplicate$ "0" chr.to.int$ < not + swap$ "9" chr.to.int$ > not and +} + +FUNCTION {extract.num} +{ duplicate$ 't := + "" 's := + { t empty$ not } + { t #1 #1 substring$ + t #2 global.max$ substring$ 't := + duplicate$ is.num + { s swap$ * 's := } + { pop$ "" 't := } + if$ + } + while$ + s empty$ + 'skip$ + { pop$ s } + if$ +} + +FUNCTION {convert.edition} +{ edition extract.num "l" change.case$ 's := + s "first" = s "1" = or + { bbl.first 't := } + { s "second" = s "2" = or + { bbl.second 't := } + { s "third" = s "3" = or + { bbl.third 't := } + { s "fourth" = s "4" = or + { bbl.fourth 't := } + { s "fifth" = s "5" = or + { bbl.fifth 't := } + { s #1 #1 substring$ is.num + { s eng.ord 't := } + { edition 't := } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + t +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { convert.edition "l" change.case$ " " * bbl.edition * } + { convert.edition "t" change.case$ " " * bbl.edition * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check +% { bbl.pages pages n.dashify tie.or.space.connect } +% { bbl.page pages tie.or.space.connect } + { pages n.dashify } + { pages } + if$ + } + if$ +} + +FUNCTION {first.page} +{ 't := + "" + { t empty$ not t #1 #1 substring$ "-" = not and } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + while$ +} + +FUNCTION {format.journal.pages} +{ pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { + ", " * + pages first.page * + } + if$ + } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + { "" } + { type empty$ + { bbl.chapter } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { word.in booktitle emphasize * } + { word.in booktitle emphasize * + ", " * + editor num.names$ #1 > + { bbl.editors } + { bbl.editor } + if$ + * " " * + format.in.editors * + } + if$ + } + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { bbl.techrep } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + word.in + } + { bbl.volume volume tie.or.space.connect + bbl.of space.word * + } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} + +FUNCTION {format.publisher} +{ publisher empty$ + { "empty publisher in " cite$ * warning$ } + 'skip$ + if$ + "" + address empty$ publisher empty$ and + 'skip$ + { + add.blank "(" * + address empty$ + 'skip$ + { address * } + if$ + publisher empty$ + 'skip$ + { address empty$ + 'skip$ + { ": " * } + if$ + publisher * + } + if$ + ")" * + } + if$ + output +} + +STRINGS {oldname} + +FUNCTION {name.or.dash} +{ 's := + oldname empty$ + { s 'oldname := s } + { s oldname = + { "---" } + { s 'oldname := s } + if$ + } + if$ +} + +%%%%%%%% Functions added from astrobib + +FUNCTION {format.edn.btitle} % Title should be on stack. +{ duplicate$ empty$ edition empty$ or + 'skip$ + { ", " * format.edition * } + if$ +} + +FUNCTION {format.ed.booktitle} % The title should be on the stack. +{ duplicate$ empty$ + { "no book title in " cite$ * warning$ "" pop$ } + { editor empty$ + author empty$ or % Empty author means editor already given. + 'format.edn.btitle + { format.edn.btitle ", " * bbl.editor * " " * format.in.editors * } + if$ + } + if$ +} + +FUNCTION {format.full.book.spec} % The title should be on the stack. +{ series empty$ + { format.ed.booktitle + volume empty$ + { number empty$ + 'skip$ + { " there's a number but no series in " cite$ * warning$ + " No." number tie.or.space.connect * } + if$ + } + { ", Vol." volume tie.or.space.connect * + number empty$ + 'skip$ + {"Both volume and number fields in " * cite$ * warning$ } + if$ + } + if$ + } + { volume empty$ + { format.ed.booktitle ", " * series * + number empty$ + 'skip$ + { " No." number tie.or.space.connect * } + if$ + } + { series ", Vol." volume tie.or.space.connect * + ", " * swap$ format.ed.booktitle * + number empty$ + 'skip$ + {"Both volume and number fields in " * cite$ * warning$ } + if$ + } + if$ + } + if$ +} + +%%%%%%% End of functions from astrobib + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + crossref missing$ + { journal + "journal" output.check + format.vol.num.pages output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + format.journal.pages + format.note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + name.or.dash + } + { format.authors output.nonnull + name.or.dash + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% crossref missing$ +% { format.bvolume output +% format.number.series output +% format.edition output + format.publisher +% } +% { +% format.book.crossref output.nonnull +% } +% if$ + format.pages output + format.note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title "title" output.check + howpublished output + address output + format.note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + name.or.dash + } + { format.authors output.nonnull + name.or.dash + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% crossref missing$ +% { +% format.bvolume output +% format.chapter.pages "chapter and pages" output.check +% format.number.series output +% format.edition output + format.publisher +% } +% { +% format.chapter.pages "chapter and pages" output.check +% format.book.crossref output.nonnull +% } +% if$ + format.pages "pages" output.check + format.note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + bbl.in " " * booktitle format.full.book.spec * output +% crossref missing$ +% { format.in.ed.booktitle "booktitle" output.check +% format.bvolume output +% format.number.series output +% format.edition output +% format.chapter.pages output + format.publisher +% } +% { format.incoll.inproc.crossref output.nonnull +% format.chapter.pages output +% } +% if$ + format.pages "pages" output.check + format.note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output % added + format.date "year" output.check + date.block + bbl.in " " * booktitle format.full.book.spec * output +% crossref missing$ +% { format.in.ed.booktitle "booktitle" output.check +% format.bvolume output +% format.number.series output + publisher empty$ + { organization output + address output + } + { organization output + format.publisher + } + if$ +% } +% { format.incoll.inproc.crossref output.nonnull +% } +% if$ + format.pages output + format.note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.btitle "title" output.check + format.edition output + organization output + address output + format.note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + bbl.mthesis format.thesis.type output.nonnull + school "school" output.check + address output + format.note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title output + howpublished output + format.note output + fin.entry +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + bbl.phdthesis format.thesis.type output.nonnull + school "school" output.check + address output + format.note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output + organization format.key output } + { format.editors output } + if$ +% format.editors output +% editor format.key output + name.or.dash + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% format.bvolume output +% format.number.series output + publisher empty$ not % No need for warning if no pub. + { format.publisher } + { editor empty$ % For empty editor, organization was already given. + 'skip$ + { organization output } + if$ + address output + } + if$ +% address output +% organization output +% publisher output + format.pages output + format.note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title "title" output.check + format.tr.number output.nonnull + institution "institution" output.check + address output + format.note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + format.note "note" output.check + fin.entry +} + +FUNCTION {default.type} { misc } + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ + " {et~al.}" * + } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { + " {et~al.}" * + } + { " \& " * s #2 "{vv~}{ll}" format.name$ + * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.label} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.label + 'author.key.label + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + { pop$ "????" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv{ } }{ll{ }}{ f{ }}{ jj{ }}" + format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { t sortify * } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.sort} +{ editor empty$ + { key empty$ + { "to sort, need editor or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.sort + 'author.sort + if$ + } + if$ + #1 entry.max$ substring$ + 'sort.label := + sort.label + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { last.label next.extra } + +INTEGERS { last.extra.num number.label } + +FUNCTION {initialize.extra.label.stuff} +{ #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.extra.label.stuff} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} +%% End of customized bst file +%% +%% End of file `apj.bst'. diff --git a/2016/authorlist.tex b/2016/authorlist.tex new file mode 100644 index 0000000..723b2ad --- /dev/null +++ b/2016/authorlist.tex @@ -0,0 +1,16 @@ +Robertson, Brant$^{1}$, Banerji, M.$^{2}$, Cooper, Michael$^{3}$, Davies, R.$^{4}$, Ferguson, Henry C.$^{5}$, Kaviraj, S.$^{6}$, Lintott, C.$^{4}$, Lotz, J.$^{5}$, Newman, J.$^{7}$, Norman, D.$^{8}$, Padilla, N.$^{9}$, Schmidt, S.$^{10}$, Verma, A.$^{4}$, Working Group Participants, Collaboration Members + +\vspace*{5mm} + +{\centering\it\small +$^{1}$University of California, Santa Cruz, +$^{2}$Cambridge University, +$^{3}$University of California, Irvine, +$^{4}$Oxford University, +$^{5}$Space Telescope Science Institute, +$^{6}$University of Hertfordshire, +$^{7}$University of Pittsburgh, +$^{8}$National Optical Astronomical Observatory, +$^{9}$Pontifica Universidad Catolica de Chile, +$^{10}$University of California, Davis, +} diff --git a/bh.tex b/2016/bh.tex similarity index 100% rename from bh.tex rename to 2016/bh.tex diff --git a/chapterbib.sty b/2016/chapterbib.sty similarity index 100% rename from chapterbib.sty rename to 2016/chapterbib.sty diff --git a/deluxetable.sty b/2016/deluxetable.sty similarity index 100% rename from deluxetable.sty rename to 2016/deluxetable.sty diff --git a/enumitem.sty b/2016/enumitem.sty similarity index 100% rename from enumitem.sty rename to 2016/enumitem.sty diff --git a/2016/exgal_roadmap.pdf b/2016/exgal_roadmap.pdf new file mode 100644 index 0000000000000000000000000000000000000000..127c596653958ca04460a29b9ad0260a40095460 GIT binary patch literal 263122 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+% PACKAGES AND OTHER DOCUMENT CONFIGURATIONS +%---------------------------------------------------------------------------------------- + +\documentclass[11pt,fleqn]{book} % Default font size and left-justified equations +\usepackage{etoolbox} +\makeatletter +\patchcmd{\chapter}{\if@openright\cleardoublepage\else\clearpage\fi}{}{}{} +\makeatother + +\input{structure} % Insert the commands.tex file which contains the majority of the structure behind the template +% media9 is for embedding 3D objects, movies, and animations +%\usepackage{media9} + +\usepackage{booktabs} +\usepackage{pdflscape} +\newcommand{\ra}[1]{\renewcommand{\arraystretch}{#1}} +\usepackage{float} + + +\begin{document} + +%---------------------------------------------------------------------------------------- +% TITLE PAGE +%---------------------------------------------------------------------------------------- + +\begingroup +\thispagestyle{empty} +%\begin{tikzpicture}[remember picture,overlay] +%\coordinate [below=11cm] (midpoint) at (current page.north); +%\node at (current page.north west) +%{\begin{tikzpicture}[remember picture,overlay] +%\node[anchor=north west,inner sep=0pt] at (0,0) {\includegraphics[]{cover_page.pdf}}; % Background image +%\draw[anchor=north] (midpoint) node [fill=ocre!30!white,fill opacity=0.6,text opacity=1,inner sep=1cm]{\centering\bfseries\sffamily\parbox[c][][t]{\paperwidth}{\centering\color{blue}{\fontsize{70}{80}\selectfont Galaxies}\\[15pt] % Book title +%{\Huge a hands-on introduction}\\[60pt] % Subtitle +%{\Huge Andrey Kravtsov}}}; % Author name +%\end{tikzpicture}}; +%\end{tikzpicture} +%{\Huge\bfseries\scshape Large Synoptic Survey Telescope} +{\Huge Large Synoptic Survey Telescope} +\linebreak +\linebreak +{\Huge Galaxies, Dark Matter, and Black Holes: Extragalactic Roadmap} +\linebreak +\linebreak +%{\paperwidth}{\centering\color{blue}{\fontsize{70}{80}\selectfont Galaxies} +{\centering +\input{authorlist} +\input{VersionDate} +} +\vfill +\endgroup + +%---------------------------------------------------------------------------------------- +% COPYRIGHT PAGE +%---------------------------------------------------------------------------------------- +\newpage +\thispagestyle{empty} +\noindent +\noindent +\noindent +\\ +\noindent + +The LSST Extragalactic Roadmap represents the collective efforts of more than one hundred scientists to define the critical research activities to prepare our field to maximize +the science return of the LSST dataset. We want to thank the LSST Corporation for their +support in developing this Roadmap and for supporting LSST-related science more broadly. +We also wish to thank the LSST Galaxies Science Collaboration members for their efforts +over the years in developing the case for extragalactic science with LSST. Lastly, we +wish to thank Harry Ferguson for his continued efforts to organize this document.\\\\ +Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}). +%\newpage + +%~\vfill +%\thispagestyle{empty} + +%\noindent Copyright \copyright\ 2016 Andrey Kravtsov\\ % Copyright notice + +%\noindent \textsc{KICP Press}\\ % Publisher + +%\noindent \textsc{http://a-kravtsov.github.io/a304s16/}\\ % URL + +%\noindent Licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License (the ``License''). You may not use this file except in compliance with the License. You may obtain a copy of the License at \url{http://creativecommons.org/licenses/by-nc/3.0}. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \textsc{``as is'' basis, without warranties or conditions of any kind}, either express or implied. See the License for the specific language governing permissions and limitations under the License.\\ % License information + +%\noindent \textit{First printing, April 2016} % Printing/edition date + +%---------------------------------------------------------------------------------------- +% Table of Contents +%---------------------------------------------------------------------------------------- + +\usechapterimagefalse % If you don't want to include a chapter image, use this to toggle images off - it can be enabled later with \usechapterimagetrue + +\pagestyle{empty} % No headers + +\include{abstract} + + + +%\chapterimage{simulation_background.png} % Table of contents heading image + +\pagestyle{empty} % No headers + +\tableofcontents % Print the table of contents itself + +\cleardoublepage % Forces the first chapter to start on an odd page so it's on the right + +\nopagebreak[4] + +%\pagestyle{fancy} % Print headers again +\pagestyle{empty} % Print headers again + +%---------------------------------------------------------------------------------------- +% Chapters +%---------------------------------------------------------------------------------------- + + +% if it ever gets so big as to require Parts +%\part{Part One} +\pagestyle{empty} +\include{introduction/introduction} +\pagestyle{empty} +\include{science_background/science_background} +\pagestyle{empty} +\include{roadmap/roadmap} +\pagestyle{empty} +\include{task_lists/task_lists} + +%\include{matrix/matrix} + + + +%\chapterimage{ch2_header.png} % Chapter heading image +%\include{galaxy_formation} + +%\appendix +%\chapterimage{uvhudf.PNG} +%\include{cosmology_distances} +%\chapterimage{suppl_header.jpg} +%\include{supplementary} +%\chapterimage{python_xkcd2.PNG} +%\include{python} +%\chapterimage{sdss_data_banner.png} +%\include{data_access}%\appendix{Practical info on accessing various data sets} +%\chapterimage{banner_bookshelf.jpg} +%\printbibliography + +%---------------------------------------------------------------------------------------- +% INDEX +%---------------------------------------------------------------------------------------- + +%\cleardoublepage +%\phantomsection +%\setlength{\columnsep}{0.75cm} +%\addcontentsline{toc}{chapter}{\textcolor{ocre}{Index}} +%\printindex + +%---------------------------------------------------------------------------------------- + +\end{document} + +%------------------------------------------------ + +%\section{Figure}\index{Figure} + +%\begin{figure}[h] +%\centering\includegraphics[scale=0.5]{blanton_moustakas_wordcloud.pdf} +%\caption{Figure caption} +%\end{figure} + + +\begin{figure}[ht] +\includemedia[ +label=LG, +width=0.5\linewidth,height=0.5\linewidth, +activate=pageopen, +3Dtoolbar, 3Dmenu, +3Dviews=dice.vws, +]{}{fig/LG3d.u3d} +\end{figure} +\end{document} diff --git a/exgal_roadmap.tmp.tex b/2016/exgal_roadmap.tmp.tex similarity index 100% rename from exgal_roadmap.tmp.tex rename to 2016/exgal_roadmap.tmp.tex diff --git a/github_instructions.pdf b/2016/github_instructions.pdf similarity index 100% rename from github_instructions.pdf rename to 2016/github_instructions.pdf diff --git a/introduction/introduction.tex~ b/2016/introduction/introduction.tex similarity index 93% rename from introduction/introduction.tex~ rename to 2016/introduction/introduction.tex index e3da003..4c8def9 100644 --- a/introduction/introduction.tex~ +++ b/2016/introduction/introduction.tex @@ -9,7 +9,7 @@ telescope, designed to image a substantial fraction of the sky in six optical bands every few nights. It is planned to operate for a decade allowing the stacked images to detect galaxies to redshifts well beyond unity. The LSST and -the survey are designed to meet the requirements (Ivezic & the LSST Science +the survey are designed to meet the requirements (Ivezic \& the LSST Science Collaboration 2011) of a broad range of science goals in astronomy, astrophysics and cosmology. The LSST was the top-ranked large ground-based initiative in the 2010 National Academy of Sciences decadal survey in astronomy and astrophysics, @@ -48,8 +48,8 @@ science themes of these investigations, outlines how complementary techniques will contribute, and identifies areas where advance work is essential. For this advance work, the emphasis is on areas that are not adequately covered in the -DESC roadmap. As convenient shorthand, we use the acronym GCAL: Galaxies, -Clustering, AGN & Lensing, to describe this joint roadmap of the overlapping +DESC roadmap. As convenient shorthand, we use the acronym GALLA (Galaxies, AGN, Lensing +Large-scale Structure and Astro-informatics) joint roadmap of the overlapping science collaborations. Chapter \ref{ch:science_background} gives a brief summary of the science background. diff --git a/kapmono.cls b/2016/kapmono.cls similarity index 100% rename from kapmono.cls rename to 2016/kapmono.cls diff --git a/kapmono.sty b/2016/kapmono.sty similarity index 100% rename from kapmono.sty rename to 2016/kapmono.sty diff --git a/lineno.sty b/2016/lineno.sty similarity index 100% rename from lineno.sty rename to 2016/lineno.sty diff --git a/lsst_roadmap_section_template.py b/2016/lsst_roadmap_section_template.py similarity index 100% rename from lsst_roadmap_section_template.py rename to 2016/lsst_roadmap_section_template.py diff --git a/lsstexgal_outline_v1.pdf b/2016/lsstexgal_outline_v1.pdf similarity index 100% rename from lsstexgal_outline_v1.pdf rename to 2016/lsstexgal_outline_v1.pdf diff --git a/m-times.sty b/2016/m-times.sty similarity index 100% rename from m-times.sty rename to 2016/m-times.sty diff --git a/monops.sty b/2016/monops.sty similarity index 100% rename from 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--git a/science_background/old/black_holes/black_holes.tex b/2016/science_background/old/black_holes/black_holes.tex similarity index 100% rename from science_background/old/black_holes/black_holes.tex rename to 2016/science_background/old/black_holes/black_holes.tex diff --git a/science_background/old/informatics/informatics.tex b/2016/science_background/old/informatics/informatics.tex similarity index 100% rename from science_background/old/informatics/informatics.tex rename to 2016/science_background/old/informatics/informatics.tex diff --git a/science_background/old/lss/lss.tex b/2016/science_background/old/lss/lss.tex similarity index 100% rename from science_background/old/lss/lss.tex rename to 2016/science_background/old/lss/lss.tex diff --git a/science_background/old/strong_lensing/strong_lensing.tex b/2016/science_background/old/strong_lensing/strong_lensing.tex similarity index 100% rename from science_background/old/strong_lensing/strong_lensing.tex rename to 2016/science_background/old/strong_lensing/strong_lensing.tex diff --git a/science_background/old/weak_lensing/weak_lensing.tex b/2016/science_background/old/weak_lensing/weak_lensing.tex similarity index 100% rename from science_background/old/weak_lensing/weak_lensing.tex rename to 2016/science_background/old/weak_lensing/weak_lensing.tex diff --git a/2016/science_background/science_background.tex b/2016/science_background/science_background.tex new file mode 100644 index 0000000..87d8304 --- /dev/null +++ b/2016/science_background/science_background.tex @@ -0,0 +1,21 @@ + +% LSST Extragalactic Roadmap +% Chapter: science_background +% First draft by + +\chapter[Science Background]{Science Background} +\label{ch:science_background} + +TBD + +\input{science_background/chapterintro.tex} + + +\input{science_background/galaxies/galaxies.tex} + +%\input{science_background/black_holes/black_holes.tex} +%\input{science_background/informatics/informatics.tex} +%\input{science_background/lss/lss.tex} +%\input{science_background/strong_lensing/strong_lensing.tex} +%\input{science_background/weak_lensing/weak_lensing.tex} + diff --git a/2016/structure.tex b/2016/structure.tex new file mode 100644 index 0000000..c883372 --- /dev/null +++ b/2016/structure.tex @@ -0,0 +1,648 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% The Legrand Orange Book +% Structural Definitions File +% Version 2.0 (9/2/15) +% +% Original author: +% Mathias Legrand (legrand.mathias@gmail.com) with modifications by: +% Vel (vel@latextemplates.com) and Andrey Kravtsov (akravtsov@gmail.com) +% +% This file has been downloaded from: +% http://www.LaTeXTemplates.com +% +% License: +% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/) +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% The Legrand Orange Book +% LaTeX Template +% Version 2.1.1 (14/2/16) +% +% This template has been downloaded from: +% http://www.LaTeXTemplates.com +% +% Original author: +% Mathias Legrand (legrand.mathias@gmail.com) with modifications by: +% Vel (vel@latextemplates.com) +% +% License: +% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/) +% +% Compiling this template: +% This template uses biber for its bibliography and makeindex for its index. +% When you first open the template, compile it from the command line with the +% commands below to make sure your LaTeX distribution is configured correctly: +% +% 1) pdflatex main +% 2) makeindex main.idx -s StyleInd.ist +% 3) biber main +% 4) pdflatex main x 2 +% +% After this, when you wish to update the bibliography/index use the appropriate +% command above and make sure to compile with pdflatex several times +% afterwards to propagate your changes to the document. +% +% This template also uses a number of packages which may need to be +% updated to the newest versions for the template to compile. It is strongly +% recommended you update your LaTeX distribution if you have any +% compilation errors. +% +% Important note: +% Chapter heading images should have a 2:1 width:height ratio, +% e.g. 920px width and 460px height. +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%---------------------------------------------------------------------------------------- +% VARIOUS REQUIRED PACKAGES AND CONFIGURATIONS +%---------------------------------------------------------------------------------------- + +\usepackage[top=3cm,bottom=3cm,left=3cm,right=3cm,headsep=10pt]{geometry} % Page margins + +\usepackage{graphicx} % Required for including pictures +\usepackage{amsmath} +\usepackage{hyperref} +\usepackage{mathptmx} +\usepackage{anyfontsize} +\usepackage{t1enc} + +\graphicspath{{fig/}} % Specifies the directory where pictures are stored + +\usepackage{lipsum} % Inserts dummy text + +\usepackage{tikz} % Required for drawing custom shapes + +\usepackage[english]{babel} % English language/hyphenation + +\usepackage{enumitem} % Customize lists +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists + +\usepackage{booktabs} % Required for nicer horizontal rules in tables + +\usepackage{xcolor} % Required for specifying colors by name +%\definecolor{ocre}{RGB}{243,102,25} % Define the orange color used for highlighting throughout the book +%\definecolor{ocre}{RGB}{119,181,254} % Define the orange color used for highlighting throughout the book +\definecolor{ocre}{RGB}{3,22,168} % Define the orange color used for highlighting throughout the book + + +\usepackage{listings} +\usepackage{color} + +\definecolor{dkgreen}{rgb}{0,0.6,0} +\definecolor{gray}{rgb}{0.5,0.5,0.5} +\definecolor{mauve}{rgb}{0.58,0,0.82} + +\lstset{frame=tb, + language=Java, + aboveskip=3mm, + belowskip=3mm, + showstringspaces=false, + columns=flexible, + basicstyle={\small\ttfamily}, + numbers=none, + numberstyle=\tiny\color{gray}, + keywordstyle=\color{blue}, + 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+%---------------------------------------------------------------------------------------- + +%\usepackage[citestyle=authoryear,style=alphabetic,natbib=true,sorting=nyt,sortcites=true,autopunct=true,babel=hyphen,hyperref=true,abbreviate=false,backref=true,backend=biber]{biblatex} +\usepackage[backend=bibtex,style=authoryear,sortcites=true,autopunct=true,babel=hyphen,hyperref=true,abbreviate=false,backref=false,natbib]{biblatex} +%\usepackage{natbib} +%\newcommand{\citep}{\autocite} +%\newcommand{\citet}{\textcite} +%\newcommand{\citealp}{\cite} +\addbibresource{galaxies.bib} % BibTeX bibliography file +%\defbibheading{bibempty}{} + +\usepackage{calc} % For simpler calculation - used for spacing the index letter headings correctly +\usepackage{makeidx} % Required to make an index +\makeindex % Tells LaTeX to create the files required for indexing + +%---------------------------------------------------------------------------------------- +% MAIN TABLE OF CONTENTS +%---------------------------------------------------------------------------------------- + +\usepackage{titletoc} % Required for manipulating the table of contents + +\contentsmargin{0cm} % Removes the default margin + +% Part text styling +\titlecontents{part}[0cm] +{\addvspace{20pt}\centering\large\bfseries} +{} +{} +{} + +% Chapter text styling +\titlecontents{chapter}[1.25cm] % Indentation +{\addvspace{12pt}\large\sffamily\bfseries} % Spacing and font options for chapters +{\color{ocre!60}\contentslabel[\Large\thecontentslabel]{1.25cm}\color{ocre}} % Chapter number +{\color{ocre}} +{\color{ocre!60}\normalsize\;\titlerule*[.5pc]{.}\;\thecontentspage} % Page number + +% Section text styling +\titlecontents{section}[1.25cm] % Indentation +{\addvspace{3pt}\sffamily\bfseries} % Spacing and font options for sections +{\contentslabel[\thecontentslabel]{1.25cm}} % Section number +{} +{\hfill\color{black}\thecontentspage} % Page number +[] + +% Subsection text styling 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+{\color{ocre}\contentslabel[\Large\thecontentslabel]{1.25cm}\color{ocre}} % Chapter number +{} +{\color{ocre}\normalsize\sffamily\bfseries\;\titlerule*[.5pc]{.}\;\thecontentspage} % Page number + +% Section text styling +\titlecontents{lsection}[0em] % Indenting +{\sffamily\small} % Spacing and font options for sections +{\contentslabel[\thecontentslabel]{1.25cm}} % Section number +{} +{} + +% Subsection text styling +\titlecontents{lsubsection}[.5em] % Indentation +{\normalfont\footnotesize\sffamily} % Font settings +{} +{} +{} + +%---------------------------------------------------------------------------------------- +% PAGE HEADERS +%---------------------------------------------------------------------------------------- + +\usepackage{fancyhdr} % Required for header and footer configuration + +\pagestyle{fancy} +\renewcommand{\chaptermark}[1]{\markboth{\sffamily\normalsize\bfseries\chaptername\ \thechapter.\ #1}{}} % Chapter text font settings 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+\theoremstyle{ocrenumbox} +\newtheorem{theoremeT}[dummy]{Theorem} +\newtheorem{problem}{Problem}[chapter] +\newtheorem{exerciseT}{Exercise}[chapter] +\theoremstyle{blacknumex} +\newtheorem{exampleT}{Example}[chapter] +\theoremstyle{blacknumbox} +\newtheorem{vocabulary}{Vocabulary}[chapter] +\newtheorem{definitionT}{Definition}[section] +\newtheorem{corollaryT}[dummy]{Corollary} +\theoremstyle{ocrenum} +\newtheorem{proposition}[dummy]{Proposition} + +%---------------------------------------------------------------------------------------- +% DEFINITION OF COLORED BOXES +%---------------------------------------------------------------------------------------- + +\RequirePackage[framemethod=default]{mdframed} % Required for creating the theorem, definition, exercise and corollary boxes + +% Theorem box +\newmdenv[skipabove=7pt, +skipbelow=7pt, +backgroundcolor=black!5, +linecolor=ocre, +innerleftmargin=5pt, +innerrightmargin=5pt, +innertopmargin=5pt, +leftmargin=0cm, +rightmargin=0cm, 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type of theorem and assigns it a theorem text style from the "Theorem Styles" section above and a colored box from above +\newenvironment{theorem}{\begin{tBox}\begin{theoremeT}}{\end{theoremeT}\end{tBox}} +\newenvironment{exercise}{\begin{eBox}\begin{exerciseT}}{\hfill{\color{ocre}\tiny\ensuremath{\blacksquare}}\end{exerciseT}\end{eBox}} +\newenvironment{definition}{\begin{dBox}\begin{definitionT}}{\end{definitionT}\end{dBox}} +\newenvironment{example}{\begin{exampleT}}{\hfill{\tiny\ensuremath{\blacksquare}}\end{exampleT}} +\newenvironment{corollary}{\begin{cBox}\begin{corollaryT}}{\end{corollaryT}\end{cBox}} + +%---------------------------------------------------------------------------------------- +% REMARK ENVIRONMENT +%---------------------------------------------------------------------------------------- + +\newenvironment{remark}{\par\vspace{10pt}\small % Vertical white space above the remark and smaller font size +\begin{list}{}{ +\leftmargin=35pt % Indentation on the left 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+\node[anchor=south east] at (\paperwidth-1cm,-\paperheight+1cm){\parbox[t][][t]{8.5cm}{ +\printcontents{l}{0}{\setcounter{tocdepth}{1}}% +}}; +\node[anchor=north east] at (\paperwidth-1.5cm,-3.25cm){\parbox[t][][t]{15cm}{\strut\raggedleft\color{white}\fontsize{30}{30}\sffamily\bfseries#2}}; +\end{tikzpicture}}; +\end{tikzpicture}}% +\@endpart} +\def\@spart#1{% +\startcontents% +\phantomsection +{\thispagestyle{empty}% +\begin{tikzpicture}[remember picture,overlay]% +\node at (current page.north west){\begin{tikzpicture}[remember picture,overlay]% +\fill[ocre!20](0cm,0cm) rectangle (\paperwidth,-\paperheight); +\node[anchor=north east] at (\paperwidth-1.5cm,-3.25cm){\parbox[t][][t]{15cm}{\strut\raggedleft\color{white}\fontsize{30}{30}\sffamily\bfseries#1}}; +\end{tikzpicture}}; +\end{tikzpicture}} +\addcontentsline{toc}{part}{\texorpdfstring{% +\setlength\fboxsep{0pt}% +\noindent\protect\colorbox{ocre!40}{\strut\protect\parbox[c][.7cm]{\linewidth}{\Large\sffamily\protect\centering #1\quad\mbox{}}}}{#1}}% +\@endpart} +\def\@endpart{\vfil\pagebreak%\newpage +\if@twoside +\if@openright +\null +\thispagestyle{empty}% +%\newpage +\pagebreak +\fi +\fi +\if@tempswa +\twocolumn +\fi} + +%---------------------------------------------------------------------------------------- +% CHAPTER HEADINGS +%---------------------------------------------------------------------------------------- + +% A switch to conditionally include a picture, implemented by Christian Hupfer +\newif\ifusechapterimage +\usechapterimagetrue +\newcommand{\thechapterimage}{}% +\newcommand{\chapterimage}[1]{\ifusechapterimage\renewcommand{\thechapterimage}{#1}\fi}% +\def\@makechapterhead#1{% +{\parindent \z@ \raggedright \normalfont +\ifnum \c@secnumdepth >\m@ne +\if@mainmatter +\begin{tikzpicture}[remember picture,overlay] +\node at (current page.north west) +{\begin{tikzpicture}[remember picture,overlay] +\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; +%rounded box +%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}\thechapter. #1\strut}; +\end{tikzpicture}}; +\end{tikzpicture} +\else +\begin{tikzpicture}[remember picture,overlay] +\node at (current page.north west) +{\begin{tikzpicture}[remember picture,overlay] +\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; +%rounded box +%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; +\end{tikzpicture}}; +\end{tikzpicture} +\fi\fi\par\vspace*{270\p@}}} + +%------------------------------------------- + +\def\@makeschapterhead#1{% +\begin{tikzpicture}[remember picture,overlay] +\node at (current page.north west) +{\begin{tikzpicture}[remember picture,overlay] +\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; +%rounded box +%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; +\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; +\end{tikzpicture}}; +\end{tikzpicture} +%\par\vspace*{270\p@}} +\par\vspace*{170\p@}} +%\par\vspace*{100\p@}} +\makeatother + +%---------------------------------------------------------------------------------------- +% HYPERLINKS IN THE DOCUMENTS +%---------------------------------------------------------------------------------------- + +\usepackage{hyperref} +\hypersetup{hidelinks,backref=true,pagebackref=true,hyperindex=true,colorlinks=false,breaklinks=true,urlcolor= ocre,bookmarks=true,bookmarksopen=false,pdftitle={Title},pdfauthor={Author}} +\usepackage{bookmark} +\bookmarksetup{ +open, +numbered, +addtohook={% +\ifnum\bookmarkget{level}=0 % chapter +\bookmarksetup{bold}% +\fi +\ifnum\bookmarkget{level}=-1 % part +\bookmarksetup{color=ocre,bold}% +\fi +} +} + + +%------------------------------------------------------------------------------% +% Task formatting: + +% PJM: description environment for tasks, needs(?) +% item heading macros, to allow global editing, and italic headings. + +% \renewcommand\descriptionlabel[1]{\hspace{\labelsep}{\textsl{#1}}} +% \def\motivation{Motivation:} +% \def\activities{Activities:} +% \def\deliverables{Deliverables:} + +% Example usage: +% +% \begin{description} +% \item[\motivation] Currently things are bad. +% \item[\activities] We will work to make them better. +% \item[\deliverables] Code to solve all problems. +% \end{description} + + +% PJM: The following macro works, but is not very transparent to the writer... +% \def\task#1#2#3% +% {\begin{description} +% \item[Motivation]{#1} +% \item[Activities]{#2} +% \item[Deliverables]{#3} +% \end{description}} + +% Example usage: +% +% \task +% {Currently things are bad.} +% {We will work to make them better.} +% {Code to solve all problems.} + + +% PJM: OK, this is better - now only task items are italicised, and we have +% control over all tasks: + +\def\motivation#1{\item[Motivation:] #1} +\def\activities#1{\item[Activities:] #1} +\def\deliverables#1{\item[Deliverables:] #1} + +\newenvironment{task}% +{\renewcommand\descriptionlabel[1]{\hspace{\labelsep}\textit{##1}} + \begin{description}\setlength{\itemsep}{0.15\baselineskip}} +{\end{description}} + +% Example usage: +% +% \begin{task} +% \motivation{Currently things are bad}. +% \activities{We will work to make them better}. +% \deliverables{Code to solve all problems}. +% \end{task} + +% PJM: here's a tasklist environment to take care of Michael's enumeration: + +\def\tasktitle#1{\item{\bf #1}} + +\newenvironment{tasklist}[1]% +{\begin{enumerate}[label=#1-\arabic{*}.,ref=\thesubsection:#1-\arabic{*},font=\bf]} +{\end{enumerate}} + +% Example usage: +% +% \begin{tasklist}{H} +% \tasktitle{Automated Lens Candidate Detection in the LSST Catalogs [Lupton]} +% \label{task:sl:detection} +% \begin{task} +% \motivation{Currently things are bad}. +% \activities{We will work to make them better}. +% \deliverables{Code to solve all problems}. +% \end{task} +% \end{tasklist} diff --git a/2016/task_lists/agn/agn.tex b/2016/task_lists/agn/agn.tex new file mode 100644 index 0000000..fbd0e2c --- /dev/null +++ b/2016/task_lists/agn/agn.tex @@ -0,0 +1,127 @@ +\section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} + +AGN are phenomena that enable us to understand the growth of BHs, understand aspects of galaxy evolution, probe the high redshift universe and study other physical activity, including accretion physics, jets, magnetic fields, etc. There are distinct aspects of the study of AGN that can best be explored by considering AGN as an evolutionary stage of galaxies rather than a distinct type of source. The tasks listed here explore aspects of AGN study that are particularly important AGN as a stage in galaxy evolution. + +\begin{tasklist}{AGN} +\tasktitle{AGN feedback in clusters} +\begin{task} +\label{task:agn:feedback_in_clusters} +\motivation{ +Brightest Cluster/Group Galaxies (hereafter BCGs) are the most massive galaxies in the local Universe residing at/near the centres of galaxy clusters/groups. They will therefore contain the largest supermassive black holes. These black holes can influence their host BCG, the cluster gas and other cluster members via the mechanical energy produced by their 100s kpc scale jets (AGN feedback). +\\ +For low redshift galaxy clusters it is possible to perform detailed studies of the star, gas and AGN jets to analyse the details of AGN feedback. LSST will provide a large sample of moderate to high redshift clusters in which we can measure AGN feedback statistically. By combining X-ray, radio and optical observations we can assess the average influence of the BCG's AGN on the hot Intra-cluster medium (ICM) for different sub-populations [e.g. Stott et al. 2012]. +} +\activities{ +By assembling a multi-wavelength dataset (optical, X-ray, Radio) we can obtain the BCG mass, cluster mass and ICM temperature, and the mechanical power injected into the ICM. We can use this to study the interplay between the BCG, its black hole and the cluster gas, to assess the balance of energies involved and for direct comparison with theoretical models of AGN feedback. This has been done with a few hundred clusters at z<0.3 using SDSS but we may well be able to reach z=1 and therefore look for an evolution in their interplay and therefore AGN feedback. There are also implications for cosmology too as this will help with the selection of clusters for which the X-ray properties better represent the mass of the cluster rather than the complex interplay of baryonic physics. } + +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Investigate the number of BCGs and the mass range of their clusters with redshift that LSST is likely to be able to observe. +\item Assess radio and X-ray data available for AGN Feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS etc). +\item Assess the theoretical predictions expected for the above (e.g. cosmological simulations such as EAGLE or more detailed single cluster studies). +\end{enumerate} +} +\end{task} +%\end{tasklist} + + +%\begin{tasklist}{T} +\tasktitle{AGN Selection from LSST Data} +\begin{task} +\label{task:agn:selection} +\motivation{ +Active Galactic Nuclei are selected using a variety of different methods. At optical and infrared wavelengths, photometric selection of AGN candidates is driven by their distinctive colors at particular redshifts. X-ray and radio observations can also be efficient selectors of candidates for additional follow-up. With spectral data, AGN can be selected using the ratios of their emission lines. LSST will also open up, in a more practical way, the identification of AGN based on their variability. +Each of these samples probes aspects of the AGN phenomena and a better understanding of the AGN role in galaxy evolution requires that we understand how and why each of these selection methods includes or excludes particular sources. Furthermore, currently each of these methods for identifying AGN candidates requires spectral follow-up to cull these samples to positively identify the most reliably clean AGN sample. +} +\activities{ +For us to use LSST as a single way to identify the diversity of AGN, we must develop selection criteria that take advantage of the source parameters available with just LSST imaging, that is, color, morphology and variability. Already there are a number of AGN surveys with input from multiple wavelength observation and spectra. Precursor work needs to be done using these surveys to determine if AGN not easily identified using optical color selection can be selected using the additional parameters of morphology, variability and/or the additional filter that LSST provides. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Cross-matched catalog of known AGN selected and verified using different methods +\item Development of morphology parameters beyond just star/galaxy separation and an understanding of the morphology parameters to be provided by LSST level 2 products. +\item Development of color selection criteria that takes into account the morphology of the source +\item Understanding of how AGN variability looks given the nominal LSST cadence +\item Development of algorithms for color selection that take into account the variability of an AGN source +\end{enumerate} +} +\end{task} +%\end{tasklist} + + +%\begin{tasklist}{T} +\tasktitle{AGN Host Galaxy Properties from LSST Data} +\begin{task} +\label{task:agn:host_galaxies} +\motivation{ +We are requesting that basic morphological parameters (e.g., CAS, G-M20, etc.) be measured in the pipeline and made available as products to help in the identification of merging galaxies in LSST data. The issue here is how well this can be done when the host galaxies contain AGN that are likely identified via their variability. In other words, how well can we determine the host morphology of galaxies with variable AGN? This would be interesting for models of AGN fueling during mergers. +} +\activities{ +Simulations of the accuracy by which the pipeline (deblender) can measure the defined morphology parameters in host galaxies as a function of AGN brightness and wavelength. We could then ``vary'' the central source by expected levels in certain filters to see the effect on the morphological params. To constrain this it would be helpful to add in central sources with reasonable SEDs across the LSST bands, and a limited set of frequencies/amplitudes (based on real data - perhaps Pan-STARRS?). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Plots of the accuracy of the measured basic morphology parameters as a function of AGN brightness and wavelength. +\item Effect of AGN brightness on classification diagrams. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\tasktitle{AGN Variability Selection in LSST Data} +\begin{task} +\label{task:agn:variability} +\motivation{ +Most AGN exhibit broad-band aperiodic, stochastic variability across the entire EM spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, making it a powerful probe of accretion physics. The main LSST WFD survey will obtain $\sim10^8$ AGN light curves (i.e. flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. The deep drilling fields will give us AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will critically depend on the interval between observations in individual filter bands. It is of crucial importance to determine guidelines for an optimal survey strategy (from an AGN variability perspective) and determine what biases and uncertainties are introduced into AGN variability science as a result of the chosen survey strategy.} +\activities{ +Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate \& study simulations using parameters selected from these models with the observationally determined constraints to determine goodness of simulations for carrying out various types of AGN variability science - PSD models, QPO searches, binary AGN models, etc. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Observational constraints on AGN variability models. +\item MAF metrics quantifying the goodness of different survey strategies for AGN variability science. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\tasktitle{AGN Photometric Redshifts from LSST Data} +\begin{task} +\label{task:agn:photoz} +\motivation{ +Given the large number of AGN that will be observed with LSST, many of these will not be followed up with spectral observations. However, understanding the large scale structure of the universe, requires a 3-D understanding of the distribution of these galaxies in the universe. Photometric redshifts can provide relatively accurate redshifts for large numbers of galaxies. However, it is harder to obtain accurate photometric redshifts for galaxies that contain AGN compared to those that do not. We must understand how to get accurate photometric redshifts of galaxies with AGN. +} +\activities{ +An initial activity for this need to include comprehensive review of the state of the art in obtaining photo-z’s for AGN host galaxy populations and how those compare to non-AGN galaxies. A comparison of model and/or observed AGN host SEDs with a matched set of non-host galaxies at a variety of redshifts will be used to determine color selection criteria for identifying AGN hosts. Explore whether variability can be used to break degeneracies. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Plots that show AGN host color selection criteria and where that color selection might become ambiguous (be degenerate) for non-host galaxies with different parameters. +\item Plots that show if other parameters might break degeneracies. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\tasktitle{AGN Merger Signature from LSST Data} +\begin{task} +\label{task:agn:mergers} +\motivation{ +Understanding the role AGN play in galaxy evolution requires identifying the phenomenon at all stages and in all types of galaxies. AGN host galaxies are often found to be disturbed suggesting that the galaxy merger process is an important trigger of AGN activity. While the ‘trainwrecks’ may be easier to find, galaxies in other merger stages can be difficult to identify and those experiencing ‘pre-merger’ harassment may be particularly hard to recognize. Preliminary work needs to be done to understand how to identify mergers from the LSST data products and whether galaxy deblending and segmentation methods and procedures are adequate or mask galaxy mergers. +} +\activities{ +Create or Identify simulated and real images that contain known galaxy mergers, these images should contain mergers with and without AGN. +Run LSST detection and identification software on these images. +Identify metrics that describe/quantify the accurate detection of galaxy mergers (with and without AGN). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Give feedback to LSST software teams about metrics and detection of galaxy mergers +\item Give feedback on structure or galaxy type that do and do not work well with current versions of LSST software +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/task_lists/chapter_intro.tex b/2016/task_lists/chapter_intro.tex similarity index 100% rename from task_lists/chapter_intro.tex rename to 2016/task_lists/chapter_intro.tex diff --git a/task_lists/chapterintro.tex b/2016/task_lists/chapterintro.tex similarity index 100% rename from task_lists/chapterintro.tex rename to 2016/task_lists/chapterintro.tex diff --git a/2016/task_lists/clss/clss.tex b/2016/task_lists/clss/clss.tex new file mode 100644 index 0000000..c7115ed --- /dev/null +++ b/2016/task_lists/clss/clss.tex @@ -0,0 +1,324 @@ +\section{Clusters and Large Scale Structure}\label{sec:tasks:clss} + +Summary + +\begin{tasklist}{CLSS} +\tasktitle{Cluster/LSS Sample Emulator} +\begin{task} +\label{task:clss:emulator} +\motivation{ +To prepare for galaxies and galaxy group/cluster science with LSST, we +need to know how many galaxies will be detected in a given range of +redshift, brightness, color, etc., and likewise how many groups and +clusters will be detected in given ranges of redshift, richness, mass, +and other physical parameters. +} +\activities{ +LSST has advanced simulations of its 10-year Wide Fast Deep survey +available from the Operations Simulator. The output databases can be +analyzed to determine the depth LSST is expected to reach in its final +detection image at each sky location, and Awan et al.~2016 +(http://adsabs.harvard.edu/abs/2016ApJ...829…50A) turns these depths +into predicted numbers of galaxies as a function of redshift and +brightness. +\\ +To predict galaxy sample sizes as a function of physical parameters, +the ``raw'' predicted galaxy numbers from Awan et al.~(2016) will be +interfaced with semi-analytical models painted on large N-body +simulations by Risa Wechsler and collaborators. This will extend the +predictions to include observed properties of color, size, morphology +and physical properties of halo mass, stellar mass, and star formation +rate. +\\ +To predict group/cluster sample sizes as a function of physical +parameters, the properties such as temperature, richness, etc., will +be painted on to dark matter halos drawn from a numerical simulation. +The properties will be based on simple scaling laws, with the user +allowed freedom to choose the parameters of the scaling laws, +including how they evolve. This will then be interfaced with the +``raw'' predicted galaxy numbers from Awan et al.~(2016), to determine +which of the groups and clusters should be detectable in the LSST +data.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Create a public LSST Extragalactic Sample Emulator with a +simple GUI. Enable user input of a range of redshift, and +physical parameters (e.g.~galaxy magnitudes, colors, size, morphology, +cluster richness, mass, temperature, etc.) to estimate the size of a +given sample detected by LSST. +\end{enumerate} +} +\end{task} + + +\tasktitle{Identifying and Characterizing Clusters} +\begin{task} +\label{task:clss:clusters} +\motivation{ +LSST photometry will make it possible to +search for and study the galaxy populations of distant clusters and +proto-clusters over huge volumes of the high-$z$ Universe. These +clusters are testbeds for cosmology, hierarchical structure formation, +intergalactic medium heating and metal enrichment, as well as +laboratories for studying galaxy evolution. +However, standard approaches for identifying clusters, such as the red +sequence method, will be hampered by the limited wavelength coverage +of LSST. +For example, at $z \gtrsim 1.5$, near-IR photometry is required to +identify systems with Balmer/$4000$\AA\ breaks. +To maximize cluster science with LSST, we must devise new techniques +for cluster identification as well as incorporate complementary data +from projects such as \emph{Euclid}, \emph{eROSITA}, etc. +} +\activities{ +Using existing imaging datasets and simulations, algorithms need to be +developed and optimised to identify clusters at intermediate +and high redshift within the LSST footprint. +Specifically, this work should characterize the selection +function, completeness, and contamination rate for different cluster +identification algorithms. +This requires realistic light-cone simulations spanning extremely +large volumes, so as to capture significant numbers ($\gg10,000$) of +simulated galaxy clusters at high $z$. +Potential algorithms to be tested include adaptations of RedMaPPer +(Rykoff et al.~2014) as well as methods that search for galaxy +overdensities over a range of scales (e.g.~Chiang et al.~2014; Wang et +al.~2016). +In parallel, a comprehensive search for multiwavelength data +(specifically IR and X-ray imaging) is needed to aid in the search for +high-$z$ clusters and in the confirmation and characterization of +systems at all redshifts.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item The primary product of this analysis will be improved cluster +identification algorithms that can be applied to LSST data once +science operations commence. +\item In addition, this work will produce a compilation of ancillary data +that will be helpful in cluster identification and characterization, +such as X-ray (e.g.~XCS, eROSITA, etc.), SZ (Planck, SPT, ACT) and +radio (SKA and its pathfinders, SUMSS), within the LSST footprint. +\end{enumerate} +} +\end{task} + + + + +\tasktitle{Developing and Optimizing Measurements of Galaxy Environment} +\begin{task} +\label{task:clss:environment} +\motivation{ +Over the past decade, many studies have +shown that ``environment'' plays a important role in shaping galaxy +properties. For example, satellite galaxies in the local Universe +exhibit lower star formation rates, more bulge-dominated morphologies, +as well as older and more metal-rich stellar populations when compared +to isolated (or ``field'') systems of equivalent stellar mass (Baldry +et al.~2006; Cooper et al.~2010; Pasquali et al.~2010). +Unlike spectroscopic surveys, LSST will lack the precise line-of-sight +velocity measurements to robustly identify satellite galaxies in +lower-mass groups, where the expected photo-$z$ precision will greatly +exceed the velocity dispersion of the host halo. +Instead, LSST will likely be better suited to measuring environment by +tracing the local galaxy density (and identifying filaments). However, +LSST is unlike any previous photometric survey and may require new +approaches to measuring environment. +The challenge remains to find the measure(s) of local galaxy density +with the greatest sensitivity to the true underlying density field (or +to host halo mass, etc.), so as to enable analyses of environment's +role in galaxy evolution with LSST. +} +\activities{ +Using mock galaxy catalogs created via +semi-analytic techniques, we will compare different tracers of local +galaxy density (i.e.~''environment'') measured on mock LSST +photometric samples to the underlying real-space density of galaxies +(or to host halo mass). In addition to testing existing density +measures, such as $N^{\rm th}$-nearest-neighbor distance and counts in +a fixed aperture, we will explore new measures that may be better +suited to LSST. For each measure, we will examine the impact of +increasing survey depth and photo-$z$ precision over the course of the +survey.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item With an improved understanding of the +strengths and weaknesses of different environment measures as applied +to LSST, this effort will yield code to measure local galaxy density +(likely in multiple ways) within the LSST dataset. +\item Create a Level 3 data product for use by the entire project. +\end{enumerate} +} +\end{task} + +\tasktitle{Enabling and Optimizing Measurements of Galaxy Clustering} +\begin{task} +\label{task:clss:clustering} +\motivation{ +Contemporary galaxy surveys have +transformed the study of large-scale structure, enabling high +precision measurements of clustering statistics. The correlation +function provides the most fundamental way to characterize the galaxy +distribution. The dependence of clustering on galaxy properties and +the evolution of clustering provide fundamental constraints on +theories of galaxy formation and evolution. Interpreting these +measurements provides crucial insight into the relation between +galaxies and dark matter halos. Understanding how galaxies relate to +the underlying dark matter is also essential for optimally utilizing +the large-scale distribution of galaxies as a cosmological probe. +} +\activities{ +Preparatory work will be along two main +tracks. The first one will be support work to define and characterize +the upcoming galaxy samples from LSST to enable clustering +measurements from them. Several distinct sets of information need to +be made available or be calculable from pipeline data. Such +requirements include a detailed understanding of any selection effects +impacting the observed galaxies, the angular and radial completeness +of the samples, and the detailed geometry of the survey (typically +provided in terms of random catalogs that cover the full survey area). +\\ +The second track will be the development, testing, and optimization of +algorithms for measuring galaxy clustering using LSST data. One aspect +to address is how best to handle the large data sets involved +(e.g.~the ``gold'' galaxy sample will include about $4$~billion +galaxies over $20$,$000$~square degrees). Another is to develop the +methodology to optimally incorporate the LSST photo-$z$ estimates with +the angular data to obtain ``2.5-dimensions'' for pristine clustering +measurements. +\\ +These algorithms will be tested on realistic LSST mock catalogs, which +will also later serve as a tool for obtaining error estimates on the +measurements. +This endeavor overlaps with DESC-LSS working group efforts, and +requires cooperation of the DESC-PhotoZ working group and the Galaxies +Theory and Mock Catalogs working group.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Ensuring LSST galaxy pipelines include all the necessary +information for measurements of the correlation function and related +statistics to take place once data is available +\item Developing and refining techniques for measuring galaxy clustering of +large LSST galaxy samples. Together these will enable realizing the +full potential of LSST data for large-scale structure studies and +galaxy formation inferences thereof. +\end{enumerate} +} +\end{task} + + +\tasktitle{Disentangling Complicated Lines of Sight} +\begin{task} +\label{task:clss:los} +\motivation{ +Lines of sight through galaxy clusters and groups are the most +challenging lines of sight along which to measure reliable photometric +redshifts because crowding of galaxies complicates the basic process +of galaxy photometry, and the presence of significant correlated +large-scale structure (LSS) complicates interpretation of the P(z) of +the galaxies that has been computed by an algorithm that ignores the +presence of the LSS. Numerous science goals require the most robust +probabilistic statements possible as to the location of galaxies along +lines of sight through clusters, for example, identification of +background galaxies for weak-lensing, identification of faint cluster +members to study the evolution of the luminosity function in clusters, +identification of star-forming galaxies in clusters and their infall +regions to probe the physics of quenching of star formation. +} +\activities{ +The LSST will deliver the most information rich dataset ever in +relation to the masses and internal structures of clusters and their +infall regions. Moreover, the dataset can be enhanced significantly +via the addition of data at other wavelengths, including X-ray, +millimeter, and near-infrared. +\\ +A tool is therefore envisaged, that can take an input catalogue of +cluster centres that has been obtained from LSST or any other dataset +(e.g.~\emph{Planck}, \emph{eROSITA}). The tool will pull out the +basic L2 LSST photometry of objects within a cone centred on the +cluster centre, and compute the $p(z)$ of each galaxy based on a +cluster-specific algorithm. This algorithm will take account of the +following where they are available: brightness and extent of X-ray +emission, over-density of galaxies as a function of magnitude and +colour, any available spectroscopic redshifts, amplitude and extent of +any SZ decrement/increment. The algorithm will likely adopt a Bayesian +hierarchical modelling approach to forward model the problem. The +algorithm can be tested on existing datasets from surveys such as the +Local Cluster Substructure Survey (LoCuSS), XXL, HSC data processed by +DM Stack within LSST, and any others that would like to join in. +\\ +This work has links with the work on deblending/ICL, forward modelling +of cluster and groups, environmental measures, cluster detection, +complementary data, and also work in the DESC Clusters WG via $p(z)$ +of background galaxies.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A new cluster-specific photometric redshift algorithm that can be +applied to a list of cluster detections that is itself based on LSST +or external data. +\end{enumerate} +} +\end{task} + + + + +\tasktitle{Forward Modeling LSST Clusters and Groups} +\begin{task} +\label{task:clss:cluster_fm} +\motivation{ +Most of the interesting cluster and group physics from LSST and its +union with complementary surveys will be derived from studies that +explore the full range of halo mass relevant to groups and clusters: +$M_{200}\simeq10^{13}-10^{15}M_\odot$. This is a wider range than +cluster cosmologists (e.g. colleagues in DESC, with whom we +collaborate) aim to incorporate into their cosmological inference -- +they restrict attention to $M_{200}>10^{14}M_\odot$. +\\ +Another important difference between the cluster/group physics +explored here, and the dark energy-motivated DESC work, is that the +requirement on controlling systematic biases is roughly an order of +magnitude less stringent here than in DESC. Arguably, $\sim10\%$ +control of systematic biases in weak-lensing measurements of low +redshift clusters ($\gtrsim2\times10^{14}M_\odot$) has already been +achieved (Okabe et al. 2013; Applegate et al. 2014; Hoekstra et +al. 2015; Okabe \& Smith 2016). Therefore in this Science +Collaboration we have the challenge of maintaining that level of +control down to smaller masses and out to higher redshifts. +\\ +A growing number of studies are adopting an approach of forward +modelling the cluster population simultaneously with the cosmological +model to obtain constraints on scaling relations and cosmological +parameters. Here, the idea is to borrow this same approach, but adopt +a fixed cosmological model, broaden the mass range of systems +considered, and expand the forward modeling to include additional +relationships of interest. For example, simultaneously fitting +density profile models to the shear profiles, the mass-concentration +relation, and the star-formation rates of clusters and groups. +Overall, this will provide a robust Bayesian inference code with which +to constrain the physics of galaxies and hot gas in groups and +clusters, tied directly to the halo mass function via weak-lensing. +} +\activities{ +Key activities include: +% +\begin{itemize} +\item Select the elements of the cluster population to include in the model +\item Write the first version of the code, and test on simulated (toy model and n-body) data +\item Improve code and consider extending range of physics explored by adding more relations +\item Test code on existing datasets from pointed surveys (e.g. LoCuSS, others) and wide area surveys (e.g. LoCuSS, DES, others) +\item Combine this development work other work packages within Galaxies and DESC +\end{itemize} +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Bayesian inference code to simultaneously model cluster shear +profiles, scaling relations (including and beyond cosmological scaling +relations, across the full range of halo mass of groups and clusters, +to $\sim10\%$ control on systematics. +\end{enumerate} +} +\end{task} + + + +\end{tasklist} diff --git a/2016/task_lists/ddf/ddf.tex b/2016/task_lists/ddf/ddf.tex new file mode 100644 index 0000000..90ce8ab --- /dev/null +++ b/2016/task_lists/ddf/ddf.tex @@ -0,0 +1,73 @@ +\section{Deep Drilling Fields}\label{sec:tasks:ddf} + +The LSST Drilling-Fields (DDF) are areas that have a higher cadence and deeper observations than the Deep-Wide survey. Many of the details of the observing strategy have yet to be finalized. Four Deep-Drilling fields have been selected. Whether to include any others will be part of a complex trade involving other special projects that depart from the Deep-Wide survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy are all still under study, and the Project needs input from the science collaborations to inform these decisions. The tasks outlined in this section are intended to help optimize the LSST observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy-evolution science. + +\begin{tasklist}{DDF} +\tasktitle{Coordinating Ancillary Observations} +\begin{task} +\label{task:ddf:ancillary_obs} +\motivation{ +It is crucial that the LSST deep-drilling fields be supported by observations from other facilities. While the LSST data by themselves will be unique in having deep and accurate photometry, good image quality, and time-series sampling, the amount of information in six bands of relatively broad optical imaging is quite limited. Estimates of photometric redshifts and stellar-population parameters (e.g. mass and star-formation rate) are greatly improved with long-wavelength data. Combining these quantities with information on dust and gas from far-IR, mm and radio observations allows one to build and test models that track the flow of gas in and out of galaxies. Deep and dense spectroscopy is essential both providing precise redshifts, calibrating photometric redshifts, and measuring physical properties of galaxies. Properly supported by this additional data, the LSST DDFs will become the most valuable areas of the sky for galaxy-evolution science. The central regions of the four fields already selected are already in this category; the main challenge is filling out the much larger area subtended by the LSST field of view. +} +\activities{ +The major challenge in supporting the Deep Drilling Fields is the huge investment of telescope time. There is a need for coordination across facilities and collaborations to make the most efficient use of this time. Coordination is certainly happening somewhat haphazardly, but there has not to date been a dedicated effort to get all the potential stakeholders involved in developing a coherent plan. The LSST science collaborations can and should be taking the lead here. The SERVS program to observe the already-designated DDFs with Spitzer is a good example of where this has happened (Manduit et al. 2012), but there is much more to be done. Activities include: +\begin{itemize} +\item Workshops to discuss LSST DDF coordination +\item Proposals for major surveys or even new instrumentation to provide supporting data +\item Executing those supporting programs +\item Working to integrate the data from those programs with the LSST data +\item Working to enable DDF support through policies and strategic planning at major observatories +\end{itemize} +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Workshops on LSST DDF supporting observations +\item Annually updated roadmap of supporting observations (conceived, planned or executed) +\item Public Release of data from supporting observations +\item Level 3 software to enable use of LSST data with supporting data +\end{enumerate} +} +\end{task} + +\tasktitle{Observing Strategy “Cadence”} +\begin{task} +\label{task:ddf:cadence} +\motivation{ +The LSST DDF observing strategy will need to serve diverse needs. For galaxy-evolution science, the time series aspect of the observation is less important than the depth, image quality, and mix of filters. Optimizing the observing strategy (including timing) is influenced by non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data. For example, for many science goals, completing the observations of one DDF to the final 10-year depth in the first year could be very beneficial. But there is work to be done to justify that, select the field, and find synergies with other science areas (e.g. DESC, AGN, transients). +} +\activities{ +The LSST observing strategy is optimized using the Operations Simulator (OpsSim). The Project works with the community to develop both strawman observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpsSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Figures of Merit via MAF for use by OpSim +\item Proposed observing strategies for DDFs with rationale +\item Proposing and/or helping to assess selection of additional DDFs +\end{enumerate} +} +\end{task} + + +\tasktitle{Data Processing} +\begin{task} +\label{task:ddf:data_processing} +\motivation{ +Getting the most out of the DDFs may require data processing beyond that required for the Deep-Wide Survey. There are a variety of issues that ought to be considered in trying to optimize the science output. These include different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features , deblending overlapping objects, or estimating photometric redshifts. The fields are small enough that it is conceivable to process or reprocess them making use of data from supporting observations. It will clearly be advantageous to have one “official” LSST-released catalog, but defining such a catalog to support a very broad range of science is challenging. This does not preclude having additional special-purpose catalogs, but it is clearly beneficial to the advancement of extragalactic research to have a high-quality official catalog that has “buy in” from the LSST Science Collaborations. This requires time and effort both in the Project and in the Collaborations. +} +\activities{ +A major activity here is to identify the most important DDF-specific science drivers and identify any processing requirements that are distinct from the Deep-Wide survey. This ought to be coordinated with the Project and the other Science Collaborations to provide a coherent set of specifications and priorities. +\\ +Another major activity is to develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection) This may stress the inputs to the image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low-surface brightness features. Use of the supporting data sets in level 2 or level 3 processing requires careful thought. For example, source identification and photometry can be improved using pixel-level information for either Euclid or WFIRST. However, this will not be available for all the DDFs and is not in the baseline plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The collaborations need to work with the various projects to identify a clear path forward.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Science drivers and input to the development of level 2 processing of the DDFs. +\item Specifications for galaxy-evolution oriented level-3 DDF processing +\item Specifications for data-processing using supporting data from other facilities +\item Simulations tailored to the DDFs +\item Level 3 processing code +\end{enumerate} +} +\end{task} + +\end{tasklist} + + \ No newline at end of file diff --git a/task_lists/galaxies/galaxies.tex~ b/2016/task_lists/galaxies/galaxies.tex similarity index 95% rename from task_lists/galaxies/galaxies.tex~ rename to 2016/task_lists/galaxies/galaxies.tex index d4932b2..ecd101e 100644 --- a/task_lists/galaxies/galaxies.tex~ +++ b/2016/task_lists/galaxies/galaxies.tex @@ -7,7 +7,7 @@ \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} The LSST design, and to a certain extent the design of the data-management system, is optimized to carry out the core science mission. For measurements -of dark-energy, that generally means treating galaxies as "tracer particles" -- +of dark-energy, that generally means treating galaxies as ``tracer particles'' -- using statistical measures of ellipticity and position provide statistical constraints on large-scale structure and cosmic geometry. While many of the DESC tasks are directly relevant to studying galaxy evolution, they are @@ -21,11 +21,27 @@ \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} design or the algorithms used in the DM to construct catalogs. These are the most urgent. Also included are activities that can be reasonably independent of the LSST survey design and DM optimization, but which will ensure good support for -LSST galaxy studies. +LSST galaxy studies. -\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:precursor} +\begin{tasklist}{G} +\tasktitle{Example Task List} +\begin{task} +\label{task:label_for_this_task} +\motivation{Put Science Motivation Here} +\activities{Described Activities Here} +\deliverables{ + Deliverables over the next several years from the activities described above include the following: + \begin{enumerate} + \item a deliverable + \item another deliverable + \end{enumerate} +} +\end{task} +\end{tasklist} + +\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} -\begin{tasklist}{T} +\begin{tasklist}{G-TAS} \tasktitle{Techniques for finding low-surface-brightness features or galaxies} % Tidal streams % Intracluster diffuse light @@ -337,26 +353,18 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec:tasks:gal:precursor} -\begin{tasklist}{T} +\begin{tasklist}{G-PO} \tasktitle{Redshift surveys in the Deep Drilling fields} \begin{task} -\label{task:gal:XXX} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Spitzer observations of Deep Drilling fields} -\begin{task} -\label{task:gal:XXX} +\label{task:gal:redshift_surveys_dd_fields} \motivation{} \activities{} \deliverables{} \end{task} -\tasktitle{VLA observations of Deep Drilling fields} +\tasktitle{Ancillary Data in Deep Drilling fields} \begin{task} -\label{task:gal:XXX} +\label{task:gal:ancillary_data_dd_fields} \motivation{} \activities{} \deliverables{} @@ -365,7 +373,7 @@ \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec: \tasktitle{Photometric redshift training and calibration} % Emphasize differences in requirements relative to DE \begin{task} -\label{task:gal:XXX} +\label{task:gal:photz_calibration} \motivation{} \activities{} \deliverables{} @@ -373,7 +381,7 @@ \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec: \tasktitle{Joint use of spectroscopic and photometric redshifts} \begin{task} -\label{task:gal:XXX} +\label{task:gal:spec_plus_phot_redshifts} \motivation{} \activities{} \deliverables{} @@ -383,14 +391,14 @@ \subsection{Precursor Observations or Synergy with Other Facilities} \label{sec: \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulations} -\begin{tasklist}{T} +\begin{tasklist}{G-TS} \tasktitle{Image simulations of galaxies with complex morphologies} % Mergers % Tidal features % Stellar halos % Vary the galaxy-evolution model \begin{task} -\label{task:gal:XXX} +\label{task:gal:image_simulations} \motivation{} \activities{} \deliverables{} @@ -401,7 +409,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation % massive early galaxies % extremely supermassive black holdes \begin{task} -\label{task:gal:XXX} +\label{task:gal:rare_objects} \motivation{} \activities{} \deliverables{} @@ -410,7 +418,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \tasktitle{Cosmic Variance estimators} % Develop simple tools...encourage their use \begin{task} -\label{task:gal:XXX} +\label{task:gal:cv_estimators} \motivation{} \activities{} \deliverables{} @@ -418,7 +426,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \tasktitle{Nearby dwarfs: surface brightness fluctuations} \begin{task} -\label{task:gal:XXX} +\label{task:gal:dwarf_sb_fluctuations} \motivation{} \activities{} \deliverables{} @@ -426,7 +434,7 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \tasktitle{Testing group and void finders} \begin{task} -\label{task:gal:XXX} +\label{task:gal:group_finders} \motivation{} \activities{} \deliverables{} @@ -436,22 +444,10 @@ \subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulation \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} -\begin{tasklist}{T} -\tasktitle{Data structures to characterize survey biases and completeness} -\begin{task} -\label{task:gal:XXX} -\motivation{} -\activities{} -\deliverables{} -\end{task} - - -\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} - -\begin{tasklist}{T} +\begin{tasklist}{G-DDS} \tasktitle{Data structures to characterize survey biases and completeness} \begin{task} -\label{task:gal:XXX} +\label{task:gal:data_structures} \motivation{} \activities{} \deliverables{} @@ -463,7 +459,7 @@ \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} % nearby dwarf candidates % morphologically disturbed close pairs \begin{task} -\label{task:gal:XXX} +\label{task:gal:queries} \motivation{} \activities{} \deliverables{} @@ -471,7 +467,7 @@ \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} \tasktitle{Compact representations of likelihood functions} \begin{task} -\label{task:gal:XXX} +\label{task:gal:likelihoods} \motivation{} \activities{} \end{task} diff --git a/task_lists/galaxies/galaxies.tex.save b/2016/task_lists/galaxies/galaxies.tex.save similarity index 100% rename from task_lists/galaxies/galaxies.tex.save rename to 2016/task_lists/galaxies/galaxies.tex.save diff --git a/2016/task_lists/high_z/high_z.tex b/2016/task_lists/high_z/high_z.tex new file mode 100644 index 0000000..f2465c2 --- /dev/null +++ b/2016/task_lists/high_z/high_z.tex @@ -0,0 +1,48 @@ +\section{High-Redshift Galaxies}\label{sec:tasks:high_z} + +Summary + +\begin{tasklist}{HZ} +\tasktitle{Optimizing Galaxy Photometry for High-Redshift Sources} +\begin{task} +\label{task:high_z:photometry} +\motivation{ +The identification and study of high-redshift galaxies with LSST hinges on reliable, accurate and optimal measurements of the galaxy flux in all LSST passbands. +Galaxies at redshifts above 7 will only be detected in the LSST y-band and will be non-detections or ``drop-outs'' in the other LSST filters. Galaxies at redshifts above 8 will not be detected at all in the LSST filters but combining LSST with infrared surveys such as Euclid and WFIRST would enable this population to be identified. It is particularly important to have robust flux measurements and robust flux limits for the undetected high-redshift galaxies in the blue LSST filters so this information can be utilized in the high-redshift galaxy selection. Since Euclid and WFIRST are space-based missions with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogenous flux measurements for sources across the different surveys. +\\ +It is not clear if the current Level 2 data products package will meet all the requirements for high-redshift science with LSST and this therefore needs to be investigated before the start of the survey. +} +\activities{ +Firstly, we need to get a clearer picture of what constitutes the LSST Level 2 data products so we can assess whether these will be adequate for the high-redshift science. Issues that we need to understand are: 1) Will photometric catalogues be produced using the reddest LSST (e.g. y-band) images as the detection image? This is critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. 2) When computing model galaxy fluxes, will negative fluxes be stored? Negative fluxes for undetected galaxies together with their corresponding errorbars, provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. + \\ +The second major activity will be determining the best approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection. We will need to determine the optimal measure of an optical-IR colour for sources from these two datasets. There is the additional complication that sources that are resolved in the Euclid/WFIRST data could be blended in LSST and will therefore need to be accurately de-blended, perhaps using the high-resolution IR data as a prior, before a reliable flux and colour measurement can be made. Tests can be run using existing datasets e.g. from the Dark Energy Survey (DES) and HST.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Determine what constitutes LSST Level 2 data products and document what additional data products will be required for high-redshift science. +\item Develop tools to produce optimal combined photometry from ground and space-based surveys and test these on existing datasets. +\end{enumerate} +} +\end{task} + +\tasktitle{High-Redshift Galaxies and Interlopers in LSST Simulations} +\begin{task} +\label{task:high_z:interlopers} +\motivation{ + Before the start of LSST operations, it is important that we are able to test our selection methods for high-redshift galaxies on high-fidelity simulations. Given the wide-field coverage of LSST, it will be uniquely positioned to uncover large samples of the most luminous and massive high-redshift galaxies at the Epoch of Reionisation and beyond. The most significant obstacle to selecting clean samples of such sources from the photometric data, is the presence of significant populations of interlopers e.g. cool stars in our own Milky Way and low-redshift, dusty and/or red galaxies, both of which can mimic the colours of high-redshift sources. Using the LSST simulations, we want to be able to devise the most effective way of separating these different populations, and utilising both photometric and morphological information for the sources. Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA infrared surveys, we expect at least some of the most luminous z > 6 galaxies to be spatially resolved in the LSST images. +} +\activities{ +Liaise with the LSST simulations working group to ensure that high-redshift galaxies have been incorporated into the simulations with a representative set of physical properties (e.g. star formation histories, UV-slopes, emission line equivalent widths, dust extinction, metallicity). It is also important that the high-redshift galaxies have the correct number density and size distribution in the simulations. The latter will allow us to investigate how effectively we can use morphology to separate these galaxies from interlopers. +\\ +In addition to the high-redshift galaxies, it is equally important from a high-redshift science perspective, that interlopers have been incorporated into the simulations with the correct number densities and colours. Interlopers of particular relevance to the high-redshift searches will be cool stars in our own Milky Way (e.g. L and T-dwarf stars) as well as populations of very red, massive and/or dusty galaxies at lower redshifts of $z\sim2$. +\\ +Finally, we may want to consider whether to include colour information in the infrared filters (e.g. those from Euclid/WFIRST) in the simulations as this information will undoubtedly help with the high-redshift selection. + } +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Incorporate high-z galaxies into LSST simulations with a realistic and representative set of properties. +\item Incorporate brown dwarfs into LSST simulations +\item Extend simulations to other datasets beyond LSST (e.g. Euclid/WFIRST filters). +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/2016/task_lists/lsb/lsb.tex b/2016/task_lists/lsb/lsb.tex new file mode 100644 index 0000000..3160598 --- /dev/null +++ b/2016/task_lists/lsb/lsb.tex @@ -0,0 +1,167 @@ +\section{Low-Surface Brightness Science}\label{sec:tasks:lsb} + +Summary + +\begin{tasklist}{LSB} +\tasktitle{Techniques for Finding Low-Surface Brightness Tidal Features} +\begin{task} +\label{task:lsb:tidal_features} +\motivation{ +A key advantage of LSST over previous large-area surveys (e.g. the SDSS) is its ability to detect low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and other features associated with past and ongoing interactions, intra-cluster and intra-group light, and nearby, extended low- surface-brightness galaxies. +\\ +Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected by criteria that are difficult to quantify (e.g. visual inspection that can somewhat subjective) or reproduce in theoretical models. Automated (algorithmic) measurements of the LSB features themselves can be challenging and many past studies have relied on visual inspection for the identification and characterization of features (which may not easily applied on the LSST scale). For LSST it is highly desirable that we automate the detection and characterization of LSB features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. +} +\activities{ +Several activities are of crucial importance: +\begin{enumerate} +\item Simulating realistic LSST images and LSB features (using, e.g., high-resolution hydro simulations) +\item Identifying precursor datasets that can be used as proxies for developing LSB tools for use on LSST data +\item Using the simulations to develop algorithms for detection and measurement of LSB features +\item Applying these algorithms to the precursor datasets to test their suitability +\item Ensuring that LSST level-2 processing strategies and observing strategies are aligned with the needs of LSB science +\item Developing a strategy for finding and measuring LSB features through a combination of level 2 measurements, database queries, and level 3 processing +\end{enumerate} +It is important to produce realistic LSST images from e.g. the current generation of hydro-dynamical cosmological simulations (which faithfully incorporate both the evolution of large-scale structure and the interplay between baryons and dark matter during interactions). Scattering from bright stars (which may or may not be in the actual field of view of the telescope) is likely to be the primary source of contamination when searching for extended LSB features. Ideally, the LSST scattered-light model, tuned by repeated observations, will be sufficiently good that these contaminants can be removed or at least flagged at level 2. Defining the metrics for “sufficiently good,” based on analysis of simulated images, is an important activity that needs early work to help inform LSST development. +\\ +Including Galactic cirrus in the simulations will be important when developing strategies for detecting for large-scale LSB features. Including a cirrus model as part of the LSST background estimation is worth considering, but it is unclear yet whether the science benefit can justify the extra effort. +\\ +Because the LSST source extraction is primarily optimized for finding faint, barely-resolved galaxies, it will be challenging to optimize simultaneously for finding large LSB structures and cataloging them as one entity in the database. For very large structures, analysis of the LSST “sky background” map, might be the most productive approach. We need to work with the LSST project to make sure the background map is stored in a useful form, and that background measurements from repeated observations can be combined to separate the fluctuating foreground and scattered light from the astrophysically interesting signal from extended LSB structures. Then, we need strategies for measuring these background maps, characterizing structures, and developing value-added catalogs to supplement the level 2 database. +\\ +For smaller structures, it is likely that the database will contain pieces of the structure, either as portions of a hierarchical family of deblended objects, or catalogued as separate objects. Therefore, we need to develop strategies for querying the database to identify galaxies which are likely to have such structures. E.g. in galaxies that have LSB tidal features around them, the main body of the galaxy is likely to be disturbed and therefore asymmetric. Measures of asymmetry will therefore be useful for flagging such systems. We then need to have a strategy for either extracting the appropriate data for customized processing, or develop ways to put back together the separate entries in the database. A possible value-added catalog, for example, from the galaxies collaboration might be an extra flag in the database to indicate that a galaxy is likely to have LSB tidal features and an extra set of fields for the database to indicate which separate objects are probably part of the same physical entity. +\\ +This would be relatively sparsely populated in the initial stages of LSST. Estimates from the Stripe 82, indicate that 15\% of galaxies carry LSB tidal features (LSST will reach Stripe 82 in a single shot) but by the end of the survey will become a key resource for a wide variety of investigations. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Realistic mock LSST images from hydro cosmological simulations (including re-simulations of individual objects were necessary) with spatial resolutions of tens of parsecs. +\item Algorithms for finding galaxies with LSB features and for measuring the properties of these features. +\item Input to the Project on scattered-light mitigation and modeling strategies from the simulations. +\item Input to the Project on photometric and morphological parameters (e.g. asymmetry, residual flux fractions etc) to measure and store in the level 2 database. +\item Query strategies and sample queries for finding LSB structures. +\item A baseline concept for a value-added database of LSB structures. +\end{enumerate} +} +\end{task} + + + + +\tasktitle{Low-Surface Brightness Galaxies} +\begin{task} +\label{task:lsb:galaxies} +\motivation{ +Our objective is to investigate the most relevant and challenging aspects of the Low Surface Brightness (LSB) Universe. This has a direct baring on the range of galaxies initially formed, the properties that they have during and after their assembly, their connection to the cosmic web and ultimately to the nature of dark matter, which plays a large part in all of these processes. +\\ +By LSB we mean objects that have surface brightnesses much less than that of the background night sky and that which is typical of the Milky Way galaxy we live within. Many authors have previously shown how difficult it is to detect objects of LSB and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to the spiral galaxy that we live within. Thus the Universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? +\\ +The problem is that astronomical observations always include a signal from a background, a level we need to detect our sources above. For ground based observations the background arises locally from the atmosphere and our proximity to the Sun, scattered light from the solar system, diffuse star light from the Galaxy and a small contribution from other galaxies in the Universe. For an astronomical object to be detected it must stand out above the noise level in this background. If this noise was purely due to photon statistics then very simply all we would need to do is collect as many photons as possible and the signal would gradually appear out of the noise. However, we currently know that it is nowhere near this simple because of scattered light across the field of view (FOV), instrumental calibration uncertainties and real fluctuations in the cosmic background. For these reasons there has previously been little progress in making a definitive study of the extent and brightness limits of the LSB Universe. +\\ +Additionally, this LSB universe include a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model. The galaxy mass function at masses less than Mh ~ 1010 Msun systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via HI surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies are still quite easy to detect in LSST images. +\\ +The challenge is to identify them as nearby dwarfs and estimate their distances and hence luminosities. The dwarfs in question are low-surface-brightness galaxies, so many of the source-detection issues are common to the more general problem of detecting LSB features. LSST data allow us to focus on different issues. For certain distances and luminosities, typical dwarf spheroidal galaxies will be distinct from the vast majority of background galaxies in the radius vs apparent magnitude plane. However, there will often be overlapping background galaxies, so it is important that the de-blending and cataloging steps try to remove the overlaps and allow one to query for galaxies in the right portion of the color-size-brightness manifold. Once candidates are identified, it should be possible to tease out approximate distances for many dwarf galaxies via surface-brightness fluctuations (SBF). Once again this requires careful treatment of the background galaxies, but this step is now Level 3 processing, so can be customized much more than the detection step. More ambitiously, it is conceivable that machine-learning techniques could be trained to identify semi-resolved nearby dwarf galaxies given a suitable training set from LSST-precursor observations. +\\ +On the other extreme of LSB objects, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disc of stars and an impressive system of spiral arms only revealed in 2015. The central bulge of the galaxy is prominent, but the stellar disc and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB discs? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting SB of the LSST combined with the large FOV make this instrument unique to probe the existence of large LSBs, similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant discs like Malin 1 only make this problem worse. This is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. In addition we will be exploring the very outer regions of galaxies and so will be able to explore the connection between the decreasing surface density of baryons and the increasing significance of the dark matter component of galaxies. +\\ +One reason why this subject has made little progress over the last few years is because of the limited amount of deep large area data available. Most previous deep (CCD) surveys have been specifically designed to investigate the distant Universe and so, like the Hubble Deep Field, have concentrated on long exposures over small areas of sky. The extensive sky survey that LSST will carry out will become the state-of-the-art for years to come and offers a new and enormous LSB discovery potential. As a pointer to these exciting discoveries there have recently been relatively small-scale observations that indicate that a hidden LSB galaxy population does exit. An example is the population of LSB galaxies recently detected in the Coma and Fornax clusters, galaxies not only with astonishing LSB (>27 B mag arcsec-2), but also with some of them exhibiting effective radii similar to that of the Milky Way. This is despite both Coma and Fornax being two of the previously most studies regions of the nearby Universe. +\\ +To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5\mathrm{mag}~\mathrm{arcsec}^2$ and that from a space telescope typically an order of magnitude fainter $\approx25.0\mathrm{mag}~\mathrm{arcsec}^2$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0\mathrm{mag}~\mathrm{arcsec}^2$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28\mathrm{mag}~\mathrm{arcsec}^2$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32\mathrm{mag}~\mathrm{arcsec}^2$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into high surface brightness stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26\mathrm{mag}~\mathrm{arcsec}^2$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the Universe using LSST to at least a surface brightness level of $30\mathrm{mag}~\mathrm{arcsec}^2$. +} +\activities{ +\begin{enumerate} +\item Production of simulated data that can be passed through the LSST data reduction pipeline. +\item Analysis of simulated images to ensure that LSB features can be accurately preserved and measured. +\item The development of new object detection software specifically designed for the detection of LSB features, in particular: +\begin{itemize} +\item Objects with large size. +\item Objects near or melted with large size, bright galaxies. +\item Objects with patterns similar to galaxy streams. +\item Highly irregular and distorted objects. +\end{itemize} +\item Identification of precursor data sets that can be used to test our methods. We can use data generated using numerical simulations to look at the types of galaxies produced that have sufficient angular momentum to become LSB discs. These discs can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. We will develop new methods of detecting LSB objects. These will include pixel clustering methods and the labeling of pixels with certain properties i.e. surface brightness level, SED shape, proximity to other similar pixels etc. We will trial our methods on other currently available data sets (KIDS, CFHT etc). +\item Simulate realistic LSST images of nearby dwarf galaxies. +\item Identify nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools. +\item Develop and test the database search queries for finding candidates of several shapes and sizes. +\item Develop and test a measurement of semi-resolved ``texture'' as a candidate level 2 measurement. +\end{enumerate} +The use of ``texture'' as a means of identifying candidate nearby dwarf galaxies is something that needs near-term attention if it is to make it into level 2 processing early in the survey. This can be developed and tested on the semi- resolved-galaxy simulations, but it is also essential to test it on precursor data sets from DES, CFHTLS or HSC. +\\ +As a natural consequence of the effort that the members of this team are going to invest on the discovery and catalogue, we can foresee a long-term group effort for continuing the research once deliverables are available. A natural strategy, will be to perform several follow ups with large aperture telescopes available in Chile, with powerful instruments capable of obtaining optical, near-IR spectra, sub-mm, mm and IFU data for LSB objects. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Realistic mock LSST images. +\item An assessment of the influence of the PSF, scattered light and other instrument signals that may affect our ability to detect LSB features +\item An assessment of the effect of proposed pipeline on the detection and measurement of LSB features. +\item A baseline concept for the construction of a database of LSB features detected using LSST data. +\begin{itemize} +\item Realistic inputs of dwarf galaxies for the LSST image simulations. +\item Realistic postage-stamp simulations of semi-resolved dwarf galaxies. +\item Training set of nearby dwarfs from LSST precursor data. +\item Figures of Merit for detection and selection algorithms +\item Run LSST pipeline on both simulations and precursor data and assess performance. +\end{itemize} +\item Optimized algorithms measuring surface brightness fluctuation distances. +\item A new LSB object detection package, friendly adapted for the user. +\end{enumerate} +} +\end{task} + + + +\tasktitle{Probing the Faint Outskirts of Galaxies with LSST} +\begin{task} +\label{task:lsb:faint_outskirts} +\motivation{ +The outskirts of nearby galaxies, loosely defined as the regions below $25-26\mathrm{mag}~\mathrm{arcsec}^2$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). +\\ +The main science driver here is understanding the assembly, formation, and evolution of galaxies. This can be studied through imaging and subsequent parametrization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar haloes. From numerical modelling we know that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo, are tightly related to the accretion and merging history. This is illustrated by the imaging of the stars in the outskirts of M31 and other local group galaxies, which show detailed structure. +\\ +Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to local group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams may be less affected by overall PSF, but more by foreground cirrus. +} +\activities{ +Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modelling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyse the outskirts. Dithering and rotation of individual imaging will need to be modelled before stacking multiple imaging. +\\ +Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} + + + +\tasktitle{Low-Surface Brightness Intracluster Light} +\begin{task} +\label{task:lsb:icl} +\motivation{ +The Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. It is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. +\\ +Some outstanding scientific questions, which LSST could solve: +\begin{itemize} +\item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? +\item Does it contain significant substructure? +\item What is its surface brightness profile and does it have a colour dependence, which would indicate age/metallicity gradients? +\item Where does the ICL begin and the large diffuse cD halo of the Brightest Cluster Galaxy (BCG) end and do they have the same origin? +\end{itemize} +} +\activities{ +The preparation work for the ICL component of the LSB case involves investigating LSST specific issues for large LSB features and the known properties of the ICL itself. +\\ +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce low surface brightness signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for the LSB team to liaise with LSST strategy, telescope, instrument and data reduction teams. +\\ +The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Investigate any telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. +\item Investigate observation specific issues that affect the measurement of large LSB features: dither pattern strategy. +\item Investigate image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. +\item Feasibility: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? +\item Investigate stacking clusters to obtain faint ICL - this is difficult as will require very strong masking of even the faintest observable cluster members. +\end{enumerate} +} +\end{task} +\end{tasklist} \ No newline at end of file diff --git a/task_lists/old/black_holes/black_holes.tex b/2016/task_lists/old/black_holes/black_holes.tex similarity index 100% rename from task_lists/old/black_holes/black_holes.tex rename to 2016/task_lists/old/black_holes/black_holes.tex diff --git a/task_lists/old/informatics/informatics.tex b/2016/task_lists/old/informatics/informatics.tex similarity index 100% rename from task_lists/old/informatics/informatics.tex rename to 2016/task_lists/old/informatics/informatics.tex diff --git a/task_lists/old/lss/lss.tex b/2016/task_lists/old/lss/lss.tex similarity index 100% rename from task_lists/old/lss/lss.tex rename to 2016/task_lists/old/lss/lss.tex diff --git a/task_lists/old/strong_lensing/strong_lensing.tex b/2016/task_lists/old/strong_lensing/strong_lensing.tex similarity index 100% rename from task_lists/old/strong_lensing/strong_lensing.tex rename to 2016/task_lists/old/strong_lensing/strong_lensing.tex diff --git a/task_lists/old/weak_lensing/weak_lensing.tex b/2016/task_lists/old/weak_lensing/weak_lensing.tex similarity index 100% rename from task_lists/old/weak_lensing/weak_lensing.tex rename to 2016/task_lists/old/weak_lensing/weak_lensing.tex diff --git a/2016/task_lists/photo_z/photo_z.tex b/2016/task_lists/photo_z/photo_z.tex new file mode 100644 index 0000000..c5b2a01 --- /dev/null +++ b/2016/task_lists/photo_z/photo_z.tex @@ -0,0 +1,142 @@ +\section{Photometric Redshifts}\label{sec:tasks:photo_z} + +Summary + + +\begin{tasklist}{PZ} +\tasktitle{Impact of Filter Variations on Galaxy photo-z Precision} +\begin{task} +\label{task:photo_z:filter_variations} +\motivation{ +For accurate photometric redshifts, well calibrated photometry is essential. Variations in the telescope system, particularly the broad-band ugrizy filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of local environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane. Such corrections will be SED dependent, and may leave residuals, particularly for specific populations with unusual SEDs. Tests of the amplitude of these residuals, and the impact on photo-z as a whole, and for particular object classes, is an important consideration. Beyond this, if the variations turn out to be very well calibrated, they could potentially be used to further improve, rather than degrade, photo-z performance. The variations in filter response can offer up additional a small amount of extra information on the object SED, given the slight variation in effective filter wavelength, particularly for objects with strong narrow features, i.e. emission lines. Tests of how much information is gained can inform whether or not the extra computational effort used in computing photo-z’s from many slightly different filters as opposed to measurements corrected to the six fiducial filters of the survey. +} +\activities{ +XXX} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} + +\tasktitle{Photometric Reshifts in the LSST Deep Drilling Fields} +\begin{task} +\label{task:photo_z:ddf} +\motivation{ +The LSST Deep Drilling Fields present different challenges than the main survey, including more confusion between sources, and the ability to use the best subsets of the images due to their being many repeat observations. These properties allow investigations of galaxies of brightness close to the noise in the main survey at higher signal to noise. +} +\activities{ +Assessing robustness of photo-zs with spectroscopic surveys will be difficult at the faintest fluxes, relationship to clustering redshifts important. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} + +\tasktitle{Multivariate Physical Properties of Galaxies from Photometric Redshifts} +\begin{task} +\label{task:photo_z:physical_properties} +\motivation{ +The knowledge of the derived physical properties underlies much of the work involving galaxies and their evolution. Derived physical properties include, among others: star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity. When it comes to scientific analysis, in recent years the derived physical properties have largely supplanted fluxes and luminosities in the UV, optical and near-IR bands. This is because derived properties require no redshift (K) corrections, are dust-corrected, and are therefore easier to relate across surveys and studies and to compare with the models. Stellar mass has emerged as a parameter of choice for selecting galaxy types and making apple-to-apple comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a rough estimate of galaxy’s SF history. Dust attenuation and stellar metallicity are also indicative of various processes important for understanding galaxy evolution. +} +\activities{ +Deriving physical properties, usually accomplished by spectral energy distribution (SED) fitting, is an involved process and the results depend on the number of factors, including: underlying population models, assumed dust attenuation law, assumed star formation histories, choice of model priors, choice of IMF, emission line corrections, choice of input fluxes, type of flux measurements, treatment of flux errors, SED fitting methodology, interpretation of the resulting probability distribution functions (PDF) (e.g., Salim et al. 2016). In the case of LSST, the additional challenge is that the redshifts are for the most part photometric, and carry a PDF (a measure of uncertainty) of their own. In principle, the redshifts could be determined as part of the SED fitting (and vice versa, physical parameters can be obtained from some photo-z codes), but it is not clear whether this joint approach is the best. Alternatives are to use empirical training sets to obtain the photo-z (some “best” estimate or a PDF) and then feed it into the SED fitting code. +\\ +Activities will consist of testing whether the determination of physical parameters and photo-z should be performed jointly or not, based on training sets with spectroscopic redshifts, at a range of redshifts. Furthermore, testing should be performed on mock galaxies to understand which choices of methods and assumptions (specifically related to LSST data) produces the best results in the sense of retrieving the “known” properties. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-z and properties, together with the software to be used. +\item With LSST data: the production of catalogs of properties to be used by the collaboration. +\end{enumerate} +} +\end{task} + +\tasktitle{Identifying Spectroscopic Redshift Training Sets for LSST} +\begin{task} +\label{task:photo_z:specz_training_sets} +\motivation{ +Require deep spectroscopic redshift data in order to help train algorithms, improve algorithms with clustering etc, and also provide a basis for determining accuracy of photo-z algorithms. +} +\activities{Collate existing spectroscopic redshift data over both DDF and wider fields, along with selection biases for each spectroscopic data set. Assess robustness of existing data, determine colour space where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item AAA +\item BBB +\end{enumerate} +} +\end{task} + +\tasktitle{Develop Techniques to Identify Specific Sub-Populations of Galaxies} +\begin{task} +\label{task:photo_z:subpops} +\motivation{ Studying properties related with the star formation activity of galaxies, such as color and specific star formation rate (sSFR), as a function of mass, environment and redshift is relevant for understanding the different physical processes in galaxy formation and evolution. The aim is to develop techniques in order to identify specific sub-populations with the aforementioned properties (e.g. blue/star-forming and red/quenched galaxies) based on photometric data. Another interesting sub-population is galaxies which contain an active nucleus. The identification of AGN candidates will also be explored. +\\ +This task is potentially cross-cutting with the theory/mock catalogs, machine learning, clusters, lss, AGN, and DESC working groups and collaborations. +} +\activities{ +We can use simulations and mock catalogs to obtain prior estimates of the calibrations used to identify specific galaxy sub-populations. These calibrations will depend on mass and redshift (z). One technique to explore is fitting two Gaussians to the corresponding color and sSFR distributions in different mass and redshift bins to identify populations of red and blue galaxies. It is important that the mass definition assumed in the mocks be comparable to that estimated for observations. Note that the stellar mass would be used as the alpha parameter in the joint probability distribution functions, p(z,alpha). +\\ +Furthermore, we will make efforts to identify AGNs to obtain a sample of AGN candidates and, also, isolate them from “normal” galaxy samples without AGNs. The information of color and star formation described above can be used for this aim. +\\ +The techniques can be probed as a function of environment, which can be defined using different approaches at both small and large scales (e.g. number of neighbor galaxies, location in large-scale structures such as filaments, voids, knots, or Voronoi tessellation techniques). This would enable the characterization of galaxy sub-populations according to the environment. The resulting galaxy sub-populations can be used as training sets to be implemented on machine learning models. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Obtaining mass from mock catalogs compatible with the mass used in p(z,mass). +\item Developing techniques that depend on this mass and redshift using mock catalogs for selecting samples with red/blue colors. +\item Developing multiple techniques that depend on this mass and redshift using mock catalogs for selecting star-forming/quenched samples. +\item Developing techniques that may depend on star formation, color and redshift for selecting AGN samples. +\item Defining several environment estimators in simulated datasets. +\item Probing techniques in b), c) and d) as a function of the environments defined in e). +\item Obtaining training sets to be implemented on machine learning models. +\end{enumerate} +} +\end{task} + +\tasktitle{Simulations with Realistic Galaxy Colors and Physical Properties} +\begin{task} +\label{task:photo_z:color_simulations} +\motivation{ +As representative samples of spectroscopic redshifts will be very difficult to compile for LSST, simulations will play a key role in calibrating estimates of physical properties such as galaxy stellar mass, star formation rate, and other properties. This is particularly problematic for photometric surveys, where photometric redshift and physical property estimates must be calculated jointly. In addition, we must include prominent effects that will influence the expected photometric performance, for example the presence of an active galactic nucleus can significantly impact the color of a galaxy and the inferred values for the physical parameters, so models of AGN components of varying strength must be included in the simulations. Many current generation simulations cannot or do not simultaneously match observed color distributions and physical property characteristics for the galaxy population at high redshift. As photo-z algorithms are highly dependent on accurate photometry, realistic color distributions are required to test the bivariate redshift-physical property estimates. Working with the galaxy simulations and high redshift galaxy working groups to develop new simulations with more accurate high redshift colors is a priority. These photo-z needs are not unique, and the improved simulations will benefit the wider Collaboration as a whole. +} +\activities{ +The main activity for this task is to bring together the knowledge gained from observational studies of high redshift galaxies to act as input for improved simulation metrics. This will require expertise from the photo-z group, the high redshift galaxies group, the AGN group, and the simulations group. In order to test whether mock high-z populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions. Assuming that the simulations are valid beyond the test intervals, we can then test bivariate photo-z/physical process determinations to develop improved algorithms. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Determination of a list of which physical parameters are important for galaxy science. +\item Compiling observable datasets that can be used as comparators for simulated datasets. +\item Developing a set of metrics to compare simulations to the observational data. +\item Use the metrics in deliverable B to create updated simulations with more realistic parameter distributions. +\item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc…). +\end{enumerate} +} +\end{task} + +\tasktitle{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} +\begin{task} +\label{task:photo_z:size_and_sb_priors} +\motivation{ +Photometric redshift algorithms traditionally use galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information in the form of the galaxy’s size/shape/surface brightness (SB) profile adds additional information that can aid in constraining both the redshift and type of the galaxy, breaking potential degeneracies that using colors alone would miss. Adding type information beyond just the rest frame SED may help to constrain bivariate galaxy properties that correlate with morphological type as well. If sufficient training samples are available, a Bayesian prior on colors and SB profile, p(z|C,SB), can be constructed that should lead to improved photometric redshifts. +} +\activities{ +The primary activity in this task is to develop an algorithm to compute a parameterized SB profile fit (e.g. Sersic index, though other measures may be appropriate) for a large number of galaxies. The algorithm must be fast enough to compute SB profiles for large numbers of galaxies. Simulated datasets may be necessary to calibrate this code in the limits of galaxy sizes approaching the size of the PSF, and in the limit of low signal-to-noise ratios. With SB measurements in hand, the computation of a Bayesian prior on redshift given galaxy photometry and SB. This can be done with either simulated datasets, or real observations with spectroscopic redshifts. Tests will then show the performance of such a prior relative to using galaxy photometry alone. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A fast, scalable algorithm for measuring the surface brightness profile of galaxies. +\item A cross matched catalog with objects at known redshifts and measured surface brightness profiles. +\item A Bayesian prior $p(z|C,SB)$ that can be used to improve photo-z measurements. +\end{enumerate} +} +\end{task} +\end{tasklist} + + + diff --git a/2016/task_lists/task_lists.tex b/2016/task_lists/task_lists.tex new file mode 100644 index 0000000..fbbea34 --- /dev/null +++ b/2016/task_lists/task_lists.tex @@ -0,0 +1,30 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% First draft by + +\chapter[Task Lists by Science Area]{Task Lists by Science Area} +\label{ch:task_lists} + +%\input{task_lists/chapter_intro.tex} +%\input{task_lists/black_holes/black_holes.tex} +%\input{task_lists/informatics/informatics.tex} +%\input{task_lists/lss/lss.tex} +%\input{task_lists/strong_lensing/strong_lensing.tex} +%\input{task_lists/weak_lensing/weak_lensing.tex} + +\input{task_lists/agn/agn.tex} +\newpage +\input{task_lists/clss/clss.tex} +\newpage +\input{task_lists/ddf/ddf.tex} +\newpage +\input{task_lists/galaxies/galaxies.tex} +\newpage +\input{task_lists/high_z/high_z.tex} +\newpage +\input{task_lists/lsb/lsb.tex} +\newpage +\input{task_lists/photo_z/photo_z.tex} +\newpage +\input{task_lists/tmc/tmc.tex} diff --git a/task_lists/template.tex b/2016/task_lists/template.tex similarity index 100% rename from task_lists/template.tex rename to 2016/task_lists/template.tex diff --git a/2016/task_lists/tmc/tmc.tex b/2016/task_lists/tmc/tmc.tex new file mode 100644 index 0000000..dd5850c --- /dev/null +++ b/2016/task_lists/tmc/tmc.tex @@ -0,0 +1,75 @@ +\section{Theory and Mock Catalogs}\label{sec:tasks:tmc} + +Summary + +\begin{tasklist}{TMC} +\tasktitle{Image Simulations of Galaxies with Complex Morphologies} +\begin{task} +\label{task:tmc:complex_morphology} +\motivation{ +LSST images will contain significant information about the dynamical state of galaxies. In principle, this can be exploited to learn about their formation and evolutionary histories. Examples of such features include spiral arms, tidal tails, double nuclei, clumps, warps, and streams. A wide variety of analysis and modeling techniques can be applied to determine the past, present, or future states of observed galaxies with complex morphologies, and therefore improve our understanding of galaxy assembly. +} +\activities{ +Activities include creating synthetic LSST observations containing a wide variety of galaxies with complex morphologies, for the purpose of testing analysis algorithms such as de-blending, photometry, and morphological characterization. Supporting activities include creating databases of galaxy images from models (such as cosmological simulations) or existing optical data, analyzing them using LSST software or prototype algorithms, and distributing the findings of these studies. These analyses can be performed on small subsets of the sky and do not necessarily have to include very-large-area image simulations or match known constraints on source density. Results will include predicting the incidence of measured morphological features, optimizing level-3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Creating synthetic LSST images of galaxies with complex morphology from simulations. +\item Creating synthetic LSST images based on prior observations in similar filters. +\item Making these LSST-specific complex galaxy data products widely available. +\item Publicizing results of algorithm tests based on these simulations. +\item Assessing level-3 measurements to propose and/or apply to maximize the return of LSST catalogs for complex galaxy morphology science. +\end{enumerate} +} +\end{task} + + +\tasktitle{New Theoretical Models for the Galaxy Distribution} +\begin{task} +\label{task:tmc:galaxy_distribution} +\motivation{ +Our aim is to bring together key areas of expertise to meet the challenge of building synthetic, computer generated mock surveys which will be used in the preparation for Galaxy science with LSST. Surveys like LSST will collect more data than is contained in the current largest survey, the SDSS, every night for ten years. The analysis of such data demands a complete overhaul of traditional techniques and will require the incorporation of ideas from different disciplines. The mock catalogs we will produce offer the best means to test and constrain theoretical models using observational data. +Computer mock catalogs play a well established role in modern galaxy surveys. For the first time, the scientific potential of the new surveys will be limited by systematic errors rather than sampling errors driven by the volume mapped. The signals from viable, competing cosmological models are already extremely close. Distinguishing between the models requires that we build the best possible theoretical predictions to understand the measurements and how they should be analyzed. We also need to understand the errors on the measurements. +} +\activities{ +Develop a new state-of-the-art in physical models of the galaxy distribution combining models of the physics of galaxy formation with high resolution N-body simulations which track the hierarchical growth of structure in the matter distribution. The key task is to take the results of calculations in moderate volume cosmological N-body simulations and to develop schemes to embed this information into very large volume simulations. The large volume simulations will be bigger than the target survey, allowing a robust assessment of the systematic errors on large-scale structure measurements.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Physically motivated mock galaxy catalogues on volumes larger than will be sampled by LSST, with a consistently evolving population of galaxies. +\item Base catalogues of dark matter haloes and their merger trees that will be available for other theoretical models of populating these with galaxies (halo and subhalo occupation/abundance matching techniques). +\item Small volume simulations for further tests. +\end{enumerate} +} +\end{task} + +\tasktitle{Design of New Empirical Models for the Galaxy Distribution.} +\begin{task} +\label{task:section:title} +\motivation{ +We will explore the galaxy-halo connection, using the simulations of the galaxy formation process as encapsulated in physically motivated models to build better empirical models. Empirical models can be adjusted to reproduce observational results as closely as possible, whereas physical models are computationally expensive, so only a small number of examples can be run, and the results cannot be tuned in the same way. Empirical models also have the advantage of being extremely fast, allowing large parameter spaces to be explored. +} +\activities{ +There are two stages here: one is to test current models to see how well they can reproduce the predictions of physical models and the second is to use the physical models to devise new parametrizations to describe galaxy selections for which there is little or no current observational data. This is particularly relevant for upcoming surveys which will probe regimes that remain largely unmapped.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item The evolution of the clustering predicted by the physical models may allow us to model how parameters should change in the empirical models, thereby reducing the number of parameters which we need to fit and to populate catalogs on the observer’s past lightcone. +\end{enumerate} +} +\end{task} + + +\tasktitle{Estimating Uncertainties for Large-Scale Structure Statistics} +\begin{task} +\label{task:tmc:uncertainties} +\motivation{ +The ability to interpret the relation between galaxies and the matter density field will depend critically on how well we understand the errors on large-scale structure measurements. The accurate estimation of the covariance on a large-scale structure measurement such as the correlation function would require tens of thousands of simulations. +} +\activities{ +Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, based for example on perturbation theory. +Coordinate with WGs of the Dark Energy Science Collaboration as these covariance matrices can also be applied to Cosmological parameter constraints.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Physically motivated estimates of covariance matrices for galaxy occupation (and other) parameter searches. +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/whitepaper.sty b/2016/whitepaper.sty similarity index 100% rename from whitepaper.sty rename to 2016/whitepaper.sty diff --git a/VersionDate.tex b/VersionDate.tex index 590c876..f04b5c6 100644 --- a/VersionDate.tex +++ b/VersionDate.tex @@ -1,4 +1,4 @@ \begin{center} Version -December 20, 2016 +March 21, 2017 \end{center} diff --git a/apj.bst b/apj.bst index 71f0966..f7a0aa6 100644 --- a/apj.bst +++ b/apj.bst @@ -1,15 +1,19 @@ -%% 1998/08/12 J Baker -%% Tweaked by hand to get correct results for ApJ. Added functions from -%% astrobib. - %% $Log: apj.bst,v $ +%% Revision 1.4 2002/06/18 16:37:48 alberto +%% Add comma after first author in two-author reference +%% Fix courtesy of Tim Robishaw +%% %% Revision 1.3 2000/04/20 22:17:50 jbaker %% Fixed INBOOK bug, now works essentially like BOOK. %% %% Revision 1.2 1998/08/30 22:35:45 jbaker %% Added RCS keywords. %% +%% 1998/08/12 J Baker +%% Tweaked by hand to get correct results for ApJ. Added functions from +%% astrobib. + %% %% This is file `apj.bst', @@ -387,17 +391,26 @@ FUNCTION {format.names} { 's := #1 'nameptr := s num.names$ 'numnames := + numnames 'namesleft := { namesleft #0 > } - { s nameptr - "{vv~}{ll}{, jj}{, f.}" format.name$ - 't := + { + s nameptr "{vv~}{ll}{, jj}{, f.}" format.name$ 't := nameptr #1 > { + #8 numnames < + { #0 'namesleft := } + 'skip$ + if$ namesleft #1 > { ", " * t * } { - numnames #2 > + numnames #1 > +%% AA 6/18/2002 +%% This fix courtesy of Tim Robishaw : +%% Original version left comma out after initials of first author +%% for two-author papers!! +%% numnames #2 > { "," * } 'skip$ if$ @@ -405,7 +418,8 @@ FUNCTION {format.names} { 't := } { pop$ } if$ - t "others" = + %t "others" = + #8 numnames < { " {et~al.}" * } diff --git a/exgal_roadmap.pdf b/exgal_roadmap.pdf index 8b56d3f99d0550b6fafaafeacbcdcd690284dee0..e8f1b4bad74cbccae04db1eac12544e24c9c1b08 100644 GIT binary patch delta 192786 zcmZs?V{|4!v#uT6wl%RPd17Z`+qUf|wr$(CGqG*ko;W%0KIg+(Ywv&kuY2{XyX(HH zs}_HdV-}H6C>2D-8CV#9!%@yH4X?qmC7@t{ad0FhK+phd)Mec_02te+>K>MP=AFeHmOQdaNz80f8JaYE{#x~1jro?qFWyZs1Y?P_3`87Fub1Acsuu`3Dpvb80(#uoq&}s@FSbvQ(8J1S_oig0;%2K}6lzD{5r{@XV)`{TIqfp+k-0kMi;Dd7v^ z$%Y=(=Zmx>$C>~(W+C#gxB0L`cd6>1Dn3pSMFI*?jMPR3|G3v@%C~%i46Wm?6((yL z4mTugIFfuoaxgxDu;YakaF7`Qk)?TA-a7V$jSbw+Cjue0T5qL0FL>>y{x*f(oLhbz zi7DmCd!{TzHLe8zD<^q0VTMswb)CEOasn36d~R^3%)E14gPXRg>zRkm&wbm7Jm=3; 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\usepackage{pdflscape} -\newcommand{\ra}[1]{\renewcommand{\arraystretch}{#1}} \usepackage{float} - - \begin{document} +\input{journal_macros} +%\newcommand{\ra}[1]{\renewcommand{\arraystretch}{#1}} + %---------------------------------------------------------------------------------------- % TITLE PAGE %---------------------------------------------------------------------------------------- -\begingroup -\thispagestyle{empty} -%\begin{tikzpicture}[remember picture,overlay] -%\coordinate [below=11cm] (midpoint) at (current page.north); -%\node at (current page.north west) -%{\begin{tikzpicture}[remember picture,overlay] -%\node[anchor=north west,inner sep=0pt] at (0,0) {\includegraphics[]{cover_page.pdf}}; % Background image -%\draw[anchor=north] (midpoint) node [fill=ocre!30!white,fill opacity=0.6,text opacity=1,inner sep=1cm]{\centering\bfseries\sffamily\parbox[c][][t]{\paperwidth}{\centering\color{blue}{\fontsize{70}{80}\selectfont Galaxies}\\[15pt] % Book title -%{\Huge a hands-on introduction}\\[60pt] % Subtitle -%{\Huge Andrey Kravtsov}}}; % Author name -%\end{tikzpicture}}; -%\end{tikzpicture} -%{\Huge\bfseries\scshape Large Synoptic Survey Telescope} {\Huge Large Synoptic Survey Telescope} \linebreak \linebreak @@ -51,7 +30,6 @@ \input{VersionDate} } \vfill -\endgroup %---------------------------------------------------------------------------------------- % COPYRIGHT PAGE @@ -73,26 +51,12 @@ Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}). %\newpage -%~\vfill -%\thispagestyle{empty} - -%\noindent Copyright \copyright\ 2016 Andrey Kravtsov\\ % Copyright notice - -%\noindent \textsc{KICP Press}\\ % Publisher - -%\noindent \textsc{http://a-kravtsov.github.io/a304s16/}\\ % URL - -%\noindent Licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License (the ``License''). You may not use this file except in compliance with the License. You may obtain a copy of the License at \url{http://creativecommons.org/licenses/by-nc/3.0}. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \textsc{``as is'' basis, without warranties or conditions of any kind}, either express or implied. See the License for the specific language governing permissions and limitations under the License.\\ % License information - -%\noindent \textit{First printing, April 2016} % Printing/edition date - %---------------------------------------------------------------------------------------- % Table of Contents %---------------------------------------------------------------------------------------- -\usechapterimagefalse % If you don't want to include a chapter image, use this to toggle images off - it can be enabled later with \usechapterimagetrue -\pagestyle{empty} % No headers +%\pagestyle{empty} % No headers \include{abstract} @@ -100,83 +64,31 @@ %\chapterimage{simulation_background.png} % Table of contents heading image -\pagestyle{empty} % No headers +%\pagestyle{empty} % No headers \tableofcontents % Print the table of contents itself -\cleardoublepage % Forces the first chapter to start on an odd page so it's on the right +%\cleardoublepage % Forces the first chapter to start on an odd page so it's on the right -\nopagebreak[4] +%\nopagebreak[4] -%\pagestyle{fancy} % Print headers again -\pagestyle{empty} % Print headers again %---------------------------------------------------------------------------------------- % Chapters %---------------------------------------------------------------------------------------- - -% if it ever gets so big as to require Parts -%\part{Part One} -\pagestyle{empty} +%\pagestyle{empty} \include{introduction/introduction} -\pagestyle{empty} +%\pagestyle{empty} \include{science_background/science_background} -\pagestyle{empty} -\include{roadmap/roadmap} -\pagestyle{empty} +%\pagestyle{empty} +%\include{roadmap/roadmap} +%\pagestyle{empty} \include{task_lists/task_lists} -%\include{matrix/matrix} - - - -%\chapterimage{ch2_header.png} % Chapter heading image -%\include{galaxy_formation} - -%\appendix -%\chapterimage{uvhudf.PNG} -%\include{cosmology_distances} -%\chapterimage{suppl_header.jpg} -%\include{supplementary} -%\chapterimage{python_xkcd2.PNG} -%\include{python} -%\chapterimage{sdss_data_banner.png} -%\include{data_access}%\appendix{Practical info on accessing various data sets} -%\chapterimage{banner_bookshelf.jpg} -%\printbibliography - -%---------------------------------------------------------------------------------------- -% INDEX -%---------------------------------------------------------------------------------------- - -%\cleardoublepage -%\phantomsection -%\setlength{\columnsep}{0.75cm} -%\addcontentsline{toc}{chapter}{\textcolor{ocre}{Index}} -%\printindex - -%---------------------------------------------------------------------------------------- +%--------------------------------------------------------------------------------------- +\bibliography{references} \end{document} -%------------------------------------------------ - -%\section{Figure}\index{Figure} -%\begin{figure}[h] -%\centering\includegraphics[scale=0.5]{blanton_moustakas_wordcloud.pdf} -%\caption{Figure caption} -%\end{figure} - - -\begin{figure}[ht] -\includemedia[ -label=LG, -width=0.5\linewidth,height=0.5\linewidth, -activate=pageopen, -3Dtoolbar, 3Dmenu, -3Dviews=dice.vws, -]{}{fig/LG3d.u3d} -\end{figure} -\end{document} diff --git a/introduction/introduction.tex b/introduction/introduction.tex index 4c8def9..0bc3019 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -48,16 +48,24 @@ science themes of these investigations, outlines how complementary techniques will contribute, and identifies areas where advance work is essential. For this advance work, the emphasis is on areas that are not adequately covered in the -DESC roadmap. As convenient shorthand, we use the acronym GALLA (Galaxies, AGN, Lensing -Large-scale Structure and Astro-informatics) joint roadmap of the overlapping -science collaborations. +DESC roadmap. +%As convenient shorthand, we use the acronym GALLA (Galaxies, AGN, Lensing +%Large-scale Structure and Astro-informatics) joint roadmap of the overlapping +%science collaborations. Chapter \ref{ch:science_background} gives a brief summary of the science background. Many of the themes and projects are already set out in the Science Book, where more -detail is provided for many of the science investigations. Chapter \ref{ch:roadmap} -sets out the highest priority preparatory work to enable these investigations. These tasks -are laid out on the assumption that the work plan of the DESC will be carried out -and that software and data products resulting from that work will be available to -other science collaborations. The Appendix \ref{ch:task_lists} organizes the tasks -by science topic and desribes them in more detail. +detail is provided for many of the science investigations. +Chapter \ref{ch:task_lists} presents preparatory science tasks for +Extragalactic science with LSST. These tasks are organized by science topic. +The science task list content assumes that the work plan of the DESC will be executed +and that the resulting software and other data products resulting from the DESC +efforts will be made available to the other science collaborations. +%Chapter \ref{ch:roadmap} +%sets out the highest priority preparatory work to enable these investigations. +%These tasks +%are laid out on the assumption that the work plan of the DESC will be carried out +%and that software and data products resulting from that work will be available to +%other science collaborations. The Appendix \ref{ch:task_lists} organizes the tasks +%by science topic and desribes them in more detail. diff --git a/references.bib b/references.bib index b7274fb..2c7a4c0 100644 --- a/references.bib +++ b/references.bib @@ -1,17 +1,20 @@ -@article{LSSTSciBook, - author = "Abell, Paul A. and others", - title = "{LSST Science Book, Version 2.0}", - collaboration = "LSST Science Collaborations, LSST Project", - year = "2009", - eprint = "0912.0201", - archivePrefix = "arXiv", - primaryClass = "astro-ph.IM", - reportNumber = "FERMILAB-TM-2495-A", - SLACcitation = "%%CITATION = ARXIV:0912.0201;%%", +@ARTICLE{LSSTSciBook, + author = {{LSST Science Collaboration} and {Abell}, P.~A. and {Allison}, J. and + {Anderson}, S.~F. and {Andrew}, J.~R. and {Angel}, J.~R.~P. and + {Armus}, L. and {Arnett}, D. and {Asztalos}, S.~J. and {Axelrod}, T.~S. and et al.}, + title = "{LSST Science Book, Version 2.0}", + journal = {ArXiv e-prints}, +archivePrefix = "arXiv", + eprint = {0912.0201}, + primaryClass = "astro-ph.IM", + keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Galaxy Astrophysics, Astrophysics - Solar and Stellar Astrophysics}, + year = 2009, + month = dec, + adsurl = {http://adsabs.harvard.edu/abs/2009arXiv0912.0201L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} } - %AAAAAAAAAAA @ARTICLE{abraham2003a, author = {{Abraham}, R.~G. and {van den Bergh}, S. and {Nair}, P.}, @@ -311,17 +314,7 @@ @ARTICLE{lotz2008a adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...672..177L}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } -@article{LSSTSciBook, - author = "Abell, Paul A. and others", - title = "{LSST Science Book, Version 2.0}", - collaboration = "LSST Science Collaborations, LSST Project", - year = "2009", - eprint = "0912.0201", - archivePrefix = "arXiv", - primaryClass = "astro-ph.IM", - reportNumber = "FERMILAB-TM-2495-A", - SLACcitation = "%%CITATION = ARXIV:0912.0201;%%", -} + %MMMMMMMMMMM @ARTICLE{madau2014a, author = {{Madau}, P. and {Dickinson}, M.}, diff --git a/roadmap/roadmap.tex~ b/roadmap/roadmap.tex~ deleted file mode 100644 index c536354..0000000 --- a/roadmap/roadmap.tex~ +++ /dev/null @@ -1,25 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% First draft by - -\chapter[Science Background]{Science Background} -\label{ch:science_background} - -TBD - -\input{science_background/chapterintro.tex} - - -\input{science_background/black_holes/black_holes.tex} - -\input{science_background/galaxies/galaxies.tex} - -\input{science_background/informatics/informatics.tex} - -\input{science_background/lss/lss.tex} - -\input{science_background/strong_lensing/strong_lensing.tex} - -\input{science_background/weak_lensing/weak_lensing.tex} - diff --git a/science_background/chapterintro.tex~ b/science_background/chapterintro.tex~ deleted file mode 100644 index c17e6cc..0000000 --- a/science_background/chapterintro.tex~ +++ /dev/null @@ -1,7 +0,0 @@ -% LSST Extragalactic Roadmap -% Chapter: science_background -% First draft by - -\section{Overview}\label{sec:sci:intro} - - diff --git a/science_background/galaxies/galaxies.tex~ b/science_background/galaxies/galaxies.tex~ deleted file mode 100644 index 3cad1ba..0000000 --- a/science_background/galaxies/galaxies.tex~ +++ /dev/null @@ -1,10 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: galaxies -% First draft by - -\section{XXX}\label{sec:sci:gal:XXX} - - - diff --git a/science_background/science_background.tex~ b/science_background/science_background.tex~ deleted file mode 100644 index 79f8b96..0000000 --- a/science_background/science_background.tex~ +++ /dev/null @@ -1,25 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% First draft by - -\chapter[Science Background] -\label{ch:science_background} - -TBD - -\input{science_background/chapterintro.tex} - - -\input{science_background/black_holes/black_holes.tex} - -\input{science_background/galaxies/galaxies.tex} - -\input{science_background/informatics/informatics.tex} - -\input{science_background/lss/lss.tex} - -\input{science_background/strong_lensing/strong_lensing.tex} - -\input{science_background/weak_lensing/weak_lensing.tex} - diff --git a/structure.tex b/structure.tex index c883372..6738e01 100644 --- a/structure.tex +++ b/structure.tex @@ -1,614 +1,39 @@ -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% The Legrand Orange Book -% Structural Definitions File -% Version 2.0 (9/2/15) -% -% Original author: -% Mathias Legrand (legrand.mathias@gmail.com) with modifications by: -% Vel (vel@latextemplates.com) and Andrey Kravtsov (akravtsov@gmail.com) -% -% This file has been downloaded from: -% http://www.LaTeXTemplates.com -% -% License: -% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/) -% -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% The Legrand Orange Book -% LaTeX Template -% Version 2.1.1 (14/2/16) -% -% This template has been downloaded from: -% http://www.LaTeXTemplates.com -% -% Original author: -% Mathias Legrand (legrand.mathias@gmail.com) with modifications by: -% Vel (vel@latextemplates.com) -% -% License: -% CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/) -% -% Compiling this template: -% This template uses biber for its bibliography and makeindex for its index. -% When you first open the template, compile it from the command line with the -% commands below to make sure your LaTeX distribution is configured correctly: -% -% 1) pdflatex main -% 2) makeindex main.idx -s StyleInd.ist -% 3) biber main -% 4) pdflatex main x 2 -% -% After this, when you wish to update the bibliography/index use the appropriate -% command above and make sure to compile with pdflatex several times -% afterwards to propagate your changes to the document. -% -% This template also uses a number of packages which may need to be -% updated to the newest versions for the template to compile. 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+%FONTS +\usepackage{anyfontsize} \usepackage{avant} % Use the Avantgarde font for headings -%\usepackage{times} % Use the Times font for headings \usepackage{mathptmx} % Use the Adobe Times Roman as the default text font together with math symbols from the Sym­bol, Chancery and Com­puter Modern fonts - \usepackage{microtype} % Slightly tweak font spacing for aesthetics -\usepackage[utf8]{inputenc} % Required for including letters with accents -\usepackage[T1]{fontenc} % Use 8-bit encoding that has 256 glyphs -%---------------------------------------------------------------------------------------- -% BIBLIOGRAPHY AND INDEX -%---------------------------------------------------------------------------------------- -%\usepackage[citestyle=authoryear,style=alphabetic,natbib=true,sorting=nyt,sortcites=true,autopunct=true,babel=hyphen,hyperref=true,abbreviate=false,backref=true,backend=biber]{biblatex} -\usepackage[backend=bibtex,style=authoryear,sortcites=true,autopunct=true,babel=hyphen,hyperref=true,abbreviate=false,backref=false,natbib]{biblatex} -%\usepackage{natbib} -%\newcommand{\citep}{\autocite} -%\newcommand{\citet}{\textcite} -%\newcommand{\citealp}{\cite} -\addbibresource{galaxies.bib} % BibTeX bibliography file -%\defbibheading{bibempty}{} \usepackage{calc} % For simpler calculation - used for spacing the index letter headings correctly \usepackage{makeidx} % Required to make an index \makeindex % Tells LaTeX to create the files required for indexing -%---------------------------------------------------------------------------------------- -% MAIN TABLE OF CONTENTS -%---------------------------------------------------------------------------------------- - -\usepackage{titletoc} % Required for manipulating the table of contents - -\contentsmargin{0cm} % Removes the default margin - -% Part text styling -\titlecontents{part}[0cm] -{\addvspace{20pt}\centering\large\bfseries} -{} -{} -{} - -% Chapter text styling -\titlecontents{chapter}[1.25cm] % Indentation -{\addvspace{12pt}\large\sffamily\bfseries} % Spacing and font options for chapters -{\color{ocre!60}\contentslabel[\Large\thecontentslabel]{1.25cm}\color{ocre}} % Chapter number -{\color{ocre}} -{\color{ocre!60}\normalsize\;\titlerule*[.5pc]{.}\;\thecontentspage} % Page number - -% Section text styling -\titlecontents{section}[1.25cm] % Indentation -{\addvspace{3pt}\sffamily\bfseries} % Spacing and font options for sections -{\contentslabel[\thecontentslabel]{1.25cm}} % Section number -{} -{\hfill\color{black}\thecontentspage} % Page number -[] - -% Subsection text styling -\titlecontents{subsection}[1.25cm] % Indentation -{\addvspace{1pt}\sffamily\small} % Spacing and font options for subsections -{\contentslabel[\thecontentslabel]{1.25cm}} % Subsection number -{} -{\ \titlerule*[.5pc]{.}\;\thecontentspage} % Page number -[] - -% List of figures -\titlecontents{figure}[0em] -{\addvspace{-5pt}\sffamily} -{\thecontentslabel\hspace*{1em}} -{} -{\ \titlerule*[.5pc]{.}\;\thecontentspage} -[] - -% List of tables -\titlecontents{table}[0em] -{\addvspace{-5pt}\sffamily} -{\thecontentslabel\hspace*{1em}} -{} -{\ \titlerule*[.5pc]{.}\;\thecontentspage} -[] - -%---------------------------------------------------------------------------------------- -% MINI TABLE OF CONTENTS IN PART HEADS -%---------------------------------------------------------------------------------------- - -% Chapter text styling -\titlecontents{lchapter}[0em] % Indenting -{\addvspace{15pt}\large\sffamily\bfseries} % Spacing and font options for chapters -{\color{ocre}\contentslabel[\Large\thecontentslabel]{1.25cm}\color{ocre}} % Chapter number -{} -{\color{ocre}\normalsize\sffamily\bfseries\;\titlerule*[.5pc]{.}\;\thecontentspage} % Page number - -% Section text styling -\titlecontents{lsection}[0em] % Indenting -{\sffamily\small} % Spacing and font options for sections -{\contentslabel[\thecontentslabel]{1.25cm}} % Section number -{} -{} - -% Subsection text styling -\titlecontents{lsubsection}[.5em] % Indentation -{\normalfont\footnotesize\sffamily} % Font settings -{} -{} -{} - -%---------------------------------------------------------------------------------------- -% PAGE HEADERS -%---------------------------------------------------------------------------------------- - -\usepackage{fancyhdr} % Required for header and footer configuration - -\pagestyle{fancy} -\renewcommand{\chaptermark}[1]{\markboth{\sffamily\normalsize\bfseries\chaptername\ \thechapter.\ #1}{}} % Chapter text font settings -\renewcommand{\sectionmark}[1]{\markright{\sffamily\normalsize\thesection\hspace{5pt}#1}{}} % Section text font settings -\fancyhf{} \fancyhead[LE,RO]{\sffamily\normalsize\thepage} % Font setting for the page number in the header -\fancyhead[LO]{\rightmark} % Print the nearest section name on the left side of odd pages -\fancyhead[RE]{\leftmark} % Print the current chapter name on the right side of even pages -\renewcommand{\headrulewidth}{0.5pt} % Width of the rule under the header -\addtolength{\headheight}{2.5pt} % Increase the spacing around the header slightly -\renewcommand{\footrulewidth}{0pt} % Removes the rule in the footer -\fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}} % Style for when a plain pagestyle is specified - -% Removes the header from odd empty pages at the end of chapters -\makeatletter -\renewcommand{\cleardoublepage}{ -\clearpage\ifodd\c@page\else -\hbox{} -\vspace*{\fill} -\thispagestyle{empty} -\pagebreak -\fi} - -%---------------------------------------------------------------------------------------- -% THEOREM STYLES -%---------------------------------------------------------------------------------------- - -\usepackage{amsmath,amsfonts,amssymb,amsthm} % For math equations, theorems, symbols, etc - -\newcommand{\intoo}[2]{\mathopen{]}#1\,;#2\mathclose{[}} -\newcommand{\ud}{\mathop{\mathrm{{}d}}\mathopen{}} -\newcommand{\intff}[2]{\mathopen{[}#1\,;#2\mathclose{]}} -\newtheorem{notation}{Notation}[chapter] -% Boxed/framed environments -\newtheoremstyle{ocrenumbox}% % Theorem style name -{0pt}% Space above -{0pt}% Space below -{\normalfont}% % Body font -{}% Indent amount -{\small\bf\sffamily\color{ocre}}% % Theorem head font -{\;}% Punctuation after theorem head -{0.25em}% Space after theorem head -{\small\sffamily\color{ocre}\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) -\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries\color{black}---\nobreakspace#3.}} % Optional theorem note -\renewcommand{\qedsymbol}{$\blacksquare$}% Optional qed square -\newtheoremstyle{blacknumex}% Theorem style name -{5pt}% Space above -{5pt}% Space below -{\normalfont}% Body font -{} % Indent amount -{\small\bf\sffamily}% Theorem head font -{\;}% Punctuation after theorem head -{0.25em}% Space after theorem head -{\small\sffamily{\tiny\ensuremath{\blacksquare}}\nobreakspace\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) -\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries---\nobreakspace#3.}}% Optional theorem note +\bibliographystyle{apj} +\usepackage{natbib} -\newtheoremstyle{blacknumbox} % Theorem style name -{0pt}% Space above -{0pt}% Space below -{\normalfont}% Body font -{}% Indent amount -{\small\bf\sffamily}% Theorem head font -{\;}% Punctuation after theorem head -{0.25em}% Space after theorem head -{\small\sffamily\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) -\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries---\nobreakspace#3.}}% Optional theorem note +%\usepackage{titletoc} % Required for manipulating the table of contents -% Non-boxed/non-framed environments -\newtheoremstyle{ocrenum}% % Theorem style name -{5pt}% Space above -{5pt}% Space below -{\normalfont}% % Body font -{}% Indent amount -{\small\bf\sffamily\color{ocre}}% % Theorem head font -{\;}% Punctuation after theorem head -{0.25em}% Space after theorem head -{\small\sffamily\color{ocre}\thmname{#1}\nobreakspace\thmnumber{\@ifnotempty{#1}{}\@upn{#2}}% Theorem text (e.g. Theorem 2.1) -\thmnote{\nobreakspace\the\thm@notefont\sffamily\bfseries\color{black}---\nobreakspace#3.}} % Optional theorem note -\renewcommand{\qedsymbol}{$\blacksquare$}% Optional qed square -\makeatother -% Defines the theorem text style for each type of theorem to one of the three styles above -\newcounter{dummy} -\numberwithin{dummy}{section} -\theoremstyle{ocrenumbox} -\newtheorem{theoremeT}[dummy]{Theorem} -\newtheorem{problem}{Problem}[chapter] -\newtheorem{exerciseT}{Exercise}[chapter] -\theoremstyle{blacknumex} -\newtheorem{exampleT}{Example}[chapter] -\theoremstyle{blacknumbox} -\newtheorem{vocabulary}{Vocabulary}[chapter] -\newtheorem{definitionT}{Definition}[section] -\newtheorem{corollaryT}[dummy]{Corollary} -\theoremstyle{ocrenum} -\newtheorem{proposition}[dummy]{Proposition} -%---------------------------------------------------------------------------------------- -% DEFINITION OF COLORED BOXES -%---------------------------------------------------------------------------------------- - -\RequirePackage[framemethod=default]{mdframed} % Required for creating the theorem, definition, exercise and corollary boxes - -% Theorem box -\newmdenv[skipabove=7pt, -skipbelow=7pt, -backgroundcolor=black!5, -linecolor=ocre, -innerleftmargin=5pt, -innerrightmargin=5pt, -innertopmargin=5pt, -leftmargin=0cm, -rightmargin=0cm, -innerbottommargin=5pt]{tBox} - -% Exercise box -\newmdenv[skipabove=7pt, -skipbelow=7pt, -rightline=false, -leftline=true, -topline=false, -bottomline=false, -backgroundcolor=ocre!10, -linecolor=ocre, -innerleftmargin=5pt, -innerrightmargin=5pt, -innertopmargin=5pt, -innerbottommargin=5pt, -leftmargin=0cm, -rightmargin=0cm, -linewidth=4pt]{eBox} - -% Definition box -\newmdenv[skipabove=7pt, -skipbelow=7pt, -rightline=false, -leftline=true, -topline=false, -bottomline=false, -linecolor=ocre, -innerleftmargin=5pt, -innerrightmargin=5pt, -innertopmargin=0pt, -leftmargin=0cm, -rightmargin=0cm, -linewidth=4pt, -innerbottommargin=0pt]{dBox} - -% Corollary box -\newmdenv[skipabove=7pt, -skipbelow=7pt, -rightline=false, -leftline=true, -topline=false, -bottomline=false, -linecolor=gray, -backgroundcolor=black!5, -innerleftmargin=5pt, -innerrightmargin=5pt, -innertopmargin=5pt, -leftmargin=0cm, -rightmargin=0cm, -linewidth=4pt, -innerbottommargin=5pt]{cBox} - -% Creates an environment for each type of theorem and assigns it a theorem text style from the "Theorem Styles" section above and a colored box from above -\newenvironment{theorem}{\begin{tBox}\begin{theoremeT}}{\end{theoremeT}\end{tBox}} -\newenvironment{exercise}{\begin{eBox}\begin{exerciseT}}{\hfill{\color{ocre}\tiny\ensuremath{\blacksquare}}\end{exerciseT}\end{eBox}} -\newenvironment{definition}{\begin{dBox}\begin{definitionT}}{\end{definitionT}\end{dBox}} -\newenvironment{example}{\begin{exampleT}}{\hfill{\tiny\ensuremath{\blacksquare}}\end{exampleT}} -\newenvironment{corollary}{\begin{cBox}\begin{corollaryT}}{\end{corollaryT}\end{cBox}} - -%---------------------------------------------------------------------------------------- -% REMARK ENVIRONMENT -%---------------------------------------------------------------------------------------- - -\newenvironment{remark}{\par\vspace{10pt}\small % Vertical white space above the remark and smaller font size -\begin{list}{}{ -\leftmargin=35pt % Indentation on the left -\rightmargin=25pt}\item\ignorespaces % Indentation on the right -\makebox[-2.5pt]{\begin{tikzpicture}[overlay] -\node[draw=ocre!60,line width=1pt,circle,fill=ocre!25,font=\sffamily\bfseries,inner sep=2pt,outer sep=0pt] at (-15pt,0pt){\textcolor{ocre}{R}};\end{tikzpicture}} % Orange R in a circle -\advance\baselineskip -1pt}{\end{list}\vskip5pt} % Tighter line spacing and white space after remark - -%---------------------------------------------------------------------------------------- -% SECTION NUMBERING IN THE MARGIN -%---------------------------------------------------------------------------------------- - -\makeatletter -\renewcommand{\@seccntformat}[1]{\llap{\textcolor{ocre}{\csname the#1\endcsname}\hspace{1em}}} -\renewcommand{\section}{\@startsection{section}{1}{\z@} -{-4ex \@plus -1ex \@minus -.4ex} -{1ex \@plus.2ex } -{\normalfont\large\sffamily\bfseries}} -\renewcommand{\subsection}{\@startsection {subsection}{2}{\z@} -{-3ex \@plus -0.1ex \@minus -.4ex} -{0.5ex \@plus.2ex } -{\normalfont\sffamily\bfseries}} -\renewcommand{\subsubsection}{\@startsection {subsubsection}{3}{\z@} -{-2ex \@plus -0.1ex \@minus -.2ex} -{.2ex \@plus.2ex } -{\normalfont\small\sffamily\bfseries}} -\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@} -{-2ex \@plus-.2ex \@minus .2ex} -{.1ex} -{\normalfont\small\sffamily\bfseries}} - -%---------------------------------------------------------------------------------------- -% PART HEADINGS -%---------------------------------------------------------------------------------------- - -% numbered part in the table of contents -\newcommand{\@mypartnumtocformat}[2]{% -\setlength\fboxsep{0pt}% -\noindent\colorbox{ocre!20}{\strut\parbox[c][.7cm]{\ecart}{\color{ocre!70}\Large\sffamily\bfseries\centering#1}}\hskip\esp\colorbox{ocre!40}{\strut\parbox[c][.7cm]{\linewidth-\ecart-\esp}{\Large\sffamily\centering#2}}}% -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% unnumbered part in the table of contents -\newcommand{\@myparttocformat}[1]{% -\setlength\fboxsep{0pt}% -\noindent\colorbox{ocre!40}{\strut\parbox[c][.7cm]{\linewidth}{\Large\sffamily\centering#1}}}% -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -\newlength\esp -\setlength\esp{4pt} -\newlength\ecart -\setlength\ecart{1.2cm-\esp} -\newcommand{\thepartimage}{}% -\newcommand{\partimage}[1]{\renewcommand{\thepartimage}{#1}}% -\def\@part[#1]#2{% -\ifnum \c@secnumdepth >-2\relax% -\refstepcounter{part}% -\addcontentsline{toc}{part}{\texorpdfstring{\protect\@mypartnumtocformat{\thepart}{#1}}{\partname~\thepart\ ---\ #1}} -\else% -\addcontentsline{toc}{part}{\texorpdfstring{\protect\@myparttocformat{#1}}{#1}}% -\fi% -\startcontents% -\markboth{}{}% -{\thispagestyle{empty}% -\begin{tikzpicture}[remember picture,overlay]% -\node at (current page.north west){\begin{tikzpicture}[remember picture,overlay]% -\fill[ocre!20](0cm,0cm) rectangle (\paperwidth,-\paperheight); -\node[anchor=north] at (4cm,-3.25cm){\color{ocre!40}\fontsize{220}{100}\sffamily\bfseries\@Roman\c@part}; -\node[anchor=south east] at (\paperwidth-1cm,-\paperheight+1cm){\parbox[t][][t]{8.5cm}{ -\printcontents{l}{0}{\setcounter{tocdepth}{1}}% -}}; -\node[anchor=north east] at (\paperwidth-1.5cm,-3.25cm){\parbox[t][][t]{15cm}{\strut\raggedleft\color{white}\fontsize{30}{30}\sffamily\bfseries#2}}; -\end{tikzpicture}}; -\end{tikzpicture}}% -\@endpart} -\def\@spart#1{% -\startcontents% -\phantomsection -{\thispagestyle{empty}% -\begin{tikzpicture}[remember picture,overlay]% -\node at (current page.north west){\begin{tikzpicture}[remember picture,overlay]% -\fill[ocre!20](0cm,0cm) rectangle (\paperwidth,-\paperheight); -\node[anchor=north east] at (\paperwidth-1.5cm,-3.25cm){\parbox[t][][t]{15cm}{\strut\raggedleft\color{white}\fontsize{30}{30}\sffamily\bfseries#1}}; -\end{tikzpicture}}; -\end{tikzpicture}} -\addcontentsline{toc}{part}{\texorpdfstring{% -\setlength\fboxsep{0pt}% -\noindent\protect\colorbox{ocre!40}{\strut\protect\parbox[c][.7cm]{\linewidth}{\Large\sffamily\protect\centering #1\quad\mbox{}}}}{#1}}% -\@endpart} -\def\@endpart{\vfil\pagebreak%\newpage -\if@twoside -\if@openright -\null -\thispagestyle{empty}% -%\newpage -\pagebreak -\fi -\fi -\if@tempswa -\twocolumn -\fi} - -%---------------------------------------------------------------------------------------- -% CHAPTER HEADINGS -%---------------------------------------------------------------------------------------- - -% A switch to conditionally include a picture, implemented by Christian Hupfer -\newif\ifusechapterimage -\usechapterimagetrue -\newcommand{\thechapterimage}{}% -\newcommand{\chapterimage}[1]{\ifusechapterimage\renewcommand{\thechapterimage}{#1}\fi}% -\def\@makechapterhead#1{% -{\parindent \z@ \raggedright \normalfont -\ifnum \c@secnumdepth >\m@ne -\if@mainmatter -\begin{tikzpicture}[remember picture,overlay] -\node at (current page.north west) -{\begin{tikzpicture}[remember picture,overlay] -\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; -%rounded box -%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; -\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}\thechapter. #1\strut}; -\end{tikzpicture}}; -\end{tikzpicture} -\else -\begin{tikzpicture}[remember picture,overlay] -\node at (current page.north west) -{\begin{tikzpicture}[remember picture,overlay] -\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; -%rounded box -%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; -\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; -\end{tikzpicture}}; -\end{tikzpicture} -\fi\fi\par\vspace*{270\p@}}} - -%------------------------------------------- - -\def\@makeschapterhead#1{% -\begin{tikzpicture}[remember picture,overlay] -\node at (current page.north west) -{\begin{tikzpicture}[remember picture,overlay] -\node[anchor=north west,inner sep=0pt] at (0,0) {\ifusechapterimage\includegraphics[width=\paperwidth]{\thechapterimage}\fi}; -%rounded box -%\draw[anchor=west] (\Gm@lmargin,-9cm) node [line width=2pt,rounded corners=15pt,draw=ocre,fill=white,fill opacity=0.5,inner sep=15pt]{\strut\makebox[22cm]{}}; -\draw[anchor=west] (\Gm@lmargin+.3cm,-9cm) node {\huge\sffamily\bfseries\color{black}#1\strut}; -\end{tikzpicture}}; -\end{tikzpicture} -%\par\vspace*{270\p@}} -\par\vspace*{170\p@}} -%\par\vspace*{100\p@}} -\makeatother - -%---------------------------------------------------------------------------------------- -% HYPERLINKS IN THE DOCUMENTS -%---------------------------------------------------------------------------------------- - -\usepackage{hyperref} -\hypersetup{hidelinks,backref=true,pagebackref=true,hyperindex=true,colorlinks=false,breaklinks=true,urlcolor= ocre,bookmarks=true,bookmarksopen=false,pdftitle={Title},pdfauthor={Author}} -\usepackage{bookmark} -\bookmarksetup{ -open, -numbered, -addtohook={% -\ifnum\bookmarkget{level}=0 % chapter -\bookmarksetup{bold}% -\fi -\ifnum\bookmarkget{level}=-1 % part -\bookmarksetup{color=ocre,bold}% -\fi -} -} - - -%------------------------------------------------------------------------------% -% Task formatting: - -% PJM: description environment for tasks, needs(?) -% item heading macros, to allow global editing, and italic headings. - -% \renewcommand\descriptionlabel[1]{\hspace{\labelsep}{\textsl{#1}}} -% \def\motivation{Motivation:} -% \def\activities{Activities:} -% \def\deliverables{Deliverables:} - -% Example usage: -% -% \begin{description} -% \item[\motivation] Currently things are bad. -% \item[\activities] We will work to make them better. -% \item[\deliverables] Code to solve all problems. -% \end{description} - - -% PJM: The following macro works, but is not very transparent to the writer... -% \def\task#1#2#3% -% {\begin{description} -% \item[Motivation]{#1} -% \item[Activities]{#2} -% \item[Deliverables]{#3} -% \end{description}} - -% Example usage: -% -% \task -% {Currently things are bad.} -% {We will work to make them better.} -% {Code to solve all problems.} - - -% PJM: OK, this is better - now only task items are italicised, and we have -% control over all tasks: +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists \def\motivation#1{\item[Motivation:] #1} \def\activities#1{\item[Activities:] #1} @@ -629,20 +54,9 @@ % PJM: here's a tasklist environment to take care of Michael's enumeration: -\def\tasktitle#1{\item{\bf #1}} +%\def\tasktitle#1{\item{\bf #1}} +\def\tasktitle#1{\item{}} \newenvironment{tasklist}[1]% {\begin{enumerate}[label=#1-\arabic{*}.,ref=\thesubsection:#1-\arabic{*},font=\bf]} {\end{enumerate}} - -% Example usage: -% -% \begin{tasklist}{H} -% \tasktitle{Automated Lens Candidate Detection in the LSST Catalogs [Lupton]} -% \label{task:sl:detection} -% \begin{task} -% \motivation{Currently things are bad}. -% \activities{We will work to make them better}. -% \deliverables{Code to solve all problems}. -% \end{task} -% \end{tasklist} diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index fbd0e2c..7705045 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -2,7 +2,9 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} AGN are phenomena that enable us to understand the growth of BHs, understand aspects of galaxy evolution, probe the high redshift universe and study other physical activity, including accretion physics, jets, magnetic fields, etc. There are distinct aspects of the study of AGN that can best be explored by considering AGN as an evolutionary stage of galaxies rather than a distinct type of source. The tasks listed here explore aspects of AGN study that are particularly important AGN as a stage in galaxy evolution. + \begin{tasklist}{AGN} +\subsection{AGN feedback in clusters} \tasktitle{AGN feedback in clusters} \begin{task} \label{task:agn:feedback_in_clusters} @@ -26,6 +28,7 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} %\begin{tasklist}{T} +\subsection{AGN Selection from LSST Data} \tasktitle{AGN Selection from LSST Data} \begin{task} \label{task:agn:selection} @@ -50,6 +53,7 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} %\begin{tasklist}{T} +\subsection{AGN Host Galaxy Properties from LSST Data} \tasktitle{AGN Host Galaxy Properties from LSST Data} \begin{task} \label{task:agn:host_galaxies} @@ -69,6 +73,7 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} %\end{tasklist} %\begin{tasklist}{T} +\subsection{AGN Variability Selection in LSST Data} \tasktitle{AGN Variability Selection in LSST Data} \begin{task} \label{task:agn:variability} @@ -87,6 +92,7 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} %\end{tasklist} %\begin{tasklist}{T} +\subsection{AGN Photometric Redshifts from LSST Data} \tasktitle{AGN Photometric Redshifts from LSST Data} \begin{task} \label{task:agn:photoz} @@ -106,6 +112,7 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} %\end{tasklist} %\begin{tasklist}{T} +\subsection{AGN Merger Signature from LSST Data} \tasktitle{AGN Merger Signature from LSST Data} \begin{task} \label{task:agn:mergers} diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index c7115ed..c1facfb 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -1,8 +1,10 @@ + \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} Summary \begin{tasklist}{CLSS} +\subsection{Cluster/LSS Sample Emulator} \tasktitle{Cluster/LSS Sample Emulator} \begin{task} \label{task:clss:emulator} @@ -51,6 +53,7 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} \end{task} +\subsection{Identifying and Characterizing Clusters} \tasktitle{Identifying and Characterizing Clusters} \begin{task} \label{task:clss:clusters} @@ -103,7 +106,7 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} - +\subsection{Developing and Optimizing Measurements of Galaxy Environment} \tasktitle{Developing and Optimizing Measurements of Galaxy Environment} \begin{task} \label{task:clss:environment} @@ -150,6 +153,7 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} } \end{task} +\subsection{Enabling and Optimizing Measurements of Galaxy Clustering} \tasktitle{Enabling and Optimizing Measurements of Galaxy Clustering} \begin{task} \label{task:clss:clustering} @@ -206,6 +210,7 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} \end{task} +\subsection{Disentangling Complicated Lines of Sight} \tasktitle{Disentangling Complicated Lines of Sight} \begin{task} \label{task:clss:los} @@ -261,7 +266,7 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} - +\subsection{Forward Modeling LSST Clusters and Groups} \tasktitle{Forward Modeling LSST Clusters and Groups} \begin{task} \label{task:clss:cluster_fm} diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index 90ce8ab..c7f0545 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -3,6 +3,8 @@ \section{Deep Drilling Fields}\label{sec:tasks:ddf} The LSST Drilling-Fields (DDF) are areas that have a higher cadence and deeper observations than the Deep-Wide survey. Many of the details of the observing strategy have yet to be finalized. Four Deep-Drilling fields have been selected. Whether to include any others will be part of a complex trade involving other special projects that depart from the Deep-Wide survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy are all still under study, and the Project needs input from the science collaborations to inform these decisions. The tasks outlined in this section are intended to help optimize the LSST observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy-evolution science. \begin{tasklist}{DDF} + +\subsection{Coordinating Ancillary Observations} \tasktitle{Coordinating Ancillary Observations} \begin{task} \label{task:ddf:ancillary_obs} @@ -29,6 +31,7 @@ \section{Deep Drilling Fields}\label{sec:tasks:ddf} } \end{task} +\subsection{Observing Strategy “Cadence”} \tasktitle{Observing Strategy “Cadence”} \begin{task} \label{task:ddf:cadence} @@ -46,7 +49,7 @@ \section{Deep Drilling Fields}\label{sec:tasks:ddf} } \end{task} - +\subsection{Data Processing} \tasktitle{Data Processing} \begin{task} \label{task:ddf:data_processing} diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index ecd101e..0ed6cc8 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -23,21 +23,22 @@ \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} LSST survey design and DM optimization, but which will ensure good support for LSST galaxy studies. -\begin{tasklist}{G} -\tasktitle{Example Task List} -\begin{task} -\label{task:label_for_this_task} -\motivation{Put Science Motivation Here} -\activities{Described Activities Here} -\deliverables{ - Deliverables over the next several years from the activities described above include the following: - \begin{enumerate} - \item a deliverable - \item another deliverable - \end{enumerate} -} -\end{task} -\end{tasklist} +%\begin{tasklist}{G} +%\subsection{Example Task List} +%\tasktitle{Example Task List} +%\begin{task} +%\label{task:label_for_this_task} +%\motivation{Put Science Motivation Here} +%\activities{Described Activities Here} +%\deliverables{ +% Deliverables over the next several years from the activities described above include the following: +% \begin{enumerate} +% \item a deliverable +% \item another deliverable +% \end{enumerate} +%} +%\end{task} +%\end{tasklist} \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} @@ -123,6 +124,7 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga } \end{task} +\subsection{Techniques for identifying and deblending overlapping galaxies} \tasktitle{Techniques for identifying and deblending overlapping galaxies} \begin{task} \label{task:gal:deblending} @@ -188,6 +190,7 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga } \end{task} +\subsection{Optimizing Galaxy Morphology Measurements} \tasktitle{Optimizing Galaxy Morphology Measurements} % techniques for identifying mergers % Bayesian techniques for inference from large data sets @@ -241,6 +244,7 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga } \end{task} +\subsection{Optimizing Galaxy Photometry} \tasktitle{Optimizing Galaxy Photometry} % background subtraction % optimal co-adds @@ -294,6 +298,7 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga } \end{task} +\subsection{Optimizing Measurements of Stellar Population Parameters} \tasktitle{Optimizing Measurements of Stellar Population Parameters} % Strategies for dealing with strong covariance of parameter estmates \begin{task} @@ -330,6 +335,7 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga } \end{task} +\subsection{Software Integration} \tasktitle{Software Integration} % Level 2 and Level 3 software \begin{task} diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index f2465c2..1b768ba 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -3,6 +3,8 @@ \section{High-Redshift Galaxies}\label{sec:tasks:high_z} Summary \begin{tasklist}{HZ} + +\subsection{Optimizing Galaxy Photometry for High-Redshift Sources} \tasktitle{Optimizing Galaxy Photometry for High-Redshift Sources} \begin{task} \label{task:high_z:photometry} @@ -24,6 +26,7 @@ \section{High-Redshift Galaxies}\label{sec:tasks:high_z} } \end{task} +\subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} \tasktitle{High-Redshift Galaxies and Interlopers in LSST Simulations} \begin{task} \label{task:high_z:interlopers} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 3160598..297d555 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -3,6 +3,7 @@ \section{Low-Surface Brightness Science}\label{sec:tasks:lsb} Summary \begin{tasklist}{LSB} +\subsection{Techniques for Finding Low-Surface Brightness Tidal Features} \tasktitle{Techniques for Finding Low-Surface Brightness Tidal Features} \begin{task} \label{task:lsb:tidal_features} @@ -44,8 +45,7 @@ \section{Low-Surface Brightness Science}\label{sec:tasks:lsb} \end{task} - - +\subsection{Low-Surface Brightness Galaxies} \tasktitle{Low-Surface Brightness Galaxies} \begin{task} \label{task:lsb:galaxies} @@ -108,6 +108,7 @@ \section{Low-Surface Brightness Science}\label{sec:tasks:lsb} +\subsection{Probing the Faint Outskirts of Galaxies with LSST} \tasktitle{Probing the Faint Outskirts of Galaxies with LSST} \begin{task} \label{task:lsb:faint_outskirts} @@ -133,6 +134,7 @@ \section{Low-Surface Brightness Science}\label{sec:tasks:lsb} +\subsection{Low-Surface Brightness Intracluster Light} \tasktitle{Low-Surface Brightness Intracluster Light} \begin{task} \label{task:lsb:icl} diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index c5b2a01..67aa12c 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -4,6 +4,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} \begin{tasklist}{PZ} +\subsection{Impact of Filter Variations on Galaxy photo-z Precision} \tasktitle{Impact of Filter Variations on Galaxy photo-z Precision} \begin{task} \label{task:photo_z:filter_variations} @@ -20,6 +21,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} } \end{task} +\subsection{Photometric Reshifts in the LSST Deep Drilling Fields} \tasktitle{Photometric Reshifts in the LSST Deep Drilling Fields} \begin{task} \label{task:photo_z:ddf} @@ -37,6 +39,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} } \end{task} +\subsection{Multivariate Physical Properties of Galaxies from Photometric Redshifts} \tasktitle{Multivariate Physical Properties of Galaxies from Photometric Redshifts} \begin{task} \label{task:photo_z:physical_properties} @@ -56,6 +59,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} } \end{task} +\subsection{Identifying Spectroscopic Redshift Training Sets for LSST} \tasktitle{Identifying Spectroscopic Redshift Training Sets for LSST} \begin{task} \label{task:photo_z:specz_training_sets} @@ -72,6 +76,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} } \end{task} +\subsection{Develop Techniques to Identify Specific Sub-Populations of Galaxies} \tasktitle{Develop Techniques to Identify Specific Sub-Populations of Galaxies} \begin{task} \label{task:photo_z:subpops} @@ -99,6 +104,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} } \end{task} +\subsection{Simulations with Realistic Galaxy Colors and Physical Properties} \tasktitle{Simulations with Realistic Galaxy Colors and Physical Properties} \begin{task} \label{task:photo_z:color_simulations} @@ -114,11 +120,12 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} \item Compiling observable datasets that can be used as comparators for simulated datasets. \item Developing a set of metrics to compare simulations to the observational data. \item Use the metrics in deliverable B to create updated simulations with more realistic parameter distributions. -\item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc…). +\item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc.). \end{enumerate} } \end{task} +\subsection{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} \tasktitle{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} \begin{task} \label{task:photo_z:size_and_sb_priors} diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index 8031f30..fbbea34 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -14,10 +14,17 @@ %\input{task_lists/weak_lensing/weak_lensing.tex} \input{task_lists/agn/agn.tex} +\newpage \input{task_lists/clss/clss.tex} +\newpage \input{task_lists/ddf/ddf.tex} +\newpage \input{task_lists/galaxies/galaxies.tex} +\newpage \input{task_lists/high_z/high_z.tex} +\newpage \input{task_lists/lsb/lsb.tex} +\newpage \input{task_lists/photo_z/photo_z.tex} +\newpage \input{task_lists/tmc/tmc.tex} diff --git a/task_lists/task_lists.tex~ b/task_lists/task_lists.tex~ deleted file mode 100644 index 062ea83..0000000 --- a/task_lists/task_lists.tex~ +++ /dev/null @@ -1,22 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: task_lists -% First draft by - -\chapter[Task Lists by Science Area]{Task Lists by Science Area} -\label{ch:task_lists} - -\input{task_lists/chapter_intro.tex} - -\input{task_lists/black_holes/black_holes.tex} - -%\input{task_lists/galaxies/galaxies.tex} - -\input{task_lists/informatics/informatics.tex} - -\input{task_lists/lss/lss.tex} - -\input{task_lists/strong_lensing/strong_lensing.tex} - -\input{task_lists/weak_lensing/weak_lensing.tex} - diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index dd5850c..29dd976 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -3,6 +3,7 @@ \section{Theory and Mock Catalogs}\label{sec:tasks:tmc} Summary \begin{tasklist}{TMC} +\subsection{Image Simulations of Galaxies with Complex Morphologies} \tasktitle{Image Simulations of Galaxies with Complex Morphologies} \begin{task} \label{task:tmc:complex_morphology} @@ -23,6 +24,7 @@ \section{Theory and Mock Catalogs}\label{sec:tasks:tmc} \end{task} +\subsection{New Theoretical Models for the Galaxy Distribution} \tasktitle{New Theoretical Models for the Galaxy Distribution} \begin{task} \label{task:tmc:galaxy_distribution} @@ -41,6 +43,7 @@ \section{Theory and Mock Catalogs}\label{sec:tasks:tmc} } \end{task} +\subsection{Design of New Empirical Models for the Galaxy Distribution.} \tasktitle{Design of New Empirical Models for the Galaxy Distribution.} \begin{task} \label{task:section:title} @@ -57,6 +60,7 @@ \section{Theory and Mock Catalogs}\label{sec:tasks:tmc} \end{task} +\subsection{Estimating Uncertainties for Large-Scale Structure Statistics} \tasktitle{Estimating Uncertainties for Large-Scale Structure Statistics} \begin{task} \label{task:tmc:uncertainties} From 84d1519e3f2666e3c2ba301b61d32b8635e04a91 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 21 Mar 2017 03:10:15 -0700 Subject: [PATCH 13/64] Additional changes, reflects distributed copy on 03212017. --- abstract.tex | 12 ++- exgal_roadmap.pdf | Bin 240013 -> 241486 bytes journal_macros.tex | 105 ++++++++++++++++++++++ science_background/chapterintro.tex | 7 ++ science_background/science_background.tex | 5 +- structure.tex | 1 + task_lists/clss/clss.tex | 9 +- task_lists/galaxies/galaxies.tex | 5 ++ task_lists/high_z/high_z.tex | 10 ++- task_lists/lsb/lsb.tex | 13 ++- task_lists/photo_z/photo_z.tex | 28 +++--- task_lists/tmc/tmc.tex | 12 ++- 12 files changed, 182 insertions(+), 25 deletions(-) create mode 100644 journal_macros.tex create mode 100644 science_background/chapterintro.tex diff --git a/abstract.tex b/abstract.tex index d37ca9f..86a51ae 100644 --- a/abstract.tex +++ b/abstract.tex @@ -2,8 +2,12 @@ \vspace*{30mm} -{\bf Abstract.} - -TBD - +{\bf Abstract} +\vspace*{5mm} + +The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of +galaxies, dark matter, and black holes over cosmic time. The +LSST Galaxies Science Collaboration (LSST GSC) has identified a host of preparatory research tasks required +to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. +This {\it Extragalactic Roadmap} provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. 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TeX/BibTeX entries returned by +% the ADS abstract service. +% +% If you plan not to use this file to resolve the journal macros +% rather than the whole AAS TeX macro package, you should save the +% file as ``aas_macros.sty'' and then include it in your LaTeX paper +% by using a construct such as: +% \documentstyle[11pt,aas_macros]{article} +% +% For more information on the AASTeX and A&A packages, please see: +% http://journals.aas.org/authors/aastex.html +% ftp://ftp.edpsciences.org/pub/aa/readme.html +% For more information about ADS abstract server, please see: +% http://adsabs.harvard.edu/ads_abstracts.html +% + +% Abbreviations for journals. The object here is to provide authors +% with convenient shorthands for the most "popular" (often-cited) +% journals; the author can use these markup tags without being concerned +% about the exact form of the journal abbreviation, or its formatting. +% It is up to the keeper of the macros to make sure the macros expand +% to the proper text. If macro package writers agree to all use the +% same TeX command name, authors only have to remember one thing, and +% the style file will take care of editorial preferences. This also +% applies when a single journal decides to revamp its abbreviating +% scheme, as happened with the ApJ (Abt 1991). + +\def\refj@jnl#1{{\rm#1}} + +\def\aj{\refj@jnl{AJ}} % Astronomical Journal +\def\actaa{\refj@jnl{Acta Astron.}} % Acta Astronomica +\def\araa{\refj@jnl{ARA\&A}} % Annual Review of Astron and Astrophys +\def\apj{\refj@jnl{ApJ}} % Astrophysical Journal +\def\apjl{\refj@jnl{ApJ}} % Astrophysical Journal, Letters +\def\apjs{\refj@jnl{ApJS}} % Astrophysical Journal, Supplement +\def\ao{\refj@jnl{Appl.~Opt.}} % Applied Optics +\def\apss{\refj@jnl{Ap\&SS}} % Astrophysics and Space Science +\def\aap{\refj@jnl{A\&A}} % Astronomy and Astrophysics +\def\aapr{\refj@jnl{A\&A~Rev.}} % Astronomy and Astrophysics Reviews +\def\aaps{\refj@jnl{A\&AS}} % Astronomy and Astrophysics, Supplement +\def\azh{\refj@jnl{AZh}} % Astronomicheskii Zhurnal +\def\baas{\refj@jnl{BAAS}} % Bulletin of the AAS +\def\bac{\refj@jnl{Bull. astr. Inst. Czechosl.}} + % Bulletin of the Astronomical Institutes of Czechoslovakia +\def\caa{\refj@jnl{Chinese Astron. Astrophys.}} + % Chinese Astronomy and Astrophysics +\def\cjaa{\refj@jnl{Chinese J. Astron. Astrophys.}} + % Chinese Journal of Astronomy and Astrophysics +\def\icarus{\refj@jnl{Icarus}} % Icarus +\def\jcap{\refj@jnl{J. Cosmology Astropart. Phys.}} + % Journal of Cosmology and Astroparticle Physics +\def\jrasc{\refj@jnl{JRASC}} % Journal of the RAS of Canada +\def\memras{\refj@jnl{MmRAS}} % Memoirs of the RAS +\def\mnras{\refj@jnl{MNRAS}} % Monthly Notices of the RAS +\def\na{\refj@jnl{New A}} % New Astronomy +\def\nar{\refj@jnl{New A Rev.}} % New Astronomy Review +\def\pra{\refj@jnl{Phys.~Rev.~A}} % Physical Review A: General Physics +\def\prb{\refj@jnl{Phys.~Rev.~B}} % Physical Review B: Solid State +\def\prc{\refj@jnl{Phys.~Rev.~C}} % Physical Review C +\def\prd{\refj@jnl{Phys.~Rev.~D}} % Physical Review D +\def\pre{\refj@jnl{Phys.~Rev.~E}} % Physical Review E +\def\prl{\refj@jnl{Phys.~Rev.~Lett.}} % Physical Review Letters +\def\pasa{\refj@jnl{PASA}} % Publications of the Astron. Soc. of Australia +\def\pasp{\refj@jnl{PASP}} % Publications of the ASP +\def\pasj{\refj@jnl{PASJ}} % Publications of the ASJ +\def\rmxaa{\refj@jnl{Rev. Mexicana Astron. Astrofis.}}% + % Revista Mexicana de Astronomia y Astrofisica +\def\qjras{\refj@jnl{QJRAS}} % Quarterly Journal of the RAS +\def\skytel{\refj@jnl{S\&T}} % Sky and Telescope +\def\solphys{\refj@jnl{Sol.~Phys.}} % Solar Physics +\def\sovast{\refj@jnl{Soviet~Ast.}} % Soviet Astronomy +\def\ssr{\refj@jnl{Space~Sci.~Rev.}} % Space Science Reviews +\def\zap{\refj@jnl{ZAp}} % Zeitschrift fuer Astrophysik +\def\nat{\refj@jnl{Nature}} % Nature +\def\iaucirc{\refj@jnl{IAU~Circ.}} % IAU Cirulars +\def\aplett{\refj@jnl{Astrophys.~Lett.}} % Astrophysics Letters +\def\apspr{\refj@jnl{Astrophys.~Space~Phys.~Res.}} + % Astrophysics Space Physics Research +\def\bain{\refj@jnl{Bull.~Astron.~Inst.~Netherlands}} + % Bulletin Astronomical Institute of the Netherlands +\def\fcp{\refj@jnl{Fund.~Cosmic~Phys.}} % Fundamental Cosmic Physics +\def\gca{\refj@jnl{Geochim.~Cosmochim.~Acta}} % Geochimica Cosmochimica Acta +\def\grl{\refj@jnl{Geophys.~Res.~Lett.}} % Geophysics Research Letters +\def\jcp{\refj@jnl{J.~Chem.~Phys.}} % Journal of Chemical Physics +\def\jgr{\refj@jnl{J.~Geophys.~Res.}} % Journal of Geophysics Research +\def\jqsrt{\refj@jnl{J.~Quant.~Spec.~Radiat.~Transf.}} + % Journal of Quantitiative Spectroscopy and Radiative Transfer +\def\memsai{\refj@jnl{Mem.~Soc.~Astron.~Italiana}} + % Mem. Societa Astronomica Italiana +\def\nphysa{\refj@jnl{Nucl.~Phys.~A}} % Nuclear Physics A +\def\physrep{\refj@jnl{Phys.~Rep.}} % Physics Reports +\def\physscr{\refj@jnl{Phys.~Scr}} % Physica Scripta +\def\planss{\refj@jnl{Planet.~Space~Sci.}} % Planetary Space Science +\def\procspie{\refj@jnl{Proc.~SPIE}} % Proceedings of the SPIE + +\let\astap=\aap +\let\apjlett=\apjl +\let\apjsupp=\apjs +\let\applopt=\ao diff --git a/science_background/chapterintro.tex b/science_background/chapterintro.tex new file mode 100644 index 0000000..ca6352f --- /dev/null +++ b/science_background/chapterintro.tex @@ -0,0 +1,7 @@ +% LSST Extragalactic Roadmap +% Chapter: science_background +% First draft by + +\section{Overview}\label{sec:sci:intro} + +TBD diff --git a/science_background/science_background.tex b/science_background/science_background.tex index 87d8304..bd4f0e0 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -6,9 +6,8 @@ \chapter[Science Background]{Science Background} \label{ch:science_background} -TBD - -\input{science_background/chapterintro.tex} +%TBD +%\input{science_background/chapterintro.tex} \input{science_background/galaxies/galaxies.tex} diff --git a/structure.tex b/structure.tex index 6738e01..d0bba70 100644 --- a/structure.tex +++ b/structure.tex @@ -5,6 +5,7 @@ +\usepackage{verbatim} \usepackage{enumitem} % Customize lists \setlist{nolistsep} % Reduce spacing between bullet points and numbered lists \usepackage{booktabs} % Required for nicer horizontal rules in tables diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index c1facfb..620ba9d 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -1,7 +1,12 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} -Summary +The cosmological process of galaxy formation inextricably links +the together, environment and large scale structure with the detailed +properties of galaxy populations. The extent of this connection +ranges from the scales of superclusters down to small groups. The +following preparatory science tasks focus on this critical connection +between galaxy formation, clusters, and large scale structure. \begin{tasklist}{CLSS} \subsection{Cluster/LSS Sample Emulator} @@ -104,8 +109,6 @@ \subsection{Identifying and Characterizing Clusters} } \end{task} - - \subsection{Developing and Optimizing Measurements of Galaxy Environment} \tasktitle{Developing and Optimizing Measurements of Galaxy Environment} \begin{task} diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 0ed6cc8..de49c68 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -335,6 +335,9 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} } \end{task} + +\begin{comment} + \subsection{Software Integration} \tasktitle{Software Integration} % Level 2 and Level 3 software @@ -478,4 +481,6 @@ \subsection{Databases and Data Services} \label{sec:tasks:gal:databases} \activities{} \end{task} +\end{comment} + \end{tasklist} diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index 1b768ba..214509a 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -1,6 +1,14 @@ \section{High-Redshift Galaxies}\label{sec:tasks:high_z} -Summary +Observations of distant galaxies provide critical information +into the efficiency of the galaxy formation process, the end +of the reionization era, the early enrichment of the intergalactic +medium, and the initial conditions for the formation of modern +galaxies at later times. Through its wide area and sensitivity +in $zy$ LSST will probe galaxies out to $z\sim7$, and will probe +yet further in conjuction with future wide-area infrared surveys. +The following science tasks address outstanding preparatory work +for maximizing high-redshift science with LSST. \begin{tasklist}{HZ} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 297d555..b75b9c6 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -1,6 +1,13 @@ \section{Low-Surface Brightness Science}\label{sec:tasks:lsb} -Summary +The exquisite data quality of LSST will enable a new regime in +low-surface brightness (LSB) science over large areas of the sky. The capability +to conduct unparalleled LSB science with LSST will uncover new +evidence for and measures of the cosmic merger rate, reveal the +signature of hierarchical structure formation in extragalactic stellar +halos, and probe the LSB outskirts around other galaxies. The following +science tasks provide an enumeration of preparatory research tasks for +leveraging fully the LSST dataset for LSB science. \begin{tasklist}{LSB} \subsection{Techniques for Finding Low-Surface Brightness Tidal Features} @@ -126,8 +133,8 @@ \subsection{Probing the Faint Outskirts of Galaxies with LSST} } \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item AAA -\item BBB +\item Information on the stability and spatial constancy of the LSST PSF. +\item Improved control over systematics for LSB science, and other fields including weak lensing. \end{enumerate} } \end{task} diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index 67aa12c..2166542 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -1,7 +1,15 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} -Summary - +For a photometric survey like LSST, the ability to measure +vast distances to galaxy samples, understand the time evolution +and spatial clustering of galaxy populations, surmise the +stellar mass, age, and metallicity of objects, and to identify +unusual objects at various cosmic epochs relies heavily on +methodologies for constructing photometric redshifts from the data. +The following important preparatory science tasks address both the +systematic uncertainties on photometric redshifts associated +with the LSST observatory and with the requisite +stellar population synthesis models. \begin{tasklist}{PZ} \subsection{Impact of Filter Variations on Galaxy photo-z Precision} @@ -12,11 +20,11 @@ \subsection{Impact of Filter Variations on Galaxy photo-z Precision} For accurate photometric redshifts, well calibrated photometry is essential. Variations in the telescope system, particularly the broad-band ugrizy filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of local environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane. Such corrections will be SED dependent, and may leave residuals, particularly for specific populations with unusual SEDs. Tests of the amplitude of these residuals, and the impact on photo-z as a whole, and for particular object classes, is an important consideration. Beyond this, if the variations turn out to be very well calibrated, they could potentially be used to further improve, rather than degrade, photo-z performance. The variations in filter response can offer up additional a small amount of extra information on the object SED, given the slight variation in effective filter wavelength, particularly for objects with strong narrow features, i.e. emission lines. Tests of how much information is gained can inform whether or not the extra computational effort used in computing photo-z’s from many slightly different filters as opposed to measurements corrected to the six fiducial filters of the survey. } \activities{ -XXX} +Tests of the SED-dependent residuals in photometric redshifts induced by photometric calibration systematics.} \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item AAA -\item BBB +\item Improved photometric calibration for LSST across all pass bands. +\item Identification of SED classes where photometric redshift failures are prominent. \end{enumerate} } \end{task} @@ -29,12 +37,12 @@ \subsection{Photometric Reshifts in the LSST Deep Drilling Fields} The LSST Deep Drilling Fields present different challenges than the main survey, including more confusion between sources, and the ability to use the best subsets of the images due to their being many repeat observations. These properties allow investigations of galaxies of brightness close to the noise in the main survey at higher signal to noise. } \activities{ -Assessing robustness of photo-zs with spectroscopic surveys will be difficult at the faintest fluxes, relationship to clustering redshifts important. +Assessing robustness of photo-zs with spectroscopic surveys will be difficult at the faintest fluxes, but the relationship to clustering redshifts is critically important. } \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item AAA -\item BBB +\item {\bf TBD} +\item {\bf TBD} \end{enumerate} } \end{task} @@ -70,8 +78,8 @@ \subsection{Identifying Spectroscopic Redshift Training Sets for LSST} } \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item AAA -\item BBB +\item {\bf TBD} +\item {\bf TBD} \end{enumerate} } \end{task} diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index 29dd976..bd4ba11 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -1,6 +1,16 @@ \section{Theory and Mock Catalogs}\label{sec:tasks:tmc} -Summary +A critical challenge for interpreting the vast LSST dataset +in the context of a cosmological model for galaxy formation +is the development of theory, both in the practical applications +of realistic simulations and the engineering of new physical +models for the important processes that govern the observable +properties of galaxies. The following preparatory science tasks +for LSST-related theoretical efforts range from understanding the +detail properties of galaxies that LSST will uncover to predicting +the large-scale properties of galaxy populations that LSST will probe +on unprecedented scales. + \begin{tasklist}{TMC} \subsection{Image Simulations of Galaxies with Complex Morphologies} From 42860b539709c423fa121cf1de0cb852292ca096 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 21 Mar 2017 08:51:45 -0700 Subject: [PATCH 14/64] Adding Graham Smith to author list (sorry Graham)! --- authorlist.tex | 3 ++- exgal_roadmap.pdf | Bin 241486 -> 241538 bytes 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/authorlist.tex b/authorlist.tex index 723b2ad..577722a 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -1,4 +1,4 @@ -Robertson, Brant$^{1}$, Banerji, M.$^{2}$, Cooper, Michael$^{3}$, Davies, R.$^{4}$, Ferguson, Henry C.$^{5}$, Kaviraj, S.$^{6}$, Lintott, C.$^{4}$, Lotz, J.$^{5}$, Newman, J.$^{7}$, Norman, D.$^{8}$, Padilla, N.$^{9}$, Schmidt, S.$^{10}$, Verma, A.$^{4}$, Working Group Participants, Collaboration Members +Robertson, Brant$^{1}$, Banerji, M.$^{2}$, Cooper, Michael$^{3}$, Davies, R.$^{4}$, Ferguson, Henry C.$^{5}$, Kaviraj, S.$^{6}$, Lintott, C.$^{4}$, Lotz, J.$^{5}$, Newman, J.$^{7}$, Norman, D.$^{8}$, Padilla, N.$^{9}$, Schmidt, S.$^{10}$, Smith, G.~P.$^{11}$,Verma, A.$^{4}$, Working Group Participants, Collaboration Members \vspace*{5mm} @@ -13,4 +13,5 @@ $^{8}$National Optical Astronomical Observatory, $^{9}$Pontifica Universidad Catolica de Chile, $^{10}$University of California, Davis, +$^{11}$University of Birmingham, } diff --git a/exgal_roadmap.pdf b/exgal_roadmap.pdf index 2f9acb413291dbcd2256ff2c3cf7efa3084147cc..44f4c254551d5473a2c672414fc32cb5150ba742 100644 GIT binary patch delta 1893 zcmV-r2b%cK-VTD_4v-@QF)=lhVIU}ft(Q%6+cpq}@BS4$k~0>H?~mSMJ8_c6vBy^1 zL)!x^(Gn7g^nj4!%npBi z4sH~m7Jiu#k>>TE@9n!`rf{0i@@iB*=e2M$;1m(6L4Y7GTC>-7W?x)howtjwtpD1M zZfpp-&p1xwCtHl$!Ntsu;-vQ_*#EULt{Kwc`T+c9CK`YH61<&cA_bAr8uq@lFH6{lZai{iqcLc>L(fchr zGb++=b6XtJ5OOCQ)JYnp-`KzEwXYDB-J_{bv42-rH9K~*nO!ONiV!3P?}(UFGVEbA zox5>3m|YTKMY{zC_bF(^rS5-In7c5I<7>2bjgWLt$h7HtL&$Mre>5g@*pismjKI;` zPU<&(ieOdZqtdu9et%{fr=|buib-_Qmy74_272fK?ip%#wJwRUqmQMx!IecUiuoLh zebu33s_ve3Yk)D}4WLsJyj|gyNeu8%*#eRlP?Fd>e=pp!E?79NT!?=)s(gwJcIKW+ zU$|9jJpiDM-~8goc@GMK;z@Mf3Dy$yD3D7#fAnrVsZnAd-(eFX?Nc-iVcFGV|G(oO z{L&S9J-OFsY7is5%fOFfxP1YYjHz_oWMkcS7+iaBLK4l9)FgqXjTEQJaQ-v0ko`2# zLQSP42NMD@VOkTShpT@pOBf_CoP;gihi5x#wuHmQ$?(m^30^TM4lXZN-#-*paA6Vl z$0`a@X`poP(8*WmC|qN(&zg#p1!$7KsX|t>a*>urIp2J^eXMf7w4wBS&*^&S;pQ$0O9b2~G>(3lem~Y^ zlwqXcX$$SHDXT?re`8EX_UEE8w&ND>63Aw5HD#Q~w^KKJHBp)2NK>+nyJ~KGc{zr- z!*ywkcYnztyCqYHz*TkWs)KRl3VuaFNQg!?z`WB3x47y%5^3v>e7*KvI6sFzHMR5e z{lCb%KT9Aiv~E2ViIx3To2@pz%lgr@9a0jDD#b+gO1vGO{R`i6V2P6<3loEh1c!+P z0f&hM0=J0-12mi{I5jacFfA}QConK4DGD!5Z)8MabY&nYL^?7sF*h(XGBGeXH8CLpL)EOlVBhzeCTtozX;A4G@f`F)nF&aD3%0d%kVYF3)7K8+Ij21>M=xmIQ zF>181F*Z_Im?*|V_y4!~GT-dX?7jD#F*Ez;nfV|LW?@T5E=JS>e=kex`D=jiU|BDe zi&BF`7A*U>ay8U!f5M05O)}>%A#&2XD9s~sVMU|rsG}AT`LNPCx>$ueRoa}lB#7SB9sHMNu|fhBv@TTYb0hB6PNwhGwrTXig_a-Lrao4l%$Dk2Iy zH80g`Rm0BrNo$E1Z0e^}AEyp>ystz)YjY zw@?oghk&OuDmh9V0p>F|>=-c&ydIE_5XXTJH>D?tQQ*s0={PY4EOctT4(}u}0sOk4 z95>2YniGb=gNMp-g`5X3ctx5;aD|*taB*A?Q9*EVR9r5>opJd@0X+YSdPDH)Zz~GJ z>$#|?5Z+iwQ4zcwx&p2k-fXU-2)xJ76_vnS(2a1V2qf<-DnsC0g(9wtYa@97T%2e} fVESJAJsx$~f4N6{8J8um10V@FI0_{tMNdWwvCeiK delta 1843 zcmV-32h8|_-ww{+4v-@PFgBObBLXRZtyfKV+Bg*5=T~@XpA$6t{+L~pv}rp{lanwr zifBih$0t{nF=$Q=|S$g-rtE=|}P9_OXuFo!pXTQ9YCLtIZY)CSE zN(3cHV3{Z)k)bRZj+4JqlKnIMc!uMu^>?$Ba-_6smJXO=h!~X&s6<+-cI_vT&JBND z1UHJmmVT8Hk>>Ts_jYWUDV*lByc(5@yarANoFYOs01(7Q8}{1H?6b?O^LEjd^V$eE@kg6NA5f4&F{OkpjqQL-xM3$g{bTvO?^uIySl2`v76288nG9IASrkU#GC^1Fq+QY zI2?7CL|AqAnczMIjkwf32!DTMgpf1`t>VC&UNafk3h}dM`ZLowE&W$lOj=JLq^i$6yM?^a)B z639qW+0rKM@s=dEwciW3s*4FuD;Hw@D4!w;J9AH^FWg$N2ViL9JHLPYao)p)Kw%?| zej5n-Dk7J5{^;F!Qd5aNc8{A7X&<72++`P!{r`!7@GDp3_2k~1sX>hJE(iW94!6&M zk};Kz8?)3cfx(poCnV7vNlg-Hs7P^|4Cnu)EMz~M7@=mRB!>_JF=5&eqK8)(mN2k1 z*mMW?VPQwjmT@M zEBM%sThf=nZ06Qe#?h&lQ#X6jr3`LOs&;9Y?z-z7k5$i|O_K}iU-6$ri7whft>|e+9EeV&=-T@PX zx&(*11ObP-1Om6Z1OqgjC^IlIGd3+SHzzPKCn*XqO>bmGVRU66C`39kFflhUGcqwS zGcYkTHn$d`19=NkFg7qVI5{G zEO<+~Dr$%b!gAg!S3}Jqe1BL$Cv$!tk(<$X(gGqM7Hw5W9kqxkgvF+ntEYyEVpw8O zZBZfuOLnWIl32}LDNzDTWuLT~8Y9YJy%F`UBI2-->;tK-95yedsDu(_|& zW}*r9N`L7psI5c`?9DHgv=J%T$4Al*q8+xFP>05M5*uLOZmXn=*a-XiRJw`ihW)LS zZXq@Up*-nUq6dinmTo7u0W}30-$?BvdV%HzmGl!kfRr!YMeGE6vL`)2>;?wfrF)4z zK>E3Kkk|)|>rkA&#(yv|1YBBD$$nx4xc**xkT?L$#HDHC5OBXsdW1L(%<3Na$B3iA zlRp~YL_I+q2j;J-

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z7b%+vEZg%kRe~}E_io)vFZg;LIqX@b+JtuULIAS+OZT}t(sX@$cvFgH0Na7;xn?2zvyxCM?{U_Pn&Bz7LamY$wq`-UpT_> z8NlX})E&s8hWrvs!GYumQA5UOi*7Cog;XD-IE1d8;AhFWA-H-xx0%7(=AM>pG2!th=Hoe$q_ s70@o>^Xvb_#CHF=IT%~RxVRcQyLvjCnZq!%GO}}W!jO@PDTu@TKc#h9(f|Me From c1d290ec2654aa578cf5039d7435e0d3e6c93a44 Mon Sep 17 00:00:00 2001 From: Sam Schmidt Date: Tue, 21 Mar 2017 16:46:41 -0700 Subject: [PATCH 17/64] added pz section --- 2016/science_background/galaxies/galaxies.tex | 875 +++++++++--------- 1 file changed, 441 insertions(+), 434 deletions(-) diff --git a/2016/science_background/galaxies/galaxies.tex b/2016/science_background/galaxies/galaxies.tex index 02b94b5..f1ec658 100644 --- a/2016/science_background/galaxies/galaxies.tex +++ b/2016/science_background/galaxies/galaxies.tex @@ -1,434 +1,441 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: galaxies -% First draft by - -\section{Science Background: Galaxies} -\label{sec:sci:gal:bkgnd} - -Galaxies represent fundamental astronomical objects -outside our own Milky Way. -The large luminosities of galaxies enable their -detection to extreme distances, providing abundant -and far-reaching probes into the depths of the universe. -At each epoch in cosmological history, the color -and brightness distributions of the galaxy population -reveal how stellar populations form with time and -as a function of galaxy mass. The progressive mix of -disk and spheroidal morphological components of -galaxies communicate the relative importance of -energy dissipation and collisionless processes -for their formation. -Correlations between internal galaxy properties and -cosmic environments indicate -the ways the universe nurtures galaxies as they form. -The evolution of the -detailed characteristics of galaxies over cosmic time -reflects how fundamental astrophysics -operates to generate the rich variety of -astronomical structures observed today. - -Study of the astrophysics of galaxy formation represents -a vital science of its own, but the ready -observability of galaxies critically enables a host of -astronomical experiments in other fields. -Galaxies act as the semaphores of the -universe, encoding information about -the development of large scale -structures and the mass-energy budget of the -universe in their spatial distribution. The mass distribution -and clustering of galaxies reflect essential -properties of dark matter, including potential -constraints on the velocity and mass of particle candidates. -Galaxies famously host supermassive black holes, -and observations of active galactic nuclei provide -a window into the high-energy astrophysics of black hole -accretion processes. The porous interface between the -astrophysics of black holes, galaxies, and -dark matter structures allows for astronomers to -achieve gains in each field using the same datasets. - -The Large Synoptic Survey Telescope (LSST) will provide a -digital image of the southern sky in six bands ($ugrizy$). -The area ($\sim18,000~\mathrm{deg}^2$) and depth -($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of -the survey will enable research of such breadth -that LSST may influence essentially all extragalactic -science programs that rely primarily on photometric data. -For studies of galaxies, LSST provide both an unequaled -catalogue of billions of extragalactic sources and high-quality -multiband imaging of individual objects. This section of -the {\it Extragalactic Roadmap} presents scientific -background for studies of these galaxies with LSST to provide a -context for considering how the astronomical community can -best leverage the catalogue and imaging datasets and for -identifying any required preparatory science tasks. - -LSST will begin science operations during the next decade, -more than twenty years after the start of the Sloan -Digital Sky Survey \citep{york2000a} and subsequent precursor surveys -including PanSTARRS \citep{kaiser2010a}, the Subaru -survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark -Energy Survey \citep{flaugher2005a}. Relative to these prior -efforts, extragalactic science breakthroughs -generated by LSST will likely benefit from its increased area, source -counts, and statistical samples, the constraining power of the -six-band imaging, and the survey depth and image quality. The following -discussion of LSST efforts focusing on the astrophysics of galaxies -will highlight how these features of the survey enable new science -programs. - - - -\subsection{Star Formation and Stellar Populations in Galaxies} -\label{sec:sci:gal:bkgnd:stars} - -Light emitted by stellar populations will -provide all the direct measurements made by -LSST. This information will be filtered through -the six passbands utilized by the survey -($ugrizy$), providing constraints on the -rest-frame ultraviolet SEDs of galaxies to -redshift $z\sim6$ and a probe of rest-frame -optical spectral breaks to $z\sim1.5$. By -using stellar population synthesis modeling, -these measures of galaxy SEDS will enable -estimates of the redshifts, star formation rates, -stellar masses, dust content, and -population ages for potentially -billions of galaxies. In the context of previous -extragalactic surveys, LSST -will enable new advances in our understanding -of stellar populations in galaxies by contributing -previously unachievable statistical power and an -areal coverage that samples the rarest cosmic -environments. - -A variety of ground- and space-based observations -have constrained the -star formation history of the universe over the -redshift range that LSST will likely probe -\citep[for a recent review, see][]{madau2014a}. -The statistical power of LSST will improve our -knowledge of the evolving UV luminosity function, -luminosity density, and cosmic -star formation rate. The LSST observations can -constrain how the astrophysics of gas -cooling within dark matter halos, the efficiency -of molecular cloud formation and the star formation -within them, and -regulatory mechanisms like supernova and radiative -heating give rise to these statistical features -of the galaxy population. While measurement of -the evolving UV luminosity function can -help quantify the role of these -astrophysical processes, the ability of LSST -to probe vastly different cosmic environments -will also allow for the robust quantification of any -changes in the UV luminosity function with -environmental density, and an examination of -connections between environment and the fueling -of star formation. - -Optical observations teach us about -the established stellar content of galaxies. -For stellar populations older than $\sim100$ million -years, optical observations provide -sensitivity to the spectral breaks near a -wavelength of $\lambda\approx4000\AA$ in the -rest-frame related to absorption in the -atmospheres of mature stars. -Such observations help constrain -the amount of stellar mass in galaxies. For -passive galaxies that lack vigorous star formation, -these optical observations reveal -the well-defined ``red sequence'' of -galaxies in the color-magnitude plane -that traces the succession of -galaxies from recently-merged spheroids -to the most massive systems at the -centers of galaxy clusters. For blue, -star-forming -galaxies, optical light can help -quantify the relative contribution of -evolved stars to total galaxy luminosity, -and indeed has -led to the identification of a well-defined -locus of galaxies in the parameter space of -star formation rate and stellar mass -\citep[e.g.,][]{noeske2007a}. This -relation, often called the ``star-forming -main sequence'' of galaxies, indicates that -galaxies of the same stellar mass typically -sustain a similar star-formation rate. -Determining the -physical or possibly statistical -origin of the relation remains an active -line of inquiry, guided by recently improved -data from Hubble Space Telescope over the -$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared -Deep Extragalactic Survey -\citep{grogin2011a,koekemoer2011a}. While -LSST will be comparably limited in redshift -selection, its $~30,000$ times larger area -will enable a much fuller sampling of the -star formation--stellar mass plane, allowing -for a characterization of the distribution -of galaxies that lie off the main sequence -that can help discriminate between phenomenological -explanations of the sequence. - -\subsection{Galaxies as Cosmic Structures} -\label{sec:sci:gal:bkgnd:structures} - -The structural properties of galaxies arise from -an intricate combination of important astrophysical -processes. The gaseous disks of galaxies require -substantial energy dissipation while depositing -angular momentum into a rotating structure. These -gaseous disks form stars with a -surface density that declines exponentially with -galactic radius, populating stellar orbits that -differentially rotate about the galactic center and -somehow organize into spiral features. -Many disk galaxies contain (pseduo-)bulges that form through -a combination of violent relaxation and orbital dynamics. -These disk galaxy features contrast with systems where -spheroidal stellar distributions dominate the galactic -structure. Massive ellipticals form through galaxy -mergers and accretions, and manage to forge a regular -sequence of surface density, size, and stellar velocity -dispersion from the chaos of strong gravitational -encounters. Since these astrophysical -processes may operate with great -variety as a function of galaxy mass and -cosmic environment, LSST will revolutionize studies -of evolving galaxy morphologies by providing enormous -samples with deep imaging of exquisite quality. - -The huge sample of galaxies provided by LSST will -provide a definitive view of how the sizes and -structural parameters of disk and spheroidal systems -vary with color, stellar mass, and luminosity. -Morphological studies will employ at least two -complementary techniques for quantifying the -structural properties of galaxies. Bayesian -methods can yield multi-component -parameterized models for all the galaxies -in the LSST sample, including the quantified -contribution of bulge, disk, and -spheroid structures to the observed galaxy -surface brightness profiles. The parameterized -models will supplement non-parametric measures -of the light distribution including the -Gini and M20 metrics that quantify the surface -brightness uniformity and spatial moment of -dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. -Collectively, these morphological measures provided -by analyzing the LSST imaging data will enable -a consummate determination of the relation between -structural properties and other features of -galaxies over a range of galaxy mass and luminosity -previously unattainable. - -While the size of the LSST sample supplies the -statistical power for definitive morphological studies, -the sample size also enables the identification of rare -objects. This capability will benefit our efforts for -connecting the distribution of galaxy morphologies to their -evolutionary origin during the structure formation process, -including the formation of disk galaxies. -The emergence of ordered disk galaxies remains a hallmark -event in cosmic history, with so-called ``grand design'' -spirals like the Milky Way forming dynamically cold, thin -disks in the last $\sim10$ Gyr. Before thin disks emerged, -rotating systems featured ``clumpy'' mass distributions with -density enhancements -that may originate from large scale gravitational instability. -Whether the ground-based LSST can effectively probe -the exact timing and duration of the transition from -clumpy to well-ordered disks remains -unknown, but LSST can undoubtedly contribute studying the -variation in forming disk structures at the present day. -Unusual objects, such as the UV luminous local galaxies identified -by \citet{heckman2005a} that display physical features analogous to -Lyman break galaxies at higher redshifts, may provide a -means to study the formation of disks in the present day -under rare conditions only well-probed by the sheer size -of the LSST survey. - -Similarly, the characterizing the extremes of the -massive spheroid population can critically inform -theoretical models for their formation. For instance, -the most massive galaxies at the centers of galaxy clusters -contain vast numbers of stars within enormous stellar -envelopes. The definitive LSST sample can capture enough -of the most massive, rare clusters to quantify the -spatial extent of these galaxies at -low surface brightnesses, where the bound stellar -structures blend with the intracluster light of -their hosts. Another research area the LSST data -can help address regards the central densities of local -ellipticals that have seemingly decreased compared with -field ellipticals at higher redshifts. The transformation -of these dense, early ellipticals to the spheroids in the -present day may involve galaxy mergers and environmental -effects, two astrophysical processes that LSST can characterize -through unparalleled statistics and environmental probes. -By measuring the -surface brightness profiles of billions of -ellipticals LSST can determine whether any such dense -early ellipticals survive to the present day, whatever -their rarity. - -Beyond the statistical advances enabled by LSST and the -wide variation in environments probed by a survey -of half the sky, the image quality of LSST will permit -studies of galaxy structures in the very low surface -brightness regime. Observational -measures of the outer most regions of thin disks can constrain -how such disks ``end'', how dynamical effects might truncate -disks, and whether some disks smoothly transition into stellar -halos. LSST will provide such measures and help quantify the -relative importance the physical effects that influence the -low surface brightness regions in disks. Other galaxies -have low surface brightnesses throughout their stellar -structures, and the image quality and sensitivity -of LSST will enable the most complete census -of low surface brightness galaxies to date. LSST will provide -the best available constraints on the extremes of disk -surface brightness, which relates to the extremes of -star formation in low surface density environments. - -The ability of LSST to probe low surface brightnesses -also allows for characterization of stellar halos that -surround nearby galaxies. Structures in stellar halos, -from streams to density inhomogeneities, originate -from the hierarchical formation process and their -morphology provides clues to the formation history -on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. -Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} -have already -demonstrated that stellar halo structures display interesting -variety -\citep[e.g.,][]{van_dokkum2014a}. -LSST, with its unrivaled entendue, can help build a statistical -sample of stellar halos and cross-reference their morphologies -with the observed properties of their central galaxies. Such -studies may determine whether the formation histories reflected -in the structures of halos also influence galaxy colors or -morphological type. The -examination of stellar halos around external galaxies may -also result in the identification of small mass satellites -whose sizes, luminosities, and abundances can constrain -models of the galaxy formation process on the extreme -low-mass end of the mass function. - -\subsection{Probing the Extremes of Galaxy Formation} -\label{sec:sci:gal:bkgnd:rare} - -The deep, multiband imaging LSST provides over an enormous -area will enable the search for galaxies that form in the -rarest environments, under the most unusual conditions, -and at very early times. By probing the extremes of -galaxy formation, the LSST data will push our theoretical -understanding of the structure formation process. - -The rarest, most massive early galaxies may form in -conjunction with the supermassive black holes that -power distant quasars. LSST can use the same -types of color-color selections to identify extremely -luminosity galaxies out to redshift $z\sim6$, and -monitor whether the stellar mass build-up in these -galaxies tracks the accretion history of the most -massive supermassive black holes. If stellar mass -builds proportionally to black hole mass in quasars, -then very rare luminous star forming galaxies at -early times may immediately proceed the formation -of bright quasars. LSST has all the requisite -survey properties (area, mutliband imaging, and -depth) to investigate this long-standing problem. - -The creation of LSST Deep Drilling fields will -enable a measurement of the very bright end -of the high-redshift galaxy luminosity function. -Independent determinations of the distribution of -galaxy luminosities at $z\sim6$ show substantial -variations at the bright end. The origin of -the discrepancies between various groups remains -unclear, but the substantial cosmic variance expected -for the limited volumes probed and the intrinsic -rarity of the bright objects may conspire to -introduce large potential differences between -the abundance of massive galaxies in different -areas of the sky. Reducing this uncertainty requires -deep imaging over a wide area, and the LSST Deep Drilling -fields satisfy this need by achieving sensitivities -beyond the rest of the survey. - -Lastly, the spatial rarity of extreme objects discovered -in the wide LSST area may reflect an intrinsically -small volumetric density of objects or the short duration -of an event that gives rise to the observed properties of the -rare objects. Mergers represent a critical class -of short-lived epochs in the formation histories of -individual galaxies. Current determinations of the evolving numbers -of close galaxy pairs or morphological indicators of -mergers provide varying estimates for the -redshift dependence of the galaxy merger rate -\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. -The identification of merging -galaxy pairs as a function of separation, merger -mass ratio, and environment in the LSST data will enable -a full accounting of how galaxy mergers influence -the observed properties of galaxies as a function of -cosmic time. - -\subsection{Science Book} -\label{sec:sci:gal:bkgnd:scibook} - -The contents of the -Galaxies Chapter 9 of the Science Book (\citealt{LSSTSciBook}). - -\begin{enumerate} -\item Measurements, Detection, Photometry, Morphology -\item Demographics of Galaxy Populations -\begin{itemize} -\item Passively evolving galaxies -\item High-redshift star forming galaxies -\item Dwarf galaxies -\item Mergers and interactions -\end{itemize} -\item Distribution Functions and Scaling Relations -\begin{itemize} -\item Luminosity and size evolution -\item Relations between observables -\item Quantifying the Biases and Uncertainties -\end{itemize} -\item Galaxies in their Dark-Matter Context -\begin{itemize} -\item Measuring Galaxy Environments with LSST -\item The Galaxy-Halo Connection -\item Clusters and Cluster Galaxy Evolution -\item Probing Galaxy Evolution with Clustering Measurements -\item Measuring Angular Correlations with LSST, Cross-correlations -\end{itemize} -\item Galaxies at Extremely Low Surface Brightness -\begin{itemize} -\item Spiral Galaxies with LSB Disks -\item Dwarf Galaxies -\item Tidal Tails and Streams -\item Intracluster Light -\end{itemize} -\item Wide Area, Multiband Searches for High-Redshift Galaxies -\item Deep Drilling Fields -\item Galaxy Mergers and Merger Rates -\item Special Populations of Galaxies -\item Public Involvement -\end{enumerate} - - - - - + +% LSST Extragalactic Roadmap +% Chapter: science_background +% Section: galaxies +% First draft by + +\section{Science Background: Galaxies} +\label{sec:sci:gal:bkgnd} + +Galaxies represent fundamental astronomical objects +outside our own Milky Way. +The large luminosities of galaxies enable their +detection to extreme distances, providing abundant +and far-reaching probes into the depths of the universe. +At each epoch in cosmological history, the color +and brightness distributions of the galaxy population +reveal how stellar populations form with time and +as a function of galaxy mass. The progressive mix of +disk and spheroidal morphological components of +galaxies communicate the relative importance of +energy dissipation and collisionless processes +for their formation. +Correlations between internal galaxy properties and +cosmic environments indicate +the ways the universe nurtures galaxies as they form. +The evolution of the +detailed characteristics of galaxies over cosmic time +reflects how fundamental astrophysics +operates to generate the rich variety of +astronomical structures observed today. + +Study of the astrophysics of galaxy formation represents +a vital science of its own, but the ready +observability of galaxies critically enables a host of +astronomical experiments in other fields. +Galaxies act as the semaphores of the +universe, encoding information about +the development of large scale +structures and the mass-energy budget of the +universe in their spatial distribution. The mass distribution +and clustering of galaxies reflect essential +properties of dark matter, including potential +constraints on the velocity and mass of particle candidates. +Galaxies famously host supermassive black holes, +and observations of active galactic nuclei provide +a window into the high-energy astrophysics of black hole +accretion processes. The porous interface between the +astrophysics of black holes, galaxies, and +dark matter structures allows for astronomers to +achieve gains in each field using the same datasets. + +The Large Synoptic Survey Telescope (LSST) will provide a +digital image of the southern sky in six bands ($ugrizy$). +The area ($\sim18,000~\mathrm{deg}^2$) and depth +($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of +the survey will enable research of such breadth +that LSST may influence essentially all extragalactic +science programs that rely primarily on photometric data. +For studies of galaxies, LSST provide both an unequaled +catalogue of billions of extragalactic sources and high-quality +multiband imaging of individual objects. This section of +the {\it Extragalactic Roadmap} presents scientific +background for studies of these galaxies with LSST to provide a +context for considering how the astronomical community can +best leverage the catalogue and imaging datasets and for +identifying any required preparatory science tasks. + +LSST will begin science operations during the next decade, +more than twenty years after the start of the Sloan +Digital Sky Survey \citep{york2000a} and subsequent precursor surveys +including PanSTARRS \citep{kaiser2010a}, the Subaru +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark +Energy Survey \citep{flaugher2005a}. Relative to these prior +efforts, extragalactic science breakthroughs +generated by LSST will likely benefit from its increased area, source +counts, and statistical samples, the constraining power of the +six-band imaging, and the survey depth and image quality. The following +discussion of LSST efforts focusing on the astrophysics of galaxies +will highlight how these features of the survey enable new science +programs. + + + +\subsection{Star Formation and Stellar Populations in Galaxies} +\label{sec:sci:gal:bkgnd:stars} + +Light emitted by stellar populations will +provide all the direct measurements made by +LSST. This information will be filtered through +the six passbands utilized by the survey +($ugrizy$), providing constraints on the +rest-frame ultraviolet SEDs of galaxies to +redshift $z\sim6$ and a probe of rest-frame +optical spectral breaks to $z\sim1.5$. By +using stellar population synthesis modeling, +these measures of galaxy SEDS will enable +estimates of the redshifts, star formation rates, +stellar masses, dust content, and +population ages for potentially +billions of galaxies. In the context of previous +extragalactic surveys, LSST +will enable new advances in our understanding +of stellar populations in galaxies by contributing +previously unachievable statistical power and an +areal coverage that samples the rarest cosmic +environments. + +A variety of ground- and space-based observations +have constrained the +star formation history of the universe over the +redshift range that LSST will likely probe +\citep[for a recent review, see][]{madau2014a}. +The statistical power of LSST will improve our +knowledge of the evolving UV luminosity function, +luminosity density, and cosmic +star formation rate. The LSST observations can +constrain how the astrophysics of gas +cooling within dark matter halos, the efficiency +of molecular cloud formation and the star formation +within them, and +regulatory mechanisms like supernova and radiative +heating give rise to these statistical features +of the galaxy population. While measurement of +the evolving UV luminosity function can +help quantify the role of these +astrophysical processes, the ability of LSST +to probe vastly different cosmic environments +will also allow for the robust quantification of any +changes in the UV luminosity function with +environmental density, and an examination of +connections between environment and the fueling +of star formation. + +Optical observations teach us about +the established stellar content of galaxies. +For stellar populations older than $\sim100$ million +years, optical observations provide +sensitivity to the spectral breaks near a +wavelength of $\lambda\approx4000\AA$ in the +rest-frame related to absorption in the +atmospheres of mature stars. +Such observations help constrain +the amount of stellar mass in galaxies. For +passive galaxies that lack vigorous star formation, +these optical observations reveal +the well-defined ``red sequence'' of +galaxies in the color-magnitude plane +that traces the succession of +galaxies from recently-merged spheroids +to the most massive systems at the +centers of galaxy clusters. For blue, +star-forming +galaxies, optical light can help +quantify the relative contribution of +evolved stars to total galaxy luminosity, +and indeed has +led to the identification of a well-defined +locus of galaxies in the parameter space of +star formation rate and stellar mass +\citep[e.g.,][]{noeske2007a}. This +relation, often called the ``star-forming +main sequence'' of galaxies, indicates that +galaxies of the same stellar mass typically +sustain a similar star-formation rate. +Determining the +physical or possibly statistical +origin of the relation remains an active +line of inquiry, guided by recently improved +data from Hubble Space Telescope over the +$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared +Deep Extragalactic Survey +\citep{grogin2011a,koekemoer2011a}. While +LSST will be comparably limited in redshift +selection, its $~30,000$ times larger area +will enable a much fuller sampling of the +star formation--stellar mass plane, allowing +for a characterization of the distribution +of galaxies that lie off the main sequence +that can help discriminate between phenomenological +explanations of the sequence. + +\subsection{Galaxies as Cosmic Structures} +\label{sec:sci:gal:bkgnd:structures} + +The structural properties of galaxies arise from +an intricate combination of important astrophysical +processes. The gaseous disks of galaxies require +substantial energy dissipation while depositing +angular momentum into a rotating structure. These +gaseous disks form stars with a +surface density that declines exponentially with +galactic radius, populating stellar orbits that +differentially rotate about the galactic center and +somehow organize into spiral features. +Many disk galaxies contain (pseduo-)bulges that form through +a combination of violent relaxation and orbital dynamics. +These disk galaxy features contrast with systems where +spheroidal stellar distributions dominate the galactic +structure. Massive ellipticals form through galaxy +mergers and accretions, and manage to forge a regular +sequence of surface density, size, and stellar velocity +dispersion from the chaos of strong gravitational +encounters. Since these astrophysical +processes may operate with great +variety as a function of galaxy mass and +cosmic environment, LSST will revolutionize studies +of evolving galaxy morphologies by providing enormous +samples with deep imaging of exquisite quality. + +The huge sample of galaxies provided by LSST will +provide a definitive view of how the sizes and +structural parameters of disk and spheroidal systems +vary with color, stellar mass, and luminosity. +Morphological studies will employ at least two +complementary techniques for quantifying the +structural properties of galaxies. Bayesian +methods can yield multi-component +parameterized models for all the galaxies +in the LSST sample, including the quantified +contribution of bulge, disk, and +spheroid structures to the observed galaxy +surface brightness profiles. The parameterized +models will supplement non-parametric measures +of the light distribution including the +Gini and M20 metrics that quantify the surface +brightness uniformity and spatial moment of +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. +Collectively, these morphological measures provided +by analyzing the LSST imaging data will enable +a consummate determination of the relation between +structural properties and other features of +galaxies over a range of galaxy mass and luminosity +previously unattainable. + +While the size of the LSST sample supplies the +statistical power for definitive morphological studies, +the sample size also enables the identification of rare +objects. This capability will benefit our efforts for +connecting the distribution of galaxy morphologies to their +evolutionary origin during the structure formation process, +including the formation of disk galaxies. +The emergence of ordered disk galaxies remains a hallmark +event in cosmic history, with so-called ``grand design'' +spirals like the Milky Way forming dynamically cold, thin +disks in the last $\sim10$ Gyr. Before thin disks emerged, +rotating systems featured ``clumpy'' mass distributions with +density enhancements +that may originate from large scale gravitational instability. +Whether the ground-based LSST can effectively probe +the exact timing and duration of the transition from +clumpy to well-ordered disks remains +unknown, but LSST can undoubtedly contribute studying the +variation in forming disk structures at the present day. +Unusual objects, such as the UV luminous local galaxies identified +by \citet{heckman2005a} that display physical features analogous to +Lyman break galaxies at higher redshifts, may provide a +means to study the formation of disks in the present day +under rare conditions only well-probed by the sheer size +of the LSST survey. + +Similarly, the characterizing the extremes of the +massive spheroid population can critically inform +theoretical models for their formation. For instance, +the most massive galaxies at the centers of galaxy clusters +contain vast numbers of stars within enormous stellar +envelopes. The definitive LSST sample can capture enough +of the most massive, rare clusters to quantify the +spatial extent of these galaxies at +low surface brightnesses, where the bound stellar +structures blend with the intracluster light of +their hosts. Another research area the LSST data +can help address regards the central densities of local +ellipticals that have seemingly decreased compared with +field ellipticals at higher redshifts. The transformation +of these dense, early ellipticals to the spheroids in the +present day may involve galaxy mergers and environmental +effects, two astrophysical processes that LSST can characterize +through unparalleled statistics and environmental probes. +By measuring the +surface brightness profiles of billions of +ellipticals LSST can determine whether any such dense +early ellipticals survive to the present day, whatever +their rarity. + +Beyond the statistical advances enabled by LSST and the +wide variation in environments probed by a survey +of half the sky, the image quality of LSST will permit +studies of galaxy structures in the very low surface +brightness regime. Observational +measures of the outer most regions of thin disks can constrain +how such disks ``end'', how dynamical effects might truncate +disks, and whether some disks smoothly transition into stellar +halos. LSST will provide such measures and help quantify the +relative importance the physical effects that influence the +low surface brightness regions in disks. Other galaxies +have low surface brightnesses throughout their stellar +structures, and the image quality and sensitivity +of LSST will enable the most complete census +of low surface brightness galaxies to date. LSST will provide +the best available constraints on the extremes of disk +surface brightness, which relates to the extremes of +star formation in low surface density environments. + +The ability of LSST to probe low surface brightnesses +also allows for characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +from streams to density inhomogeneities, originate +from the hierarchical formation process and their +morphology provides clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} +have already +demonstrated that stellar halo structures display interesting +variety +\citep[e.g.,][]{van_dokkum2014a}. +LSST, with its unrivaled entendue, can help build a statistical +sample of stellar halos and cross-reference their morphologies +with the observed properties of their central galaxies. Such +studies may determine whether the formation histories reflected +in the structures of halos also influence galaxy colors or +morphological type. The +examination of stellar halos around external galaxies may +also result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +models of the galaxy formation process on the extreme +low-mass end of the mass function. + +\subsection{Probing the Extremes of Galaxy Formation} +\label{sec:sci:gal:bkgnd:rare} + +The deep, multiband imaging LSST provides over an enormous +area will enable the search for galaxies that form in the +rarest environments, under the most unusual conditions, +and at very early times. By probing the extremes of +galaxy formation, the LSST data will push our theoretical +understanding of the structure formation process. + +The rarest, most massive early galaxies may form in +conjunction with the supermassive black holes that +power distant quasars. LSST can use the same +types of color-color selections to identify extremely +luminosity galaxies out to redshift $z\sim6$, and +monitor whether the stellar mass build-up in these +galaxies tracks the accretion history of the most +massive supermassive black holes. If stellar mass +builds proportionally to black hole mass in quasars, +then very rare luminous star forming galaxies at +early times may immediately proceed the formation +of bright quasars. LSST has all the requisite +survey properties (area, mutliband imaging, and +depth) to investigate this long-standing problem. + +The creation of LSST Deep Drilling fields will +enable a measurement of the very bright end +of the high-redshift galaxy luminosity function. +Independent determinations of the distribution of +galaxy luminosities at $z\sim6$ show substantial +variations at the bright end. The origin of +the discrepancies between various groups remains +unclear, but the substantial cosmic variance expected +for the limited volumes probed and the intrinsic +rarity of the bright objects may conspire to +introduce large potential differences between +the abundance of massive galaxies in different +areas of the sky. Reducing this uncertainty requires +deep imaging over a wide area, and the LSST Deep Drilling +fields satisfy this need by achieving sensitivities +beyond the rest of the survey. + +Lastly, the spatial rarity of extreme objects discovered +in the wide LSST area may reflect an intrinsically +small volumetric density of objects or the short duration +of an event that gives rise to the observed properties of the +rare objects. Mergers represent a critical class +of short-lived epochs in the formation histories of +individual galaxies. Current determinations of the evolving numbers +of close galaxy pairs or morphological indicators of +mergers provide varying estimates for the +redshift dependence of the galaxy merger rate +\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. +The identification of merging +galaxy pairs as a function of separation, merger +mass ratio, and environment in the LSST data will enable +a full accounting of how galaxy mergers influence +the observed properties of galaxies as a function of +cosmic time. + + +\subsection{Photometric Redshifts} +\label{sec:sci:gal:bkgnd:photoz} +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-z's). While spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra, photometric redshifts, instead, estimate the rough distance to an object based on broad-band photometric colors. This can be thought of as akin to a very low-resolution spectrum sensitive to the large-scale features of a galaxy spetral energy distribution (e.~g.~the 4000$\AA$ and Lyman breaks), with each broad-band filter being a single pixel in the spectrum. By relying on imaging data alone, we are able to measure photo-z's for billions of galaxies in the LSST survey, at the cost of added uncertainty in the redshift estimates, and potential redshift degeneracies. + As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-z's is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it the incorrect luminosity via the distance modulus, and can bias estimates of the luminosity function; errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to an error in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. + In order to understand the biases and uncertainties inherent to photo-z's for a particular survey, we need to train the photo-z algorithms using galaxies with known redshifts. For a full characterization, a fully representative sub-sample of the underlying galaxy population is necessary; however, in practice, this is very difficult to achieve, due to limitations in both spectroscopic instrumentation and telescope time. We can attempt to identify and remove any biases due to incomplete training data using several redshift calibration techniques, the most prominent one relying on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts. A detailed plan describing the spectroscopic needs, for training and calibration, is laid out in \citet[]{Newman2015}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be functional in the near future. As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-z training, but also to those studying galaxy formation and evolution. In addition, any insights gained on galaxy formation and evolution during the course of the LSST survey can be used to improve photo-z algorithms. For example, improved spetral energy distribution evolution models would improve photo-z performance at high redshift. Or, observable quantities such as size and surface brightness may be incorporated as Bayesian priors on the photo-z's once their distributions are well understood. This mutual benefit between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both subjects as the survey progresses. + +\subsection{Science Book} +\label{sec:sci:gal:bkgnd:scibook} + +The contents of the +Galaxies Chapter 9 of the Science Book (\citealt{LSSTSciBook}). + +\begin{enumerate} +\item Measurements, Detection, Photometry, Morphology +\item Demographics of Galaxy Populations +\begin{itemize} +\item Passively evolving galaxies +\item High-redshift star forming galaxies +\item Dwarf galaxies +\item Mergers and interactions +\end{itemize} +\item Distribution Functions and Scaling Relations +\begin{itemize} +\item Luminosity and size evolution +\item Relations between observables +\item Quantifying the Biases and Uncertainties +\end{itemize} +\item Galaxies in their Dark-Matter Context +\begin{itemize} +\item Measuring Galaxy Environments with LSST +\item The Galaxy-Halo Connection +\item Clusters and Cluster Galaxy Evolution +\item Probing Galaxy Evolution with Clustering Measurements +\item Measuring Angular Correlations with LSST, Cross-correlations +\end{itemize} +\item Galaxies at Extremely Low Surface Brightness +\begin{itemize} +\item Spiral Galaxies with LSB Disks +\item Dwarf Galaxies +\item Tidal Tails and Streams +\item Intracluster Light +\end{itemize} +\item Wide Area, Multiband Searches for High-Redshift Galaxies +\item Deep Drilling Fields +\item Galaxy Mergers and Merger Rates +\item Special Populations of Galaxies +\item Public Involvement +\end{enumerate} + + + + + From dfe563b8bb9e3790dd85d0c6a8f3ca597c1d0040 Mon Sep 17 00:00:00 2001 From: Sam Schmidt Date: Tue, 21 Mar 2017 16:59:18 -0700 Subject: [PATCH 18/64] add Newman2015 ref --- .../galaxies/references.bib | 33 +++++++++++++++++++ 1 file changed, 33 insertions(+) diff --git a/2016/science_background/galaxies/references.bib b/2016/science_background/galaxies/references.bib index 5295805..3619ec9 100644 --- a/2016/science_background/galaxies/references.bib +++ b/2016/science_background/galaxies/references.bib @@ -368,6 +368,39 @@ @INPROCEEDINGS{miyazaki2012a adsnote = {Provided by the SAO/NASA Astrophysics Data System} } %NNNNNNNNNNN +@ARTICLE{Newman2015, + author = {{Newman}, J.~A. and {Abate}, A. and {Abdalla}, F.~B. and {Allam}, S. and + {Allen}, S.~W. and {Ansari}, R. and {Bailey}, S. and {Barkhouse}, W.~A. and + {Beers}, T.~C. and {Blanton}, M.~R. and {Brodwin}, M. and {Brownstein}, J.~R. and + {Brunner}, R.~J. and {Carrasco Kind}, M. and {Cervantes-Cota}, J.~L. and + {Cheu}, E. and {Chisari}, N.~E. and {Colless}, M. and {Comparat}, J. and + {Coupon}, J. and {Cunha}, C.~E. and {de la Macorra}, A. and + {Dell'Antonio}, I.~P. and {Frye}, B.~L. and {Gawiser}, E.~J. and + {Gehrels}, N. and {Grady}, K. and {Hagen}, A. and {Hall}, P.~B. and + {Hearin}, A.~P. and {Hildebrandt}, H. and {Hirata}, C.~M. and + {Ho}, S. and {Honscheid}, K. and {Huterer}, D. and {Ivezi{\'c}}, {\v Z}. and + {Kneib}, J.-P. and {Kruk}, J.~W. and {Lahav}, O. and {Mandelbaum}, R. and + {Marshall}, J.~L. and {Matthews}, D.~J. and {M{\'e}nard}, B. and + {Miquel}, R. and {Moniez}, M. and {Moos}, H.~W. and {Moustakas}, J. and + {Myers}, A.~D. and {Papovich}, C. and {Peacock}, J.~A. and {Park}, C. and + {Rahman}, M. and {Rhodes}, J. and {Ricol}, J.-S. and {Sadeh}, I. and + {Slozar}, A. and {Schmidt}, S.~J. and {Stern}, D.~K. and {Anthony Tyson}, J. and + {von der Linden}, A. and {Wechsler}, R.~H. and {Wood-Vasey}, W.~M. and + {Zentner}, A.~R.}, + title = "{Spectroscopic needs for imaging dark energy experiments}", + journal = {Astroparticle Physics}, +archivePrefix = "arXiv", + eprint = {1309.5384}, + keywords = {Cosmology, Dark energy, Surveys}, + year = 2015, + month = mar, + volume = 63, + pages = {81-100}, + doi = {10.1016/j.astropartphys.2014.06.007}, + adsurl = {http://adsabs.harvard.edu/abs/2015APh....63...81N}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + @ARTICLE{noeske2007a, author = {{Noeske}, K.~G. and {Weiner}, B.~J. and {Faber}, S.~M. and {Papovich}, C. and {Koo}, D.~C. and {Somerville}, R.~S. and {Bundy}, K. and {Conselice}, C.~J. and From 9f261e93269977c7d229b6bab861af3b3230fda3 Mon Sep 17 00:00:00 2001 From: Sam Schmidt Date: Tue, 21 Mar 2017 17:19:40 -0700 Subject: [PATCH 19/64] fix typos --- 2016/science_background/galaxies/galaxies.tex | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/2016/science_background/galaxies/galaxies.tex b/2016/science_background/galaxies/galaxies.tex index f1ec658..85f085b 100644 --- a/2016/science_background/galaxies/galaxies.tex +++ b/2016/science_background/galaxies/galaxies.tex @@ -388,9 +388,9 @@ \subsection{Probing the Extremes of Galaxy Formation} \subsection{Photometric Redshifts} \label{sec:sci:gal:bkgnd:photoz} -As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-z's). While spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra, photometric redshifts, instead, estimate the rough distance to an object based on broad-band photometric colors. This can be thought of as akin to a very low-resolution spectrum sensitive to the large-scale features of a galaxy spetral energy distribution (e.~g.~the 4000$\AA$ and Lyman breaks), with each broad-band filter being a single pixel in the spectrum. By relying on imaging data alone, we are able to measure photo-z's for billions of galaxies in the LSST survey, at the cost of added uncertainty in the redshift estimates, and potential redshift degeneracies. +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-z's). While spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra, photometric redshifts, instead, estimate the rough distance to an object based on broad-band photometric colors. This can be thought of as akin to a very low-resolution spectrum sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.~the 4000\AA\ and Lyman breaks), with each broad-band filter being a single pixel in the spectrum. By relying on imaging data alone, we are able to measure photo-z's for billions of galaxies in the LSST survey, at the cost of added uncertainty in the redshift estimates, and potential redshift degeneracies. As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-z's is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it the incorrect luminosity via the distance modulus, and can bias estimates of the luminosity function; errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to an error in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. - In order to understand the biases and uncertainties inherent to photo-z's for a particular survey, we need to train the photo-z algorithms using galaxies with known redshifts. For a full characterization, a fully representative sub-sample of the underlying galaxy population is necessary; however, in practice, this is very difficult to achieve, due to limitations in both spectroscopic instrumentation and telescope time. We can attempt to identify and remove any biases due to incomplete training data using several redshift calibration techniques, the most prominent one relying on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts. A detailed plan describing the spectroscopic needs, for training and calibration, is laid out in \citet[]{Newman2015}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be functional in the near future. As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-z training, but also to those studying galaxy formation and evolution. In addition, any insights gained on galaxy formation and evolution during the course of the LSST survey can be used to improve photo-z algorithms. For example, improved spetral energy distribution evolution models would improve photo-z performance at high redshift. Or, observable quantities such as size and surface brightness may be incorporated as Bayesian priors on the photo-z's once their distributions are well understood. This mutual benefit between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both subjects as the survey progresses. + In order to understand the biases and uncertainties inherent to photo-z's for a particular survey, we need to train the photo-z algorithms using galaxies with known redshifts. For a full characterization, a fully representative sub-sample of the underlying galaxy population is necessary; however, in practice, this is very difficult to achieve, due to limitations in both spectroscopic instrumentation and telescope time. We can attempt to identify and remove any biases due to incomplete training data using several redshift calibration techniques, the most prominent one relying on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts. A detailed plan describing the spectroscopic needs, for training and calibration, is laid out in \citet[]{Newman2015}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be functional in the near future. As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-z training, but also to those studying galaxy formation and evolution. In addition, any insights gained on galaxy formation and evolution during the course of the LSST survey can be used to improve photo-z algorithms. For example, improved spectral energy distribution evolution models would improve photo-z performance at high redshift. Or, observable quantities such as size and surface brightness may be incorporated as Bayesian priors on the photo-z's once their distributions are well understood. This mutual benefit between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both subjects as the survey progresses. \subsection{Science Book} \label{sec:sci:gal:bkgnd:scibook} From 07fdb29bd2ef65a469f6163c303028af35e0da17 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 22 Mar 2017 10:12:37 -0700 Subject: [PATCH 20/64] Forgot to add galaxies background (thanks @sschmidt23 !) --- science_background/galaxies/galaxies.tex | 442 +++++++++++++++++++++++ 1 file changed, 442 insertions(+) create mode 100644 science_background/galaxies/galaxies.tex diff --git a/science_background/galaxies/galaxies.tex b/science_background/galaxies/galaxies.tex new file mode 100644 index 0000000..03c09c5 --- /dev/null +++ b/science_background/galaxies/galaxies.tex @@ -0,0 +1,442 @@ + +% LSST Extragalactic Roadmap +% Chapter: science_background +% Section: galaxies +% First draft by + +\section{Galaxy Evolution Studies with LSST} +\label{sec:sci:gal:bkgnd} + +Galaxies represent fundamental astronomical objects +outside our own Milky Way. +The large luminosities of galaxies enable their +detection to extreme distances, providing abundant +and far-reaching probes into the depths of the universe. +At each epoch in cosmological history, the color +and brightness distributions of the galaxy population +reveal how stellar populations form with time and +as a function of galaxy mass. The progressive mix of +disk and spheroidal morphological components of +galaxies communicate the relative importance of +energy dissipation and collisionless processes +for their formation. +Correlations between internal galaxy properties and +cosmic environments indicate +the ways the universe nurtures galaxies as they form. +The evolution of the +detailed characteristics of galaxies over cosmic time +reflects how fundamental astrophysics +operates to generate the rich variety of +astronomical structures observed today. + +Study of the astrophysics of galaxy formation represents +a vital science of its own, but the ready +observability of galaxies critically enables a host of +astronomical experiments in other fields. +Galaxies act as the semaphores of the +universe, encoding information about +the development of large scale +structures and the mass-energy budget of the +universe in their spatial distribution. The mass distribution +and clustering of galaxies reflect essential +properties of dark matter, including potential +constraints on the velocity and mass of particle candidates. +Galaxies famously host supermassive black holes, +and observations of active galactic nuclei provide +a window into the high-energy astrophysics of black hole +accretion processes. The porous interface between the +astrophysics of black holes, galaxies, and +dark matter structures allows for astronomers to +achieve gains in each field using the same datasets. + +The Large Synoptic Survey Telescope (LSST) will provide a +digital image of the southern sky in six bands ($ugrizy$). +The area ($\sim18,000~\mathrm{deg}^2$) and depth +($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of +the survey will enable research of such breadth +that LSST may influence essentially all extragalactic +science programs that rely primarily on photometric data. +For studies of galaxies, LSST provide both an unequaled +catalogue of billions of extragalactic sources and high-quality +multiband imaging of individual objects. This section of +the {\it Extragalactic Roadmap} presents scientific +background for studies of these galaxies with LSST to provide a +context for considering how the astronomical community can +best leverage the catalogue and imaging datasets and for +identifying any required preparatory science tasks. + +LSST will begin science operations during the next decade, +more than twenty years after the start of the Sloan +Digital Sky Survey \citep{york2000a} and subsequent precursor surveys +including PanSTARRS \citep{kaiser2010a}, the Subaru +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark +Energy Survey \citep{flaugher2005a}. Relative to these prior +efforts, extragalactic science breakthroughs +generated by LSST will likely benefit from its increased area, source +counts, and statistical samples, the constraining power of the +six-band imaging, and the survey depth and image quality. The following +discussion of LSST efforts focusing on the astrophysics of galaxies +will highlight how these features of the survey enable new science +programs. + + + +\subsection{Star Formation and Stellar Populations in Galaxies} +\label{sec:sci:gal:bkgnd:stars} + +Light emitted by stellar populations will +provide all the direct measurements made by +LSST. This information will be filtered through +the six passbands utilized by the survey +($ugrizy$), providing constraints on the +rest-frame ultraviolet SEDs of galaxies to +redshift $z\sim6$ and a probe of rest-frame +optical spectral breaks to $z\sim1.5$. By +using stellar population synthesis modeling, +these measures of galaxy SEDS will enable +estimates of the redshifts, star formation rates, +stellar masses, dust content, and +population ages for potentially +billions of galaxies. In the context of previous +extragalactic surveys, LSST +will enable new advances in our understanding +of stellar populations in galaxies by contributing +previously unachievable statistical power and an +areal coverage that samples the rarest cosmic +environments. + +A variety of ground- and space-based observations +have constrained the +star formation history of the universe over the +redshift range that LSST will likely probe +\citep[for a recent review, see][]{madau2014a}. +The statistical power of LSST will improve our +knowledge of the evolving UV luminosity function, +luminosity density, and cosmic +star formation rate. The LSST observations can +constrain how the astrophysics of gas +cooling within dark matter halos, the efficiency +of molecular cloud formation and the star formation +within them, and +regulatory mechanisms like supernova and radiative +heating give rise to these statistical features +of the galaxy population. While measurement of +the evolving UV luminosity function can +help quantify the role of these +astrophysical processes, the ability of LSST +to probe vastly different cosmic environments +will also allow for the robust quantification of any +changes in the UV luminosity function with +environmental density, and an examination of +connections between environment and the fueling +of star formation. + +Optical observations teach us about +the established stellar content of galaxies. +For stellar populations older than $\sim100$ million +years, optical observations provide +sensitivity to the spectral breaks near a +wavelength of $\lambda\approx4000\AA$ in the +rest-frame related to absorption in the +atmospheres of mature stars. +Such observations help constrain +the amount of stellar mass in galaxies. For +passive galaxies that lack vigorous star formation, +these optical observations reveal +the well-defined ``red sequence'' of +galaxies in the color-magnitude plane +that traces the succession of +galaxies from recently-merged spheroids +to the most massive systems at the +centers of galaxy clusters. For blue, +star-forming +galaxies, optical light can help +quantify the relative contribution of +evolved stars to total galaxy luminosity, +and indeed has +led to the identification of a well-defined +locus of galaxies in the parameter space of +star formation rate and stellar mass +\citep[e.g.,][]{noeske2007a}. This +relation, often called the ``star-forming +main sequence'' of galaxies, indicates that +galaxies of the same stellar mass typically +sustain a similar star-formation rate. +Determining the +physical or possibly statistical +origin of the relation remains an active +line of inquiry, guided by recently improved +data from Hubble Space Telescope over the +$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared +Deep Extragalactic Survey +\citep{grogin2011a,koekemoer2011a}. While +LSST will be comparably limited in redshift +selection, its $~30,000$ times larger area +will enable a much fuller sampling of the +star formation--stellar mass plane, allowing +for a characterization of the distribution +of galaxies that lie off the main sequence +that can help discriminate between phenomenological +explanations of the sequence. + +\subsection{Galaxies as Cosmic Structures} +\label{sec:sci:gal:bkgnd:structures} + +The structural properties of galaxies arise from +an intricate combination of important astrophysical +processes. The gaseous disks of galaxies require +substantial energy dissipation while depositing +angular momentum into a rotating structure. These +gaseous disks form stars with a +surface density that declines exponentially with +galactic radius, populating stellar orbits that +differentially rotate about the galactic center and +somehow organize into spiral features. +Many disk galaxies contain (pseduo-)bulges that form through +a combination of violent relaxation and orbital dynamics. +These disk galaxy features contrast with systems where +spheroidal stellar distributions dominate the galactic +structure. Massive ellipticals form through galaxy +mergers and accretions, and manage to forge a regular +sequence of surface density, size, and stellar velocity +dispersion from the chaos of strong gravitational +encounters. Since these astrophysical +processes may operate with great +variety as a function of galaxy mass and +cosmic environment, LSST will revolutionize studies +of evolving galaxy morphologies by providing enormous +samples with deep imaging of exquisite quality. + +The huge sample of galaxies provided by LSST will +provide a definitive view of how the sizes and +structural parameters of disk and spheroidal systems +vary with color, stellar mass, and luminosity. +Morphological studies will employ at least two +complementary techniques for quantifying the +structural properties of galaxies. Bayesian +methods can yield multi-component +parameterized models for all the galaxies +in the LSST sample, including the quantified +contribution of bulge, disk, and +spheroid structures to the observed galaxy +surface brightness profiles. The parameterized +models will supplement non-parametric measures +of the light distribution including the +Gini and M20 metrics that quantify the surface +brightness uniformity and spatial moment of +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. +Collectively, these morphological measures provided +by analyzing the LSST imaging data will enable +a consummate determination of the relation between +structural properties and other features of +galaxies over a range of galaxy mass and luminosity +previously unattainable. + +While the size of the LSST sample supplies the +statistical power for definitive morphological studies, +the sample size also enables the identification of rare +objects. This capability will benefit our efforts for +connecting the distribution of galaxy morphologies to their +evolutionary origin during the structure formation process, +including the formation of disk galaxies. +The emergence of ordered disk galaxies remains a hallmark +event in cosmic history, with so-called ``grand design'' +spirals like the Milky Way forming dynamically cold, thin +disks in the last $\sim10$ Gyr. Before thin disks emerged, +rotating systems featured ``clumpy'' mass distributions with +density enhancements +that may originate from large scale gravitational instability. +Whether the ground-based LSST can effectively probe +the exact timing and duration of the transition from +clumpy to well-ordered disks remains +unknown, but LSST can undoubtedly contribute studying the +variation in forming disk structures at the present day. +Unusual objects, such as the UV luminous local galaxies identified +by \citet{heckman2005a} that display physical features analogous to +Lyman break galaxies at higher redshifts, may provide a +means to study the formation of disks in the present day +under rare conditions only well-probed by the sheer size +of the LSST survey. + +Similarly, the characterizing the extremes of the +massive spheroid population can critically inform +theoretical models for their formation. For instance, +the most massive galaxies at the centers of galaxy clusters +contain vast numbers of stars within enormous stellar +envelopes. The definitive LSST sample can capture enough +of the most massive, rare clusters to quantify the +spatial extent of these galaxies at +low surface brightnesses, where the bound stellar +structures blend with the intracluster light of +their hosts. Another research area the LSST data +can help address regards the central densities of local +ellipticals that have seemingly decreased compared with +field ellipticals at higher redshifts. The transformation +of these dense, early ellipticals to the spheroids in the +present day may involve galaxy mergers and environmental +effects, two astrophysical processes that LSST can characterize +through unparalleled statistics and environmental probes. +By measuring the +surface brightness profiles of billions of +ellipticals LSST can determine whether any such dense +early ellipticals survive to the present day, whatever +their rarity. + +Beyond the statistical advances enabled by LSST and the +wide variation in environments probed by a survey +of half the sky, the image quality of LSST will permit +studies of galaxy structures in the very low surface +brightness regime. Observational +measures of the outer most regions of thin disks can constrain +how such disks ``end'', how dynamical effects might truncate +disks, and whether some disks smoothly transition into stellar +halos. LSST will provide such measures and help quantify the +relative importance the physical effects that influence the +low surface brightness regions in disks. Other galaxies +have low surface brightnesses throughout their stellar +structures, and the image quality and sensitivity +of LSST will enable the most complete census +of low surface brightness galaxies to date. LSST will provide +the best available constraints on the extremes of disk +surface brightness, which relates to the extremes of +star formation in low surface density environments. + +The ability of LSST to probe low surface brightnesses +also allows for characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +from streams to density inhomogeneities, originate +from the hierarchical formation process and their +morphology provides clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} +have already +demonstrated that stellar halo structures display interesting +variety +\citep[e.g.,][]{van_dokkum2014a}. +LSST, with its unrivaled entendue, can help build a statistical +sample of stellar halos and cross-reference their morphologies +with the observed properties of their central galaxies. Such +studies may determine whether the formation histories reflected +in the structures of halos also influence galaxy colors or +morphological type. The +examination of stellar halos around external galaxies may +also result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +models of the galaxy formation process on the extreme +low-mass end of the mass function. + +\subsection{Probing the Extremes of Galaxy Formation} +\label{sec:sci:gal:bkgnd:rare} + +The deep, multiband imaging LSST provides over an enormous +area will enable the search for galaxies that form in the +rarest environments, under the most unusual conditions, +and at very early times. By probing the extremes of +galaxy formation, the LSST data will push our theoretical +understanding of the structure formation process. + +The rarest, most massive early galaxies may form in +conjunction with the supermassive black holes that +power distant quasars. LSST can use the same +types of color-color selections to identify extremely +luminosity galaxies out to redshift $z\sim6$, and +monitor whether the stellar mass build-up in these +galaxies tracks the accretion history of the most +massive supermassive black holes. If stellar mass +builds proportionally to black hole mass in quasars, +then very rare luminous star forming galaxies at +early times may immediately proceed the formation +of bright quasars. LSST has all the requisite +survey properties (area, mutliband imaging, and +depth) to investigate this long-standing problem. + +The creation of LSST Deep Drilling fields will +enable a measurement of the very bright end +of the high-redshift galaxy luminosity function. +Independent determinations of the distribution of +galaxy luminosities at $z\sim6$ show substantial +variations at the bright end. The origin of +the discrepancies between various groups remains +unclear, but the substantial cosmic variance expected +for the limited volumes probed and the intrinsic +rarity of the bright objects may conspire to +introduce large potential differences between +the abundance of massive galaxies in different +areas of the sky. Reducing this uncertainty requires +deep imaging over a wide area, and the LSST Deep Drilling +fields satisfy this need by achieving sensitivities +beyond the rest of the survey. + +Lastly, the spatial rarity of extreme objects discovered +in the wide LSST area may reflect an intrinsically +small volumetric density of objects or the short duration +of an event that gives rise to the observed properties of the +rare objects. Mergers represent a critical class +of short-lived epochs in the formation histories of +individual galaxies. Current determinations of the evolving numbers +of close galaxy pairs or morphological indicators of +mergers provide varying estimates for the +redshift dependence of the galaxy merger rate +\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. +The identification of merging +galaxy pairs as a function of separation, merger +mass ratio, and environment in the LSST data will enable +a full accounting of how galaxy mergers influence +the observed properties of galaxies as a function of +cosmic time. + +\subsection{Science Book} +\label{sec:sci:gal:bkgnd:scibook} + +The LSST Science Book (\citealt{LSSTSciBook}) provided +detailed descriptions of foundationl science enabled +by LSST. The LSST Galaxies Science Collaboration authored +the Chapter 9 ``Galaxies'' of the Science Book, and the +a table of contents of that chapter follow below to +provide an example list of topics in extragalactic +science that LSST data will help revolutionize. The +interested reader is referred to the LSST Science +Book for more details. + + +\begin{enumerate} +\item Measurements, Detection, Photometry, Morphology +\item Demographics of Galaxy Populations +\begin{itemize} +\item Passively evolving galaxies +\item High-redshift star forming galaxies +\item Dwarf galaxies +\item Mergers and interactions +\end{itemize} +\item Distribution Functions and Scaling Relations +\begin{itemize} +\item Luminosity and size evolution +\item Relations between observables +\item Quantifying the Biases and Uncertainties +\end{itemize} +\item Galaxies in their Dark-Matter Context +\begin{itemize} +\item Measuring Galaxy Environments with LSST +\item The Galaxy-Halo Connection +\item Clusters and Cluster Galaxy Evolution +\item Probing Galaxy Evolution with Clustering Measurements +\item Measuring Angular Correlations with LSST, Cross-correlations +\end{itemize} +\item Galaxies at Extremely Low Surface Brightness +\begin{itemize} +\item Spiral Galaxies with LSB Disks +\item Dwarf Galaxies +\item Tidal Tails and Streams +\item Intracluster Light +\end{itemize} +\item Wide Area, Multiband Searches for High-Redshift Galaxies +\item Deep Drilling Fields +\item Galaxy Mergers and Merger Rates +\item Special Populations of Galaxies +\item Public Involvement +\end{enumerate} + + + + + From 84cf7032ac41ca5f8970a3a53ebe427341be5736 Mon Sep 17 00:00:00 2001 From: Sam Schmidt Date: Wed, 22 Mar 2017 17:38:10 -0700 Subject: [PATCH 21/64] add pz text to correct file --- science_background/galaxies/galaxies.tex | 890 ++++++++++++----------- 1 file changed, 448 insertions(+), 442 deletions(-) diff --git a/science_background/galaxies/galaxies.tex b/science_background/galaxies/galaxies.tex index 03c09c5..5c200a6 100644 --- a/science_background/galaxies/galaxies.tex +++ b/science_background/galaxies/galaxies.tex @@ -1,442 +1,448 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: galaxies -% First draft by - -\section{Galaxy Evolution Studies with LSST} -\label{sec:sci:gal:bkgnd} - -Galaxies represent fundamental astronomical objects -outside our own Milky Way. -The large luminosities of galaxies enable their -detection to extreme distances, providing abundant -and far-reaching probes into the depths of the universe. -At each epoch in cosmological history, the color -and brightness distributions of the galaxy population -reveal how stellar populations form with time and -as a function of galaxy mass. The progressive mix of -disk and spheroidal morphological components of -galaxies communicate the relative importance of -energy dissipation and collisionless processes -for their formation. -Correlations between internal galaxy properties and -cosmic environments indicate -the ways the universe nurtures galaxies as they form. -The evolution of the -detailed characteristics of galaxies over cosmic time -reflects how fundamental astrophysics -operates to generate the rich variety of -astronomical structures observed today. - -Study of the astrophysics of galaxy formation represents -a vital science of its own, but the ready -observability of galaxies critically enables a host of -astronomical experiments in other fields. -Galaxies act as the semaphores of the -universe, encoding information about -the development of large scale -structures and the mass-energy budget of the -universe in their spatial distribution. The mass distribution -and clustering of galaxies reflect essential -properties of dark matter, including potential -constraints on the velocity and mass of particle candidates. -Galaxies famously host supermassive black holes, -and observations of active galactic nuclei provide -a window into the high-energy astrophysics of black hole -accretion processes. The porous interface between the -astrophysics of black holes, galaxies, and -dark matter structures allows for astronomers to -achieve gains in each field using the same datasets. - -The Large Synoptic Survey Telescope (LSST) will provide a -digital image of the southern sky in six bands ($ugrizy$). -The area ($\sim18,000~\mathrm{deg}^2$) and depth -($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of -the survey will enable research of such breadth -that LSST may influence essentially all extragalactic -science programs that rely primarily on photometric data. -For studies of galaxies, LSST provide both an unequaled -catalogue of billions of extragalactic sources and high-quality -multiband imaging of individual objects. This section of -the {\it Extragalactic Roadmap} presents scientific -background for studies of these galaxies with LSST to provide a -context for considering how the astronomical community can -best leverage the catalogue and imaging datasets and for -identifying any required preparatory science tasks. - -LSST will begin science operations during the next decade, -more than twenty years after the start of the Sloan -Digital Sky Survey \citep{york2000a} and subsequent precursor surveys -including PanSTARRS \citep{kaiser2010a}, the Subaru -survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark -Energy Survey \citep{flaugher2005a}. Relative to these prior -efforts, extragalactic science breakthroughs -generated by LSST will likely benefit from its increased area, source -counts, and statistical samples, the constraining power of the -six-band imaging, and the survey depth and image quality. The following -discussion of LSST efforts focusing on the astrophysics of galaxies -will highlight how these features of the survey enable new science -programs. - - - -\subsection{Star Formation and Stellar Populations in Galaxies} -\label{sec:sci:gal:bkgnd:stars} - -Light emitted by stellar populations will -provide all the direct measurements made by -LSST. This information will be filtered through -the six passbands utilized by the survey -($ugrizy$), providing constraints on the -rest-frame ultraviolet SEDs of galaxies to -redshift $z\sim6$ and a probe of rest-frame -optical spectral breaks to $z\sim1.5$. By -using stellar population synthesis modeling, -these measures of galaxy SEDS will enable -estimates of the redshifts, star formation rates, -stellar masses, dust content, and -population ages for potentially -billions of galaxies. In the context of previous -extragalactic surveys, LSST -will enable new advances in our understanding -of stellar populations in galaxies by contributing -previously unachievable statistical power and an -areal coverage that samples the rarest cosmic -environments. - -A variety of ground- and space-based observations -have constrained the -star formation history of the universe over the -redshift range that LSST will likely probe -\citep[for a recent review, see][]{madau2014a}. -The statistical power of LSST will improve our -knowledge of the evolving UV luminosity function, -luminosity density, and cosmic -star formation rate. The LSST observations can -constrain how the astrophysics of gas -cooling within dark matter halos, the efficiency -of molecular cloud formation and the star formation -within them, and -regulatory mechanisms like supernova and radiative -heating give rise to these statistical features -of the galaxy population. While measurement of -the evolving UV luminosity function can -help quantify the role of these -astrophysical processes, the ability of LSST -to probe vastly different cosmic environments -will also allow for the robust quantification of any -changes in the UV luminosity function with -environmental density, and an examination of -connections between environment and the fueling -of star formation. - -Optical observations teach us about -the established stellar content of galaxies. -For stellar populations older than $\sim100$ million -years, optical observations provide -sensitivity to the spectral breaks near a -wavelength of $\lambda\approx4000\AA$ in the -rest-frame related to absorption in the -atmospheres of mature stars. -Such observations help constrain -the amount of stellar mass in galaxies. For -passive galaxies that lack vigorous star formation, -these optical observations reveal -the well-defined ``red sequence'' of -galaxies in the color-magnitude plane -that traces the succession of -galaxies from recently-merged spheroids -to the most massive systems at the -centers of galaxy clusters. For blue, -star-forming -galaxies, optical light can help -quantify the relative contribution of -evolved stars to total galaxy luminosity, -and indeed has -led to the identification of a well-defined -locus of galaxies in the parameter space of -star formation rate and stellar mass -\citep[e.g.,][]{noeske2007a}. This -relation, often called the ``star-forming -main sequence'' of galaxies, indicates that -galaxies of the same stellar mass typically -sustain a similar star-formation rate. -Determining the -physical or possibly statistical -origin of the relation remains an active -line of inquiry, guided by recently improved -data from Hubble Space Telescope over the -$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared -Deep Extragalactic Survey -\citep{grogin2011a,koekemoer2011a}. While -LSST will be comparably limited in redshift -selection, its $~30,000$ times larger area -will enable a much fuller sampling of the -star formation--stellar mass plane, allowing -for a characterization of the distribution -of galaxies that lie off the main sequence -that can help discriminate between phenomenological -explanations of the sequence. - -\subsection{Galaxies as Cosmic Structures} -\label{sec:sci:gal:bkgnd:structures} - -The structural properties of galaxies arise from -an intricate combination of important astrophysical -processes. The gaseous disks of galaxies require -substantial energy dissipation while depositing -angular momentum into a rotating structure. These -gaseous disks form stars with a -surface density that declines exponentially with -galactic radius, populating stellar orbits that -differentially rotate about the galactic center and -somehow organize into spiral features. -Many disk galaxies contain (pseduo-)bulges that form through -a combination of violent relaxation and orbital dynamics. -These disk galaxy features contrast with systems where -spheroidal stellar distributions dominate the galactic -structure. Massive ellipticals form through galaxy -mergers and accretions, and manage to forge a regular -sequence of surface density, size, and stellar velocity -dispersion from the chaos of strong gravitational -encounters. Since these astrophysical -processes may operate with great -variety as a function of galaxy mass and -cosmic environment, LSST will revolutionize studies -of evolving galaxy morphologies by providing enormous -samples with deep imaging of exquisite quality. - -The huge sample of galaxies provided by LSST will -provide a definitive view of how the sizes and -structural parameters of disk and spheroidal systems -vary with color, stellar mass, and luminosity. -Morphological studies will employ at least two -complementary techniques for quantifying the -structural properties of galaxies. Bayesian -methods can yield multi-component -parameterized models for all the galaxies -in the LSST sample, including the quantified -contribution of bulge, disk, and -spheroid structures to the observed galaxy -surface brightness profiles. The parameterized -models will supplement non-parametric measures -of the light distribution including the -Gini and M20 metrics that quantify the surface -brightness uniformity and spatial moment of -dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. -Collectively, these morphological measures provided -by analyzing the LSST imaging data will enable -a consummate determination of the relation between -structural properties and other features of -galaxies over a range of galaxy mass and luminosity -previously unattainable. - -While the size of the LSST sample supplies the -statistical power for definitive morphological studies, -the sample size also enables the identification of rare -objects. This capability will benefit our efforts for -connecting the distribution of galaxy morphologies to their -evolutionary origin during the structure formation process, -including the formation of disk galaxies. -The emergence of ordered disk galaxies remains a hallmark -event in cosmic history, with so-called ``grand design'' -spirals like the Milky Way forming dynamically cold, thin -disks in the last $\sim10$ Gyr. Before thin disks emerged, -rotating systems featured ``clumpy'' mass distributions with -density enhancements -that may originate from large scale gravitational instability. -Whether the ground-based LSST can effectively probe -the exact timing and duration of the transition from -clumpy to well-ordered disks remains -unknown, but LSST can undoubtedly contribute studying the -variation in forming disk structures at the present day. -Unusual objects, such as the UV luminous local galaxies identified -by \citet{heckman2005a} that display physical features analogous to -Lyman break galaxies at higher redshifts, may provide a -means to study the formation of disks in the present day -under rare conditions only well-probed by the sheer size -of the LSST survey. - -Similarly, the characterizing the extremes of the -massive spheroid population can critically inform -theoretical models for their formation. For instance, -the most massive galaxies at the centers of galaxy clusters -contain vast numbers of stars within enormous stellar -envelopes. The definitive LSST sample can capture enough -of the most massive, rare clusters to quantify the -spatial extent of these galaxies at -low surface brightnesses, where the bound stellar -structures blend with the intracluster light of -their hosts. Another research area the LSST data -can help address regards the central densities of local -ellipticals that have seemingly decreased compared with -field ellipticals at higher redshifts. The transformation -of these dense, early ellipticals to the spheroids in the -present day may involve galaxy mergers and environmental -effects, two astrophysical processes that LSST can characterize -through unparalleled statistics and environmental probes. -By measuring the -surface brightness profiles of billions of -ellipticals LSST can determine whether any such dense -early ellipticals survive to the present day, whatever -their rarity. - -Beyond the statistical advances enabled by LSST and the -wide variation in environments probed by a survey -of half the sky, the image quality of LSST will permit -studies of galaxy structures in the very low surface -brightness regime. Observational -measures of the outer most regions of thin disks can constrain -how such disks ``end'', how dynamical effects might truncate -disks, and whether some disks smoothly transition into stellar -halos. LSST will provide such measures and help quantify the -relative importance the physical effects that influence the -low surface brightness regions in disks. Other galaxies -have low surface brightnesses throughout their stellar -structures, and the image quality and sensitivity -of LSST will enable the most complete census -of low surface brightness galaxies to date. LSST will provide -the best available constraints on the extremes of disk -surface brightness, which relates to the extremes of -star formation in low surface density environments. - -The ability of LSST to probe low surface brightnesses -also allows for characterization of stellar halos that -surround nearby galaxies. Structures in stellar halos, -from streams to density inhomogeneities, originate -from the hierarchical formation process and their -morphology provides clues to the formation history -on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. -Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} -have already -demonstrated that stellar halo structures display interesting -variety -\citep[e.g.,][]{van_dokkum2014a}. -LSST, with its unrivaled entendue, can help build a statistical -sample of stellar halos and cross-reference their morphologies -with the observed properties of their central galaxies. Such -studies may determine whether the formation histories reflected -in the structures of halos also influence galaxy colors or -morphological type. The -examination of stellar halos around external galaxies may -also result in the identification of small mass satellites -whose sizes, luminosities, and abundances can constrain -models of the galaxy formation process on the extreme -low-mass end of the mass function. - -\subsection{Probing the Extremes of Galaxy Formation} -\label{sec:sci:gal:bkgnd:rare} - -The deep, multiband imaging LSST provides over an enormous -area will enable the search for galaxies that form in the -rarest environments, under the most unusual conditions, -and at very early times. By probing the extremes of -galaxy formation, the LSST data will push our theoretical -understanding of the structure formation process. - -The rarest, most massive early galaxies may form in -conjunction with the supermassive black holes that -power distant quasars. LSST can use the same -types of color-color selections to identify extremely -luminosity galaxies out to redshift $z\sim6$, and -monitor whether the stellar mass build-up in these -galaxies tracks the accretion history of the most -massive supermassive black holes. If stellar mass -builds proportionally to black hole mass in quasars, -then very rare luminous star forming galaxies at -early times may immediately proceed the formation -of bright quasars. LSST has all the requisite -survey properties (area, mutliband imaging, and -depth) to investigate this long-standing problem. - -The creation of LSST Deep Drilling fields will -enable a measurement of the very bright end -of the high-redshift galaxy luminosity function. -Independent determinations of the distribution of -galaxy luminosities at $z\sim6$ show substantial -variations at the bright end. The origin of -the discrepancies between various groups remains -unclear, but the substantial cosmic variance expected -for the limited volumes probed and the intrinsic -rarity of the bright objects may conspire to -introduce large potential differences between -the abundance of massive galaxies in different -areas of the sky. Reducing this uncertainty requires -deep imaging over a wide area, and the LSST Deep Drilling -fields satisfy this need by achieving sensitivities -beyond the rest of the survey. - -Lastly, the spatial rarity of extreme objects discovered -in the wide LSST area may reflect an intrinsically -small volumetric density of objects or the short duration -of an event that gives rise to the observed properties of the -rare objects. Mergers represent a critical class -of short-lived epochs in the formation histories of -individual galaxies. Current determinations of the evolving numbers -of close galaxy pairs or morphological indicators of -mergers provide varying estimates for the -redshift dependence of the galaxy merger rate -\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. -The identification of merging -galaxy pairs as a function of separation, merger -mass ratio, and environment in the LSST data will enable -a full accounting of how galaxy mergers influence -the observed properties of galaxies as a function of -cosmic time. - -\subsection{Science Book} -\label{sec:sci:gal:bkgnd:scibook} - -The LSST Science Book (\citealt{LSSTSciBook}) provided -detailed descriptions of foundationl science enabled -by LSST. The LSST Galaxies Science Collaboration authored -the Chapter 9 ``Galaxies'' of the Science Book, and the -a table of contents of that chapter follow below to -provide an example list of topics in extragalactic -science that LSST data will help revolutionize. The -interested reader is referred to the LSST Science -Book for more details. - - -\begin{enumerate} -\item Measurements, Detection, Photometry, Morphology -\item Demographics of Galaxy Populations -\begin{itemize} -\item Passively evolving galaxies -\item High-redshift star forming galaxies -\item Dwarf galaxies -\item Mergers and interactions -\end{itemize} -\item Distribution Functions and Scaling Relations -\begin{itemize} -\item Luminosity and size evolution -\item Relations between observables -\item Quantifying the Biases and Uncertainties -\end{itemize} -\item Galaxies in their Dark-Matter Context -\begin{itemize} -\item Measuring Galaxy Environments with LSST -\item The Galaxy-Halo Connection -\item Clusters and Cluster Galaxy Evolution -\item Probing Galaxy Evolution with Clustering Measurements -\item Measuring Angular Correlations with LSST, Cross-correlations -\end{itemize} -\item Galaxies at Extremely Low Surface Brightness -\begin{itemize} -\item Spiral Galaxies with LSB Disks -\item Dwarf Galaxies -\item Tidal Tails and Streams -\item Intracluster Light -\end{itemize} -\item Wide Area, Multiband Searches for High-Redshift Galaxies -\item Deep Drilling Fields -\item Galaxy Mergers and Merger Rates -\item Special Populations of Galaxies -\item Public Involvement -\end{enumerate} - - - - - + +% LSST Extragalactic Roadmap +% Chapter: science_background +% Section: galaxies +% First draft by + +\section{Galaxy Evolution Studies with LSST} +\label{sec:sci:gal:bkgnd} + +Galaxies represent fundamental astronomical objects +outside our own Milky Way. +The large luminosities of galaxies enable their +detection to extreme distances, providing abundant +and far-reaching probes into the depths of the universe. +At each epoch in cosmological history, the color +and brightness distributions of the galaxy population +reveal how stellar populations form with time and +as a function of galaxy mass. The progressive mix of +disk and spheroidal morphological components of +galaxies communicate the relative importance of +energy dissipation and collisionless processes +for their formation. +Correlations between internal galaxy properties and +cosmic environments indicate +the ways the universe nurtures galaxies as they form. +The evolution of the +detailed characteristics of galaxies over cosmic time +reflects how fundamental astrophysics +operates to generate the rich variety of +astronomical structures observed today. + +Study of the astrophysics of galaxy formation represents +a vital science of its own, but the ready +observability of galaxies critically enables a host of +astronomical experiments in other fields. +Galaxies act as the semaphores of the +universe, encoding information about +the development of large scale +structures and the mass-energy budget of the +universe in their spatial distribution. The mass distribution +and clustering of galaxies reflect essential +properties of dark matter, including potential +constraints on the velocity and mass of particle candidates. +Galaxies famously host supermassive black holes, +and observations of active galactic nuclei provide +a window into the high-energy astrophysics of black hole +accretion processes. The porous interface between the +astrophysics of black holes, galaxies, and +dark matter structures allows for astronomers to +achieve gains in each field using the same datasets. + +The Large Synoptic Survey Telescope (LSST) will provide a +digital image of the southern sky in six bands ($ugrizy$). +The area ($\sim18,000~\mathrm{deg}^2$) and depth +($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of +the survey will enable research of such breadth +that LSST may influence essentially all extragalactic +science programs that rely primarily on photometric data. +For studies of galaxies, LSST provide both an unequaled +catalogue of billions of extragalactic sources and high-quality +multiband imaging of individual objects. This section of +the {\it Extragalactic Roadmap} presents scientific +background for studies of these galaxies with LSST to provide a +context for considering how the astronomical community can +best leverage the catalogue and imaging datasets and for +identifying any required preparatory science tasks. + +LSST will begin science operations during the next decade, +more than twenty years after the start of the Sloan +Digital Sky Survey \citep{york2000a} and subsequent precursor surveys +including PanSTARRS \citep{kaiser2010a}, the Subaru +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark +Energy Survey \citep{flaugher2005a}. Relative to these prior +efforts, extragalactic science breakthroughs +generated by LSST will likely benefit from its increased area, source +counts, and statistical samples, the constraining power of the +six-band imaging, and the survey depth and image quality. The following +discussion of LSST efforts focusing on the astrophysics of galaxies +will highlight how these features of the survey enable new science +programs. + + + +\subsection{Star Formation and Stellar Populations in Galaxies} +\label{sec:sci:gal:bkgnd:stars} + +Light emitted by stellar populations will +provide all the direct measurements made by +LSST. This information will be filtered through +the six passbands utilized by the survey +($ugrizy$), providing constraints on the +rest-frame ultraviolet SEDs of galaxies to +redshift $z\sim6$ and a probe of rest-frame +optical spectral breaks to $z\sim1.5$. By +using stellar population synthesis modeling, +these measures of galaxy SEDS will enable +estimates of the redshifts, star formation rates, +stellar masses, dust content, and +population ages for potentially +billions of galaxies. In the context of previous +extragalactic surveys, LSST +will enable new advances in our understanding +of stellar populations in galaxies by contributing +previously unachievable statistical power and an +areal coverage that samples the rarest cosmic +environments. + +A variety of ground- and space-based observations +have constrained the +star formation history of the universe over the +redshift range that LSST will likely probe +\citep[for a recent review, see][]{madau2014a}. +The statistical power of LSST will improve our +knowledge of the evolving UV luminosity function, +luminosity density, and cosmic +star formation rate. The LSST observations can +constrain how the astrophysics of gas +cooling within dark matter halos, the efficiency +of molecular cloud formation and the star formation +within them, and +regulatory mechanisms like supernova and radiative +heating give rise to these statistical features +of the galaxy population. While measurement of +the evolving UV luminosity function can +help quantify the role of these +astrophysical processes, the ability of LSST +to probe vastly different cosmic environments +will also allow for the robust quantification of any +changes in the UV luminosity function with +environmental density, and an examination of +connections between environment and the fueling +of star formation. + +Optical observations teach us about +the established stellar content of galaxies. +For stellar populations older than $\sim100$ million +years, optical observations provide +sensitivity to the spectral breaks near a +wavelength of $\lambda\approx4000\AA$ in the +rest-frame related to absorption in the +atmospheres of mature stars. +Such observations help constrain +the amount of stellar mass in galaxies. For +passive galaxies that lack vigorous star formation, +these optical observations reveal +the well-defined ``red sequence'' of +galaxies in the color-magnitude plane +that traces the succession of +galaxies from recently-merged spheroids +to the most massive systems at the +centers of galaxy clusters. For blue, +star-forming +galaxies, optical light can help +quantify the relative contribution of +evolved stars to total galaxy luminosity, +and indeed has +led to the identification of a well-defined +locus of galaxies in the parameter space of +star formation rate and stellar mass +\citep[e.g.,][]{noeske2007a}. This +relation, often called the ``star-forming +main sequence'' of galaxies, indicates that +galaxies of the same stellar mass typically +sustain a similar star-formation rate. +Determining the +physical or possibly statistical +origin of the relation remains an active +line of inquiry, guided by recently improved +data from Hubble Space Telescope over the +$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared +Deep Extragalactic Survey +\citep{grogin2011a,koekemoer2011a}. While +LSST will be comparably limited in redshift +selection, its $~30,000$ times larger area +will enable a much fuller sampling of the +star formation--stellar mass plane, allowing +for a characterization of the distribution +of galaxies that lie off the main sequence +that can help discriminate between phenomenological +explanations of the sequence. + +\subsection{Galaxies as Cosmic Structures} +\label{sec:sci:gal:bkgnd:structures} + +The structural properties of galaxies arise from +an intricate combination of important astrophysical +processes. The gaseous disks of galaxies require +substantial energy dissipation while depositing +angular momentum into a rotating structure. These +gaseous disks form stars with a +surface density that declines exponentially with +galactic radius, populating stellar orbits that +differentially rotate about the galactic center and +somehow organize into spiral features. +Many disk galaxies contain (pseduo-)bulges that form through +a combination of violent relaxation and orbital dynamics. +These disk galaxy features contrast with systems where +spheroidal stellar distributions dominate the galactic +structure. Massive ellipticals form through galaxy +mergers and accretions, and manage to forge a regular +sequence of surface density, size, and stellar velocity +dispersion from the chaos of strong gravitational +encounters. Since these astrophysical +processes may operate with great +variety as a function of galaxy mass and +cosmic environment, LSST will revolutionize studies +of evolving galaxy morphologies by providing enormous +samples with deep imaging of exquisite quality. + +The huge sample of galaxies provided by LSST will +provide a definitive view of how the sizes and +structural parameters of disk and spheroidal systems +vary with color, stellar mass, and luminosity. +Morphological studies will employ at least two +complementary techniques for quantifying the +structural properties of galaxies. Bayesian +methods can yield multi-component +parameterized models for all the galaxies +in the LSST sample, including the quantified +contribution of bulge, disk, and +spheroid structures to the observed galaxy +surface brightness profiles. The parameterized +models will supplement non-parametric measures +of the light distribution including the +Gini and M20 metrics that quantify the surface +brightness uniformity and spatial moment of +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. +Collectively, these morphological measures provided +by analyzing the LSST imaging data will enable +a consummate determination of the relation between +structural properties and other features of +galaxies over a range of galaxy mass and luminosity +previously unattainable. + +While the size of the LSST sample supplies the +statistical power for definitive morphological studies, +the sample size also enables the identification of rare +objects. This capability will benefit our efforts for +connecting the distribution of galaxy morphologies to their +evolutionary origin during the structure formation process, +including the formation of disk galaxies. +The emergence of ordered disk galaxies remains a hallmark +event in cosmic history, with so-called ``grand design'' +spirals like the Milky Way forming dynamically cold, thin +disks in the last $\sim10$ Gyr. Before thin disks emerged, +rotating systems featured ``clumpy'' mass distributions with +density enhancements +that may originate from large scale gravitational instability. +Whether the ground-based LSST can effectively probe +the exact timing and duration of the transition from +clumpy to well-ordered disks remains +unknown, but LSST can undoubtedly contribute studying the +variation in forming disk structures at the present day. +Unusual objects, such as the UV luminous local galaxies identified +by \citet{heckman2005a} that display physical features analogous to +Lyman break galaxies at higher redshifts, may provide a +means to study the formation of disks in the present day +under rare conditions only well-probed by the sheer size +of the LSST survey. + +Similarly, the characterizing the extremes of the +massive spheroid population can critically inform +theoretical models for their formation. For instance, +the most massive galaxies at the centers of galaxy clusters +contain vast numbers of stars within enormous stellar +envelopes. The definitive LSST sample can capture enough +of the most massive, rare clusters to quantify the +spatial extent of these galaxies at +low surface brightnesses, where the bound stellar +structures blend with the intracluster light of +their hosts. Another research area the LSST data +can help address regards the central densities of local +ellipticals that have seemingly decreased compared with +field ellipticals at higher redshifts. The transformation +of these dense, early ellipticals to the spheroids in the +present day may involve galaxy mergers and environmental +effects, two astrophysical processes that LSST can characterize +through unparalleled statistics and environmental probes. +By measuring the +surface brightness profiles of billions of +ellipticals LSST can determine whether any such dense +early ellipticals survive to the present day, whatever +their rarity. + +Beyond the statistical advances enabled by LSST and the +wide variation in environments probed by a survey +of half the sky, the image quality of LSST will permit +studies of galaxy structures in the very low surface +brightness regime. Observational +measures of the outer most regions of thin disks can constrain +how such disks ``end'', how dynamical effects might truncate +disks, and whether some disks smoothly transition into stellar +halos. LSST will provide such measures and help quantify the +relative importance the physical effects that influence the +low surface brightness regions in disks. Other galaxies +have low surface brightnesses throughout their stellar +structures, and the image quality and sensitivity +of LSST will enable the most complete census +of low surface brightness galaxies to date. LSST will provide +the best available constraints on the extremes of disk +surface brightness, which relates to the extremes of +star formation in low surface density environments. + +The ability of LSST to probe low surface brightnesses +also allows for characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +from streams to density inhomogeneities, originate +from the hierarchical formation process and their +morphology provides clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} +have already +demonstrated that stellar halo structures display interesting +variety +\citep[e.g.,][]{van_dokkum2014a}. +LSST, with its unrivaled entendue, can help build a statistical +sample of stellar halos and cross-reference their morphologies +with the observed properties of their central galaxies. Such +studies may determine whether the formation histories reflected +in the structures of halos also influence galaxy colors or +morphological type. The +examination of stellar halos around external galaxies may +also result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +models of the galaxy formation process on the extreme +low-mass end of the mass function. + +\subsection{Probing the Extremes of Galaxy Formation} +\label{sec:sci:gal:bkgnd:rare} + +The deep, multiband imaging LSST provides over an enormous +area will enable the search for galaxies that form in the +rarest environments, under the most unusual conditions, +and at very early times. By probing the extremes of +galaxy formation, the LSST data will push our theoretical +understanding of the structure formation process. + +The rarest, most massive early galaxies may form in +conjunction with the supermassive black holes that +power distant quasars. LSST can use the same +types of color-color selections to identify extremely +luminosity galaxies out to redshift $z\sim6$, and +monitor whether the stellar mass build-up in these +galaxies tracks the accretion history of the most +massive supermassive black holes. If stellar mass +builds proportionally to black hole mass in quasars, +then very rare luminous star forming galaxies at +early times may immediately proceed the formation +of bright quasars. LSST has all the requisite +survey properties (area, mutliband imaging, and +depth) to investigate this long-standing problem. + +The creation of LSST Deep Drilling fields will +enable a measurement of the very bright end +of the high-redshift galaxy luminosity function. +Independent determinations of the distribution of +galaxy luminosities at $z\sim6$ show substantial +variations at the bright end. The origin of +the discrepancies between various groups remains +unclear, but the substantial cosmic variance expected +for the limited volumes probed and the intrinsic +rarity of the bright objects may conspire to +introduce large potential differences between +the abundance of massive galaxies in different +areas of the sky. Reducing this uncertainty requires +deep imaging over a wide area, and the LSST Deep Drilling +fields satisfy this need by achieving sensitivities +beyond the rest of the survey. + +Lastly, the spatial rarity of extreme objects discovered +in the wide LSST area may reflect an intrinsically +small volumetric density of objects or the short duration +of an event that gives rise to the observed properties of the +rare objects. Mergers represent a critical class +of short-lived epochs in the formation histories of +individual galaxies. Current determinations of the evolving numbers +of close galaxy pairs or morphological indicators of +mergers provide varying estimates for the +redshift dependence of the galaxy merger rate +\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. +The identification of merging +galaxy pairs as a function of separation, merger +mass ratio, and environment in the LSST data will enable +a full accounting of how galaxy mergers influence +the observed properties of galaxies as a function of +cosmic time. + +\subsection{Photometric Redshifts} +\label{sec:sci:gal:bkgnd:photoz} +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-z's). While spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra, photometric redshifts, instead, estimate the rough distance to an object based on broad-band photometric colors. This can be thought of as akin to a very low-resolution spectrum sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.~the 4000\AA\ and Lyman breaks), with each broad-band filter being a single pixel in the spectrum. By relying on imaging data alone, we are able to measure photo-z's for billions of galaxies in the LSST survey, at the cost of added uncertainty in the redshift estimates, and potential redshift degeneracies. + As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-z's is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it the incorrect luminosity via the distance modulus, and can bias estimates of the luminosity function; errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to an error in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. + In order to understand the biases and uncertainties inherent to photo-z's for a particular survey, we need to train the photo-z algorithms using galaxies with known redshifts. For a full characterization, a fully representative sub-sample of the underlying galaxy population is necessary; however, in practice, this is very difficult to achieve, due to limitations in both spectroscopic instrumentation and telescope time. We can attempt to identify and remove any biases due to incomplete training data using several redshift calibration techniques, the most prominent one relying on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts. A detailed plan describing the spectroscopic needs, for training and calibration, is laid out in \citet[]{Newman2015}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be functional in the near future. As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-z training, but also to those studying galaxy formation and evolution. In addition, any insights gained on galaxy formation and evolution during the course of the LSST survey can be used to improve photo-z algorithms. For example, improved spectral energy distribution evolution models would improve photo-z performance at high redshift. Or, observable quantities such as size and surface brightness may be incorporated as Bayesian priors on the photo-z's once their distributions are well understood. This mutual benefit between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both subjects as the survey progresses. + +\subsection{Science Book} +\label{sec:sci:gal:bkgnd:scibook} + +The LSST Science Book (\citealt{LSSTSciBook}) provided +detailed descriptions of foundationl science enabled +by LSST. The LSST Galaxies Science Collaboration authored +the Chapter 9 ``Galaxies'' of the Science Book, and the +a table of contents of that chapter follow below to +provide an example list of topics in extragalactic +science that LSST data will help revolutionize. The +interested reader is referred to the LSST Science +Book for more details. + + +\begin{enumerate} +\item Measurements, Detection, Photometry, Morphology +\item Demographics of Galaxy Populations +\begin{itemize} +\item Passively evolving galaxies +\item High-redshift star forming galaxies +\item Dwarf galaxies +\item Mergers and interactions +\end{itemize} +\item Distribution Functions and Scaling Relations +\begin{itemize} +\item Luminosity and size evolution +\item Relations between observables +\item Quantifying the Biases and Uncertainties +\end{itemize} +\item Galaxies in their Dark-Matter Context +\begin{itemize} +\item Measuring Galaxy Environments with LSST +\item The Galaxy-Halo Connection +\item Clusters and Cluster Galaxy Evolution +\item Probing Galaxy Evolution with Clustering Measurements +\item Measuring Angular Correlations with LSST, Cross-correlations +\end{itemize} +\item Galaxies at Extremely Low Surface Brightness +\begin{itemize} +\item Spiral Galaxies with LSB Disks +\item Dwarf Galaxies +\item Tidal Tails and Streams +\item Intracluster Light +\end{itemize} +\item Wide Area, Multiband Searches for High-Redshift Galaxies +\item Deep Drilling Fields +\item Galaxy Mergers and Merger Rates +\item Special Populations of Galaxies +\item Public Involvement +\end{enumerate} + + + + + From be0ae65675a8746fd78478e447a499c8ec0dcf88 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 19 Jul 2017 15:48:26 -0700 Subject: [PATCH 22/64] Working on final draft. --- VersionDate.tex | 4 +- abstract.tex | 10 +- apj.bst | 1 - authorlist.tex | 111 +- introduction/introduction.tex | 84 +- main.pdf | Bin 0 -> 315294 bytes main.tex | 84 + {2016 => old/2016}/Makefile | 0 {2016 => old/2016}/README.md | 0 {2016 => old/2016}/SciBook.bst | 0 {2016 => old/2016}/VersionDate.begin | 0 {2016 => old/2016}/VersionDate.end | 0 {2016 => old/2016}/VersionDate.tex | 0 {2016 => old/2016}/abstract.tex | 0 {2016 => old/2016}/apj.bst | 0 {2016 => old/2016}/authorlist.tex | 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old/task_lists/photo_z/photo_z.tex create mode 100644 old/task_lists/task_lists.tex create mode 100644 old/task_lists/tmc/tmc.tex create mode 100644 science_background/science_background.save.tex create mode 100644 task_lists/aux/aux.tex diff --git a/VersionDate.tex b/VersionDate.tex index f04b5c6..d64b751 100644 --- a/VersionDate.tex +++ b/VersionDate.tex @@ -1,4 +1,4 @@ \begin{center} -Version -March 21, 2017 +Version 1.0: +June 22, 2017 \end{center} diff --git a/abstract.tex b/abstract.tex index 86a51ae..5708d14 100644 --- a/abstract.tex +++ b/abstract.tex @@ -1,13 +1,15 @@ -\begin{center} -\vspace*{30mm} +\vspace*{30mm} +\begin{center} {\bf Abstract} +\end{center} \vspace*{5mm} +{\justify The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of galaxies, dark matter, and black holes over cosmic time. The LSST Galaxies Science Collaboration (LSST GSC) has identified a host of preparatory research tasks required to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. -This {\it Extragalactic Roadmap} provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The {\it Extragalactic Roadmap} will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era. -\end{center} +This {\it Galaxies Science Roadmap} provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The {\it Galaxies Science Roadmap} will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era. +} diff --git a/apj.bst b/apj.bst index f7a0aa6..8d3ac16 100644 --- a/apj.bst +++ b/apj.bst @@ -1,4 +1,3 @@ - %% $Log: apj.bst,v $ %% Revision 1.4 2002/06/18 16:37:48 alberto %% Add comma after first author in two-author reference diff --git a/authorlist.tex b/authorlist.tex index 3fcd06f..1b6a3ab 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -1,17 +1,102 @@ -Robertson, Brant$^{1}$, Banerji, M.$^{2}$, Cooper, Michael$^{3}$, Davies, R.$^{4}$, Ferguson, Henry C.$^{5}$, Kaviraj, S.$^{6}$, Lintott, C.$^{4}$, Lotz, J.$^{5}$, Newman, J.$^{7}$, Norman, D.$^{8}$, Padilla, N.$^{9}$, Schmidt, S.$^{10}$, Smith, G.~P.$^{11}$,Verma, A.$^{4}$, Working Group Participants, Collaboration Members +Robertson, Brant E.$^{1}$, +Banerji, Manda$^{2}$, +Cooper, Michael C.$^{3}$, +Davies, Roger$^{4}$, +Driver, Simon P.$^{5}$, +Ferguson, Annette$^{6}$, +Ferguson, Henry C.$^{7}$, +Gawiser, Eric$^{8}$, +Kaviraj, Sugata$^{9}$, +Knapen, Johan H.$^{10,11}$, +Lintott, Chris$^{4}$, +Lotz, Jennifer$^{7}$, +Newman, Jeffrey A.$^{12}$, +Norman, Dara J.$^{13}$, +Padilla, Nelson$^{14}$, +Schmidt, Samuel J.$^{15}$, +Smith, Graham P.,$^{16}$, +Tyson, J. Anthony$^{15}$, +Verma, Aprajita$^{4}$, +Zehavi, Idit$^{17}$, +Armus, Lee$^{18}$, +Avestruz, Camille$^{19}$, +Barrientos, L. Felipe$^{14}$, +Bowler, Rebecca A. A.$^{4}$, +Bremer, Malcolm N.$^{20}$, +Conselice, Christopher J.$^{21}$, +Davies, Jonathan$^{22}$, +Demarco, Ricardo$^{23}$, +Galaz, Gaspar$^{14}$, +Grazian, Andrea$^{24}$, +Holwerda, Benne W.$^{25}$, +Jarvis, Matt J.$^{4}$, +Kasliwal, Vishal$^{26,27,28}$, +Lacerna, Ivan$^{14}$, +Loveday, Jon$^{29}$, +Marshall, Phil$^{30}$, +Merlin, Emiliano$^{24}$, +Napolitano, Nicola R.$^{31}$, +Puzia, Thomas H.$^{14}$, +Robotham, Aaron$^{5}$, +Salim, Samir$^{32}$, +Sereno, Mauro$^{33}$, +Snyder, Gregory F.$^{7}$, +Stott, John P.$^{34}$, +Tissera, Patricia B.$^{35}$, +Werner, Norbert$^{36,37,38}$, +Yoachim, Peter$^{39}$, +Borne, Kirk D.$^{40}$, +and Members of the LSST Galaxies Science Collaboration \vspace*{5mm} -{\centering\it\small -$^{1}$University of California, Santa Cruz, -$^{2}$Cambridge University, -$^{3}$University of California, Irvine, -$^{4}$Oxford University, -$^{5}$Space Telescope Science Institute, -$^{6}$University of Hertfordshire, -$^{7}$University of Pittsburgh, -$^{8}$National Optical Astronomy Observatory, -$^{9}$Pontifica Universidad Catolica de Chile, -$^{10}$University of California, Davis, -$^{11}$University of Birmingham, +{\justify\it\small +$^{1}$Department of Astronomy and Astrophysics, University of California, Santa Cruz, Santa Cruz, CA 96054, USA, +$^{2}$Institute of Astronomy, Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB30HA, UK, +$^{3}$Department of Physics and Astronomy, University of California, Irvine, 4129 Frederick Reines Hall, Irvine, CA 92697, USA, +$^{4}$Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Rd., Oxford, OX1 3RH, UK, +$^{5}$International Centre for Radio Astronomy Research (ICRAR), University of Western Australia, Perth, Australia, WA 6009, Australia, +$^{6}$Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, UK, +$^{7}$Space Telescope Science Institute, 3700 San Martin Drive, Baltimore MD 21218, USA, +$^{8}$Rutgers University, 136 Frelinghuysen Rd., Piscataway, NJ 08854-8019, USA, +$^{9}$Centre for Astrophysics Research, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, UK, +$^{10}$Instituto de Astrof\'\i sica de Canarias, E-38200 La Laguna, Spain, +$^{11}$Departamento de Astrof\'\i sica, Universidad de La Laguna, E-38206 La Laguna, Spain, +$^{12}$University of Pittsburgh and PITT PACC, 3941 O{'}Hara St., Pittsburgh, PA 15260, USA, +$^{13}$NOAO, 950 N. Cherry Ave, Tucson, AZ 85719, USA, +$^{14}$ Instituto de Astrof\'\i sca, Pontificia Universidad, +Cat{\'{o}}lica Chile, Vicu{\~{n}}a Mackenna 4860, Santiago, Chile, +$^{15}$Department of Physics, University of California, Davis, One Shields Ave, Davis, CA, 95616, USA, +$^{16}$School of Physics and Astronomy, University of Birmingham, Edgbaston, B15 2TT, UK, +$^{17}$Department of Astronomy, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA, +$^{18}$IPAC/Caltech, 1200 E. California Blvd. MS314-6, Pasadena, CA 91125, USA, +$^{19}$Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Ave., Chicago, IL 60637, USA, +$^{20}$H.H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol, BS8 1TL, UK, +$^{21}$School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK, +$^{22}$Cardiff University, School of Physics and Astronomy, The Parade, Cardiff, CF22 3AA, UK, +$^{23}$Departamento de Astronomía, Universidad de Concepci{\'{o}}n,Casilla 160-C, Concepción, Chile, +$^{24}$INAF - Osservatorio Astronomico di Roma, Via Frascati, 33, I-00078, Monte Porzio Catone (Roma), Italy, +$^{25}$Department of Physics and Astronomy, 102 Natural Science Building, University of Louisville, Louisville KY 40292, USA, +$^{26}$Colfax International, 750 Palomar Avenue, Sunnyvale, CA 94085, USA, +$^{27}$University of Pennsylvania, Department of Physics \& Astronomy, 209 S 33rd St, Philadelphia, PA 19104, USA, +$^{28}$Princeton University, Department of Astrophysical Sciences; 4 Ivy Ln, Princeton, NJ 08544, USA, +$^{29}$Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QH, UK, +$^{30}$Kavli Institute for Particle Astrophysics and Cosmology, P.O. Box 20450, MS29, Stanford, CA 94309, USA, +$^{31}$INAF -Osservatorio Astronomico di Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy, +$^{32}$Indiana University, Department of Astronomy, Bloomington, IN 47405, USA, +$^{33}$INAF - Osservatorio Astronomico di Bologna; Dipartimento di Fisica e Astronomia, Universit\`a di Bologna Alma-Mater, via Piero Gobetti 93/3, I-40129 Bologna, Italy, +$^{34}$Department of Physics, Lancaster University, Lancaster LA1 4YB, UK, +$^{35}$Astrophysics Group, Department of Physics - Campus La Casona, Universidad Andres Bello, Fernandez Concha 700, Las Condes, Santiago, Chile, +$^{36}$1 MTA-Eotvos University Hot Universe Research Group, Pazmany Peter Setany 1/A, Budapest, 1117, Hungary, +$^{37}$Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, Brno, 611 37, Czech Republic, +$^{38}$School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan, +$^{39}$University of Washington, Box 351580, U.W. Seattle, WA 98195-1580, USA, +$^{40}$Booz Allen Hamilton, 308 Sentinel Drive, Suite 100, Annapolis Junction, MD 20701, USA + + + + + + + } diff --git a/introduction/introduction.tex b/introduction/introduction.tex index 0bc3019..c56c1ba 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -5,67 +5,73 @@ \chapter[Introduction]{Introduction} \label{ch:intro} +{\justify The Large Synoptic Survey Telescope (LSST) is a wide-field, ground-based telescope, designed to image a substantial fraction of the sky in six optical -bands every few nights. It is planned to operate for a decade allowing the -stacked images to detect galaxies to redshifts well beyond unity. The LSST and -the survey are designed to meet the requirements (Ivezic \& the LSST Science -Collaboration 2011) of a broad range of science goals in astronomy, astrophysics -and cosmology. The LSST was the top-ranked large ground-based initiative in the +bands every few nights. +The observatory will operate for at least a decade, allowing the +stacked images to detect galaxies to redshifts well beyond unity. LSST and +its Deep-Wide-Fast and Deep Drilling Field surveys will meet +the requirements of a broad range of science goals in astronomy, astrophysics and cosmology +\citep{ivezic2008a}. +The LSST ranked first among large ground-based initiatives in the 2010 National Academy of Sciences decadal survey in astronomy and astrophysics, -and is on track to begin the survey early in the next decade. +and will begin survey operations early in the next decade. +This document, the {\it Large Synoptic Survey Telescope Galaxies Science Roadmap}, outlines critical preparatory research efforts needed +to leverage fully the power of LSST for extragalactic science. In 2008, eleven separate quasi-independent science collaborations were formed to focus on a broad range of topics in astronomy and cosmology that the LSST could -address. Members of these collaborations have been instrumental in helping to -develop the science case for LSST (encapsulated in the LSST Science Book), to +address. Members of these collaborations have proven instrumental in helping to +develop the science case for LSST (encapsulated in the LSST Science Book; +\citet{LSSTSciBook}), to refine the concepts for the survey and for the data processing, and to educate other scientists and the public about the promise of this unique observatory. The Dark Energy Science Collaboration (DESC) has taken the next logical step beyond the science book. They identified they most critical -challenges that will need to be overcome to realize LSST’s potential for -measuring the effects of Dark Energy. They looked at five complementary -techniques for tackling dark energy, and outlined high-priority tasks for the -science collaboration during construction. They designated sixteen working -groups (some of which already existed) to coordinate the work. This roadmap has -been documented in a 133-page white paper (arxiv.org/abs/1211.0310). The white +challenges the community will need to overcome +to realize LSST’s potential for +measuring the nature and effects of Dark Energy. The +DESC looked at five complementary +techniques for tackling dark energy, and outlined high-priority tasks for their +Science Collaboration during construction. The DESC designated sixteen +new and existing working +groups to coordinate the work. The DESC documented these efforts +in a 133-page white paper \citep{LSSTDESC}. The DESC white paper provides a guide for investigators looking for ways to contribute to the -overall investigation. It may help in efforts to obtain funding, because it -provides clear indication of the importance of the advance work and how the -pieces fit together. +overall DESC preparatory science effort, +indicates clearly the importance of the advance work, and +connects individual research projects together into a broader +enterprise to enable Dark Energy science with LSST. -The investigation of Dark Energy is only one topic for LSST. It is important to -develop similarly concrete roadmaps for work in other areas. After some -discussion among the collaborations, it appears useful in some cases for -different science collaborations to join forces on a single whitepaper. This is -particularly true for topics that involve observations of distant galaxies. With -the advent of the DESC, some of the science goals of the large-scale-structure, -weak-lensing, and strong-lensing collaborations have found a new home. The -remaining science goals of those collaborations tend to be focused on galaxy -evolution and dark matter. Two other collaborations: AGN and Galaxies, also have -those topics as major themes. This roadmap identifies the major high-level +Following the lead of DESC, several other LSST community organizations +including the AGN, Milky Way and Local Volume, and Solar System Science +Collaborations, +started to develop Roadmaps to outline critical preparatory tasks in +their science domains. +This document, led by members of the LSST Galaxies Science Collaboration, +acts as an Roadmap for extragalactic science covering +galaxy formation and evolution writ large, the influence of dark matter structure +formation on the properties of galaxy populations, and the impact of supermassive +black holes on their host galaxies. +This Roadmap identifies the major high-level science themes of these investigations, outlines how complementary techniques -will contribute, and identifies areas where advance work is essential. For this -advance work, the emphasis is on areas that are not adequately covered in the -DESC roadmap. +will contribute, and identifies areas where advance work will prove essential. For this +advance work, the Extragalactic Roadmap emphasizes areas that are not adequately +covered in the DESC Roadmap. %As convenient shorthand, we use the acronym GALLA (Galaxies, AGN, Lensing %Large-scale Structure and Astro-informatics) joint roadmap of the overlapping %science collaborations. Chapter \ref{ch:science_background} gives a brief summary of the science background. -Many of the themes and projects are already set out in the Science Book, where more -detail is provided for many of the science investigations. +Many of the themes and projects are already set out in the LSST Science Book, +which provides more details for many of the science investigations. Chapter \ref{ch:task_lists} presents preparatory science tasks for Extragalactic science with LSST. These tasks are organized by science topic. The science task list content assumes that the work plan of the DESC will be executed and that the resulting software and other data products resulting from the DESC efforts will be made available to the other science collaborations. -%Chapter \ref{ch:roadmap} -%sets out the highest priority preparatory work to enable these investigations. -%These tasks -%are laid out on the assumption that the work plan of the DESC will be carried out -%and that software and data products resulting from that work will be available to -%other science collaborations. 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+\usepackage{float} +\usepackage[colorlinks=true, allcolors=blue]{hyperref} +\usepackage[document]{ragged2e} +\begin{document} +\input{journal_macros} + + +%---------------------------------------------------------------------------------------- +% TITLE PAGE +%---------------------------------------------------------------------------------------- + +{\Huge Large Synoptic Survey Telescope} +\linebreak +\linebreak +{\Huge Galaxies Science Roadmap} +\linebreak +\linebreak +{\centering +\input{authorlist} +} +\vfill + +%---------------------------------------------------------------------------------------- +% COPYRIGHT PAGE +%---------------------------------------------------------------------------------------- +\newpage +\thispagestyle{empty} + +\noindent +{\justify +The {\it Large Synoptic Survey Telescope Galaxies Science Roadmap} represents the collective efforts of more than one hundred scientists to define the critical research activities to prepare our field to maximize +the science return of the LSST dataset. We want to thank the LSST Corporation for their +support in developing this Roadmap and for supporting LSST-related science more broadly. +We also wish to thank the LSST Galaxies Science Collaboration members for their efforts +over the years in developing the case for extragalactic science with LSST. Lastly, we +wish to thank Harry Ferguson for his continued efforts to organize this document. +} +\vspace{1in} + +Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}) and the LSST Galaxies Science Collaboration ({\tt lsst-galaxies@lsstcorp.org}). +\vspace{1in} +\input{VersionDate} + + +%---------------------------------------------------------------------------------------- +% Abstract +%---------------------------------------------------------------------------------------- + +\include{abstract} + +%---------------------------------------------------------------------------------------- +% Table of Contents +%---------------------------------------------------------------------------------------- + +\tableofcontents % Print the table of contents + + +%---------------------------------------------------------------------------------------- +% Chapters +%---------------------------------------------------------------------------------------- + +\include{introduction/introduction} +\include{science_background/science_background} +\include{task_lists/task_lists} + +%--------------------------------------------------------------------------------------- +% References +%--------------------------------------------------------------------------------------- +\bibliography{references} + + +%---END--- +\end{document} + + diff --git a/2016/Makefile b/old/2016/Makefile similarity index 100% rename from 2016/Makefile rename to old/2016/Makefile diff --git a/2016/README.md b/old/2016/README.md similarity index 100% rename from 2016/README.md rename to old/2016/README.md diff --git a/2016/SciBook.bst b/old/2016/SciBook.bst similarity index 100% rename from 2016/SciBook.bst rename to old/2016/SciBook.bst diff --git a/2016/VersionDate.begin b/old/2016/VersionDate.begin similarity index 100% rename from 2016/VersionDate.begin rename to 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The +LSST Galaxies Science Collaboration (LSST GSC) has identified a host of preparatory research tasks required +to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. +This {\it Extragalactic Roadmap} provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The {\it Extragalactic Roadmap} will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era. +\end{center} diff --git a/old/apj.bst b/old/apj.bst new file mode 100644 index 0000000..f7a0aa6 --- /dev/null +++ b/old/apj.bst @@ -0,0 +1,1629 @@ + +%% $Log: apj.bst,v $ +%% Revision 1.4 2002/06/18 16:37:48 alberto +%% Add comma after first author in two-author reference +%% Fix courtesy of Tim Robishaw +%% +%% Revision 1.3 2000/04/20 22:17:50 jbaker +%% Fixed INBOOK bug, now works essentially like BOOK. +%% +%% Revision 1.2 1998/08/30 22:35:45 jbaker +%% Added RCS keywords. +%% +%% 1998/08/12 J Baker +%% Tweaked by hand to get correct results for ApJ. Added functions from +%% astrobib. + + +%% +%% This is file `apj.bst', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% merlin.mbs (with options: `,ay,nat,nm-rev,nmdash,dt-beg,yr-per,note-yr,atit-u,jtit-x,jttl-rm,thtit-a,vnum-x,volp-com,jpg-1,pp-last,btit-rm,add-pub,pub-par,pre-edn,edby,edbyx,blk-com,fin-bare,ppx,ed,abr,ord,jabr,amper,em-x') +%% ---------------------------------------- +%% *** Bibliographic Style for ApJ *** +%% + %------------------------------------------------------------------- + % The original source file contains the following version information: + % \ProvidesFile{merlin.mbs}[1998/02/25 3.85a (PWD)] + % + % NOTICE: + % This file may be used for non-profit purposes. + % It may not be distributed in exchange for money, + % other than distribution costs. + % + % The author provides it `as is' and does not guarantee it in any way. + % + % Copyright (C) 1994-98 Patrick W. Daly + %------------------------------------------------------------------- + % For use with BibTeX version 0.99a or later + %------------------------------------------------------------------- + % This bibliography style file is intended for texts in ENGLISH + % This is an author-year citation style bibliography. As such, it is + % non-standard LaTeX, and requires a special package file to function properly. + % Such a package is natbib.sty by Patrick W. Daly + % The form of the \bibitem entries is + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Smith]{key}... + % The essential feature is that the label (the part in brackets) consists + % of the author names, as they should appear in the citation, with the year + % in parentheses following. There must be no space before the opening + % parenthesis! + % With natbib v5.3, a full list of authors may also follow the year. + % In natbib.sty, it is possible to define the type of enclosures that is + % really wanted (brackets or parentheses), but in either case, there must + % be parentheses in the label. + % The \cite command functions as follows: + % \citet{key} ==>> Jones et al. (1990) + % \citet*{key} ==>> Jones, Baker, and Smith (1990) + % \citep{key} ==>> (Jones et al., 1990) + % \citep*{key} ==>> (Jones, Baker, and Smith, 1990) + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.][]{key} ==>> (e.g. Jones et al., 1990) + % \citep[e.g.][p. 32]{key} ==>> (e.g. Jones et al., p. 32) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Smith + % \citeyear{key} ==>> 1990 + %--------------------------------------------------------------------- + +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ duplicate$ empty$ + 'pop$ + 'write$ + if$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {add.blank} +{ " " * before.all 'output.state := +} + +FUNCTION {date.block} +{ + skip$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ skip$ } + +FUNCTION {capitalize} +{ "u" change.case$ "t" change.case$ } + +FUNCTION {space.word} +{ " " swap$ * " " * } + + % Here are the language-specific definitions for explicit words. + % Each function has a name bbl.xxx where xxx is the English word. + % The language selected here is ENGLISH +FUNCTION {bbl.and} +{ "and"} + +FUNCTION {bbl.editors} +{ "eds." } + +FUNCTION {bbl.editor} +{ "ed." } + +FUNCTION {bbl.edby} +{ "edited by" } + +FUNCTION {bbl.edition} +{ "edn." } + +FUNCTION {bbl.volume} +{ "Vol." } + +FUNCTION {bbl.of} +{ "of" } + +FUNCTION {bbl.number} +{ "no." } + +FUNCTION {bbl.nr} +{ "no." } + +FUNCTION {bbl.in} +{ "in" } + +FUNCTION {bbl.pages} +{ "" } + +FUNCTION {bbl.page} +{ "" } + +FUNCTION {bbl.chapter} +{ "Ch." } +%{ "chap." } + +FUNCTION {bbl.techrep} +{ "Tech. Rep." } + +FUNCTION {bbl.mthesis} +{ "Master's thesis" } + +FUNCTION {bbl.phdthesis} +{ "PhD thesis" } + +FUNCTION {bbl.first} +{ "1st" } + +FUNCTION {bbl.second} +{ "2nd" } + +FUNCTION {bbl.third} +{ "3rd" } + +FUNCTION {bbl.fourth} +{ "4th" } + +FUNCTION {bbl.fifth} +{ "5th" } + +FUNCTION {bbl.st} +{ "st" } + +FUNCTION {bbl.nd} +{ "nd" } + +FUNCTION {bbl.rd} +{ "rd" } + +FUNCTION {bbl.th} +{ "th" } + +MACRO {jan} {"Jan."} + +MACRO {feb} {"Feb."} + +MACRO {mar} {"Mar."} + +MACRO {apr} {"Apr."} + +MACRO {may} {"May"} + +MACRO {jun} {"Jun."} + +MACRO {jul} {"Jul."} + +MACRO {aug} {"Aug."} + +MACRO {sep} {"Sep."} + +MACRO {oct} {"Oct."} + +MACRO {nov} {"Nov."} + +MACRO {dec} {"Dec."} + +FUNCTION {eng.ord} +{ duplicate$ "1" swap$ * + #-2 #1 substring$ "1" = + { bbl.th * } + { duplicate$ #-1 #1 substring$ + duplicate$ "1" = + { pop$ bbl.st * } + { duplicate$ "2" = + { pop$ bbl.nd * } + { "3" = + { bbl.rd * } + { bbl.th * } + if$ + } + if$ + } + if$ + } + if$ +} + +MACRO {acmcs} {"ACM Comput. Surv."} + +MACRO {acta} {"Acta Inf."} + +MACRO {cacm} {"Commun. ACM"} + +MACRO {ibmjrd} {"IBM J. Res. Dev."} + +MACRO {ibmsj} {"IBM Syst.~J."} + +MACRO {ieeese} {"IEEE Trans. Softw. Eng."} + +MACRO {ieeetc} {"IEEE Trans. Comput."} + +MACRO {ieeetcad} + {"IEEE Trans. Comput.-Aided Design Integrated Circuits"} + +MACRO {ipl} {"Inf. Process. Lett."} + +MACRO {jacm} {"J.~ACM"} + +MACRO {jcss} {"J.~Comput. Syst. Sci."} + +MACRO {scp} {"Sci. Comput. Programming"} + +MACRO {sicomp} {"SIAM J. Comput."} + +MACRO {tocs} {"ACM Trans. Comput. Syst."} + +MACRO {tods} {"ACM Trans. Database Syst."} + +MACRO {tog} {"ACM Trans. Gr."} + +MACRO {toms} {"ACM Trans. Math. Softw."} + +MACRO {toois} {"ACM Trans. Office Inf. Syst."} + +MACRO {toplas} {"ACM Trans. Prog. Lang. Syst."} + +MACRO {tcs} {"Theoretical Comput. Sci."} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + + numnames 'namesleft := + { namesleft #0 > } + { + s nameptr "{vv~}{ll}{, jj}{, f.}" format.name$ 't := + nameptr #1 > + { + #8 numnames < + { #0 'namesleft := } + 'skip$ + if$ + namesleft #1 > + { ", " * t * } + { + numnames #1 > +%% AA 6/18/2002 +%% This fix courtesy of Tim Robishaw : +%% Original version left comma out after initials of first author +%% for two-author papers!! +%% numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + %t "others" = + #8 numnames < + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.names.ed} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{f.~}{vv~}{ll}{, jj}" + format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", " * bbl.editors * } + { ", " * bbl.editor * } + if$ + } + if$ +} + +FUNCTION {format.in.editors} +{ editor empty$ + { "" } + { editor format.names.ed + } + if$ +} + +FUNCTION {format.note} +{ note empty$ + { "" } + { note #1 #1 substring$ + duplicate$ "{" = + 'skip$ + { output.state mid.sentence = + { "l" } + { "u" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title + } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.key.full} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.key.full} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {editor.key.full} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.full + { type$ "proceedings" = + 'editor.key.full + 'author.key.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[{" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "}]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {word.in} +{ bbl.in + " " * } + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * "; set to ????" * warning$ + pop$ "????" } + 'skip$ + if$ + extra.label * + before.all 'output.state := + after.sentence 'output.state := +} + +FUNCTION {format.btitle} +{ title +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { bbl.volume volume tie.or.space.connect + series empty$ + 'skip$ + { bbl.of space.word * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { bbl.number } + { bbl.number capitalize } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { bbl.in space.word * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {is.num} +{ chr.to.int$ + duplicate$ "0" chr.to.int$ < not + swap$ "9" chr.to.int$ > not and +} + +FUNCTION {extract.num} +{ duplicate$ 't := + "" 's := + { t empty$ not } + { t #1 #1 substring$ + t #2 global.max$ substring$ 't := + duplicate$ is.num + { s swap$ * 's := } + { pop$ "" 't := } + if$ + } + while$ + s empty$ + 'skip$ + { pop$ s } + if$ +} + +FUNCTION {convert.edition} +{ edition extract.num "l" change.case$ 's := + s "first" = s "1" = or + { bbl.first 't := } + { s "second" = s "2" = or + { bbl.second 't := } + { s "third" = s "3" = or + { bbl.third 't := } + { s "fourth" = s "4" = or + { bbl.fourth 't := } + { s "fifth" = s "5" = or + { bbl.fifth 't := } + { s #1 #1 substring$ is.num + { s eng.ord 't := } + { edition 't := } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + t +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { convert.edition "l" change.case$ " " * bbl.edition * } + { convert.edition "t" change.case$ " " * bbl.edition * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check +% { bbl.pages pages n.dashify tie.or.space.connect } +% { bbl.page pages tie.or.space.connect } + { pages n.dashify } + { pages } + if$ + } + if$ +} + +FUNCTION {first.page} +{ 't := + "" + { t empty$ not t #1 #1 substring$ "-" = not and } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + while$ +} + +FUNCTION {format.journal.pages} +{ pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { + ", " * + pages first.page * + } + if$ + } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + { "" } + { type empty$ + { bbl.chapter } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { word.in booktitle emphasize * } + { word.in booktitle emphasize * + ", " * + editor num.names$ #1 > + { bbl.editors } + { bbl.editor } + if$ + * " " * + format.in.editors * + } + if$ + } + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { bbl.techrep } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + word.in + } + { bbl.volume volume tie.or.space.connect + bbl.of space.word * + } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} + +FUNCTION {format.publisher} +{ publisher empty$ + { "empty publisher in " cite$ * warning$ } + 'skip$ + if$ + "" + address empty$ publisher empty$ and + 'skip$ + { + add.blank "(" * + address empty$ + 'skip$ + { address * } + if$ + publisher empty$ + 'skip$ + { address empty$ + 'skip$ + { ": " * } + if$ + publisher * + } + if$ + ")" * + } + if$ + output +} + +STRINGS {oldname} + +FUNCTION {name.or.dash} +{ 's := + oldname empty$ + { s 'oldname := s } + { s oldname = + { "---" } + { s 'oldname := s } + if$ + } + if$ +} + +%%%%%%%% Functions added from astrobib + +FUNCTION {format.edn.btitle} % Title should be on stack. +{ duplicate$ empty$ edition empty$ or + 'skip$ + { ", " * format.edition * } + if$ +} + +FUNCTION {format.ed.booktitle} % The title should be on the stack. +{ duplicate$ empty$ + { "no book title in " cite$ * warning$ "" pop$ } + { editor empty$ + author empty$ or % Empty author means editor already given. + 'format.edn.btitle + { format.edn.btitle ", " * bbl.editor * " " * format.in.editors * } + if$ + } + if$ +} + +FUNCTION {format.full.book.spec} % The title should be on the stack. +{ series empty$ + { format.ed.booktitle + volume empty$ + { number empty$ + 'skip$ + { " there's a number but no series in " cite$ * warning$ + " No." number tie.or.space.connect * } + if$ + } + { ", Vol." volume tie.or.space.connect * + number empty$ + 'skip$ + {"Both volume and number fields in " * cite$ * warning$ } + if$ + } + if$ + } + { volume empty$ + { format.ed.booktitle ", " * series * + number empty$ + 'skip$ + { " No." number tie.or.space.connect * } + if$ + } + { series ", Vol." volume tie.or.space.connect * + ", " * swap$ format.ed.booktitle * + number empty$ + 'skip$ + {"Both volume and number fields in " * cite$ * warning$ } + if$ + } + if$ + } + if$ +} + +%%%%%%% End of functions from astrobib + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + crossref missing$ + { journal + "journal" output.check + format.vol.num.pages output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + format.journal.pages + format.note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + name.or.dash + } + { format.authors output.nonnull + name.or.dash + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% crossref missing$ +% { format.bvolume output +% format.number.series output +% format.edition output + format.publisher +% } +% { +% format.book.crossref output.nonnull +% } +% if$ + format.pages output + format.note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title "title" output.check + howpublished output + address output + format.note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + name.or.dash + } + { format.authors output.nonnull + name.or.dash + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% crossref missing$ +% { +% format.bvolume output +% format.chapter.pages "chapter and pages" output.check +% format.number.series output +% format.edition output + format.publisher +% } +% { +% format.chapter.pages "chapter and pages" output.check +% format.book.crossref output.nonnull +% } +% if$ + format.pages "pages" output.check + format.note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + bbl.in " " * booktitle format.full.book.spec * output +% crossref missing$ +% { format.in.ed.booktitle "booktitle" output.check +% format.bvolume output +% format.number.series output +% format.edition output +% format.chapter.pages output + format.publisher +% } +% { format.incoll.inproc.crossref output.nonnull +% format.chapter.pages output +% } +% if$ + format.pages "pages" output.check + format.note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output % added + format.date "year" output.check + date.block + bbl.in " " * booktitle format.full.book.spec * output +% crossref missing$ +% { format.in.ed.booktitle "booktitle" output.check +% format.bvolume output +% format.number.series output + publisher empty$ + { organization output + address output + } + { organization output + format.publisher + } + if$ +% } +% { format.incoll.inproc.crossref output.nonnull +% } +% if$ + format.pages output + format.note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.btitle "title" output.check + format.edition output + organization output + address output + format.note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + bbl.mthesis format.thesis.type output.nonnull + school "school" output.check + address output + format.note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title output + howpublished output + format.note output + fin.entry +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + bbl.phdthesis format.thesis.type output.nonnull + school "school" output.check + address output + format.note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output + organization format.key output } + { format.editors output } + if$ +% format.editors output +% editor format.key output + name.or.dash + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% format.bvolume output +% format.number.series output + publisher empty$ not % No need for warning if no pub. + { format.publisher } + { editor empty$ % For empty editor, organization was already given. + 'skip$ + { organization output } + if$ + address output + } + if$ +% address output +% organization output +% publisher output + format.pages output + format.note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title "title" output.check + format.tr.number output.nonnull + institution "institution" output.check + address output + format.note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + format.note "note" output.check + fin.entry +} + +FUNCTION {default.type} { misc } + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ + " {et~al.}" * + } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { + " {et~al.}" * + } + { " \& " * s #2 "{vv~}{ll}" format.name$ + * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.label} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.label + 'author.key.label + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + { pop$ "????" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv{ } }{ll{ }}{ f{ }}{ jj{ }}" + format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { t sortify * } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.sort} +{ editor empty$ + { key empty$ + { "to sort, need editor or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.sort + 'author.sort + if$ + } + if$ + #1 entry.max$ substring$ + 'sort.label := + sort.label + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { last.label next.extra } + +INTEGERS { last.extra.num number.label } + +FUNCTION {initialize.extra.label.stuff} +{ #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.extra.label.stuff} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} +%% End of customized bst file +%% +%% End of file `apj.bst'. diff --git a/old/authorlist.tex b/old/authorlist.tex new file mode 100644 index 0000000..3fcd06f --- /dev/null +++ b/old/authorlist.tex @@ -0,0 +1,17 @@ +Robertson, Brant$^{1}$, Banerji, M.$^{2}$, Cooper, Michael$^{3}$, Davies, R.$^{4}$, Ferguson, Henry C.$^{5}$, Kaviraj, S.$^{6}$, Lintott, C.$^{4}$, Lotz, J.$^{5}$, Newman, J.$^{7}$, Norman, D.$^{8}$, Padilla, N.$^{9}$, Schmidt, S.$^{10}$, Smith, G.~P.$^{11}$,Verma, A.$^{4}$, Working Group Participants, Collaboration Members + +\vspace*{5mm} + +{\centering\it\small +$^{1}$University of California, Santa Cruz, +$^{2}$Cambridge University, +$^{3}$University of California, Irvine, +$^{4}$Oxford University, +$^{5}$Space Telescope Science Institute, +$^{6}$University of Hertfordshire, +$^{7}$University of Pittsburgh, +$^{8}$National Optical Astronomy Observatory, +$^{9}$Pontifica Universidad Catolica de Chile, +$^{10}$University of California, Davis, +$^{11}$University of Birmingham, +} diff --git a/exgal_roadmap.pdf b/old/exgal_roadmap.pdf similarity index 100% rename from exgal_roadmap.pdf rename to old/exgal_roadmap.pdf diff --git a/exgal_roadmap.tex b/old/exgal_roadmap.tex similarity index 100% rename from exgal_roadmap.tex rename to old/exgal_roadmap.tex diff --git a/old/introduction/introduction.tex b/old/introduction/introduction.tex new file mode 100644 index 0000000..0bc3019 --- /dev/null +++ b/old/introduction/introduction.tex @@ -0,0 +1,71 @@ +% LSST Extragalactic Roadmap +% Chapter: Introduction +% First draft by + +\chapter[Introduction]{Introduction} +\label{ch:intro} + +The Large Synoptic Survey Telescope (LSST) is a wide-field, ground-based +telescope, designed to image a substantial fraction of the sky in six optical +bands every few nights. It is planned to operate for a decade allowing the +stacked images to detect galaxies to redshifts well beyond unity. The LSST and +the survey are designed to meet the requirements (Ivezic \& the LSST Science +Collaboration 2011) of a broad range of science goals in astronomy, astrophysics +and cosmology. The LSST was the top-ranked large ground-based initiative in the +2010 National Academy of Sciences decadal survey in astronomy and astrophysics, +and is on track to begin the survey early in the next decade. + +In 2008, eleven separate quasi-independent science collaborations were formed to +focus on a broad range of topics in astronomy and cosmology that the LSST could +address. Members of these collaborations have been instrumental in helping to +develop the science case for LSST (encapsulated in the LSST Science Book), to +refine the concepts for the survey and for the data processing, and to educate +other scientists and the public about the promise of this unique observatory. + +The Dark Energy Science Collaboration (DESC) has taken the +next logical step beyond the science book. They identified they most critical +challenges that will need to be overcome to realize LSST’s potential for +measuring the effects of Dark Energy. They looked at five complementary +techniques for tackling dark energy, and outlined high-priority tasks for the +science collaboration during construction. They designated sixteen working +groups (some of which already existed) to coordinate the work. This roadmap has +been documented in a 133-page white paper (arxiv.org/abs/1211.0310). The white +paper provides a guide for investigators looking for ways to contribute to the +overall investigation. It may help in efforts to obtain funding, because it +provides clear indication of the importance of the advance work and how the +pieces fit together. + +The investigation of Dark Energy is only one topic for LSST. It is important to +develop similarly concrete roadmaps for work in other areas. After some +discussion among the collaborations, it appears useful in some cases for +different science collaborations to join forces on a single whitepaper. This is +particularly true for topics that involve observations of distant galaxies. With +the advent of the DESC, some of the science goals of the large-scale-structure, +weak-lensing, and strong-lensing collaborations have found a new home. The +remaining science goals of those collaborations tend to be focused on galaxy +evolution and dark matter. Two other collaborations: AGN and Galaxies, also have +those topics as major themes. This roadmap identifies the major high-level +science themes of these investigations, outlines how complementary techniques +will contribute, and identifies areas where advance work is essential. For this +advance work, the emphasis is on areas that are not adequately covered in the +DESC roadmap. +%As convenient shorthand, we use the acronym GALLA (Galaxies, AGN, Lensing +%Large-scale Structure and Astro-informatics) joint roadmap of the overlapping +%science collaborations. + +Chapter \ref{ch:science_background} gives a brief summary of the science background. +Many of the themes and projects are already set out in the Science Book, where more +detail is provided for many of the science investigations. +Chapter \ref{ch:task_lists} presents preparatory science tasks for +Extragalactic science with LSST. These tasks are organized by science topic. +The science task list content assumes that the work plan of the DESC will be executed +and that the resulting software and other data products resulting from the DESC +efforts will be made available to the other science collaborations. +%Chapter \ref{ch:roadmap} +%sets out the highest priority preparatory work to enable these investigations. +%These tasks +%are laid out on the assumption that the work plan of the DESC will be carried out +%and that software and data products resulting from that work will be available to +%other science collaborations. The Appendix \ref{ch:task_lists} organizes the tasks +%by science topic and desribes them in more detail. + diff --git a/old/journal_macros.tex b/old/journal_macros.tex new file mode 100644 index 0000000..73faeb0 --- /dev/null +++ b/old/journal_macros.tex @@ -0,0 +1,105 @@ +% +% These Macros are taken from the AAS TeX macro package version 5.2 +% and are compatible with the macros in the A&A document class +% version 7.0 +% Include this file in your LaTeX source only if you are not using +% the AAS TeX macro package or the A&A document class and need to +% resolve the macro definitions in the TeX/BibTeX entries returned by +% the ADS abstract service. +% +% If you plan not to use this file to resolve the journal macros +% rather than the whole AAS TeX macro package, you should save the +% file as ``aas_macros.sty'' and then include it in your LaTeX paper +% by using a construct such as: +% \documentstyle[11pt,aas_macros]{article} +% +% For more information on the AASTeX and A&A packages, please see: +% http://journals.aas.org/authors/aastex.html +% ftp://ftp.edpsciences.org/pub/aa/readme.html +% For more information about ADS abstract server, please see: +% http://adsabs.harvard.edu/ads_abstracts.html +% + +% Abbreviations for journals. The object here is to provide authors +% with convenient shorthands for the most "popular" (often-cited) +% journals; the author can use these markup tags without being concerned +% about the exact form of the journal abbreviation, or its formatting. +% It is up to the keeper of the macros to make sure the macros expand +% to the proper text. If macro package writers agree to all use the +% same TeX command name, authors only have to remember one thing, and +% the style file will take care of editorial preferences. This also +% applies when a single journal decides to revamp its abbreviating +% scheme, as happened with the ApJ (Abt 1991). + +\def\refj@jnl#1{{\rm#1}} + +\def\aj{\refj@jnl{AJ}} % Astronomical Journal +\def\actaa{\refj@jnl{Acta Astron.}} % Acta Astronomica +\def\araa{\refj@jnl{ARA\&A}} % Annual Review of Astron and Astrophys +\def\apj{\refj@jnl{ApJ}} % Astrophysical Journal +\def\apjl{\refj@jnl{ApJ}} % Astrophysical Journal, Letters +\def\apjs{\refj@jnl{ApJS}} % Astrophysical Journal, Supplement +\def\ao{\refj@jnl{Appl.~Opt.}} % Applied Optics +\def\apss{\refj@jnl{Ap\&SS}} % Astrophysics and Space Science +\def\aap{\refj@jnl{A\&A}} % Astronomy and Astrophysics +\def\aapr{\refj@jnl{A\&A~Rev.}} % Astronomy and Astrophysics Reviews +\def\aaps{\refj@jnl{A\&AS}} % Astronomy and Astrophysics, Supplement +\def\azh{\refj@jnl{AZh}} % Astronomicheskii Zhurnal +\def\baas{\refj@jnl{BAAS}} % Bulletin of the AAS +\def\bac{\refj@jnl{Bull. astr. Inst. Czechosl.}} + % Bulletin of the Astronomical Institutes of Czechoslovakia +\def\caa{\refj@jnl{Chinese Astron. Astrophys.}} + % Chinese Astronomy and Astrophysics +\def\cjaa{\refj@jnl{Chinese J. Astron. Astrophys.}} + % Chinese Journal of Astronomy and Astrophysics +\def\icarus{\refj@jnl{Icarus}} % Icarus +\def\jcap{\refj@jnl{J. Cosmology Astropart. Phys.}} + % Journal of Cosmology and Astroparticle Physics +\def\jrasc{\refj@jnl{JRASC}} % Journal of the RAS of Canada +\def\memras{\refj@jnl{MmRAS}} % Memoirs of the RAS +\def\mnras{\refj@jnl{MNRAS}} % Monthly Notices of the RAS +\def\na{\refj@jnl{New A}} % New Astronomy +\def\nar{\refj@jnl{New A Rev.}} % New Astronomy Review +\def\pra{\refj@jnl{Phys.~Rev.~A}} % Physical Review A: General Physics +\def\prb{\refj@jnl{Phys.~Rev.~B}} % Physical Review B: Solid State +\def\prc{\refj@jnl{Phys.~Rev.~C}} % Physical Review C +\def\prd{\refj@jnl{Phys.~Rev.~D}} % Physical Review D +\def\pre{\refj@jnl{Phys.~Rev.~E}} % Physical Review E +\def\prl{\refj@jnl{Phys.~Rev.~Lett.}} % Physical Review Letters +\def\pasa{\refj@jnl{PASA}} % Publications of the Astron. Soc. of Australia +\def\pasp{\refj@jnl{PASP}} % Publications of the ASP +\def\pasj{\refj@jnl{PASJ}} % Publications of the ASJ +\def\rmxaa{\refj@jnl{Rev. Mexicana Astron. Astrofis.}}% + % Revista Mexicana de Astronomia y Astrofisica +\def\qjras{\refj@jnl{QJRAS}} % Quarterly Journal of the RAS +\def\skytel{\refj@jnl{S\&T}} % Sky and Telescope +\def\solphys{\refj@jnl{Sol.~Phys.}} % Solar Physics +\def\sovast{\refj@jnl{Soviet~Ast.}} % Soviet Astronomy +\def\ssr{\refj@jnl{Space~Sci.~Rev.}} % Space Science Reviews +\def\zap{\refj@jnl{ZAp}} % Zeitschrift fuer Astrophysik +\def\nat{\refj@jnl{Nature}} % Nature +\def\iaucirc{\refj@jnl{IAU~Circ.}} % IAU Cirulars +\def\aplett{\refj@jnl{Astrophys.~Lett.}} % Astrophysics Letters +\def\apspr{\refj@jnl{Astrophys.~Space~Phys.~Res.}} + % Astrophysics Space Physics Research +\def\bain{\refj@jnl{Bull.~Astron.~Inst.~Netherlands}} + % Bulletin Astronomical Institute of the Netherlands +\def\fcp{\refj@jnl{Fund.~Cosmic~Phys.}} % Fundamental Cosmic Physics +\def\gca{\refj@jnl{Geochim.~Cosmochim.~Acta}} % Geochimica Cosmochimica Acta +\def\grl{\refj@jnl{Geophys.~Res.~Lett.}} % Geophysics Research Letters +\def\jcp{\refj@jnl{J.~Chem.~Phys.}} % Journal of Chemical Physics +\def\jgr{\refj@jnl{J.~Geophys.~Res.}} % Journal of Geophysics Research +\def\jqsrt{\refj@jnl{J.~Quant.~Spec.~Radiat.~Transf.}} + % Journal of Quantitiative Spectroscopy and Radiative Transfer +\def\memsai{\refj@jnl{Mem.~Soc.~Astron.~Italiana}} + % Mem. Societa Astronomica Italiana +\def\nphysa{\refj@jnl{Nucl.~Phys.~A}} % Nuclear Physics A +\def\physrep{\refj@jnl{Phys.~Rep.}} % Physics Reports +\def\physscr{\refj@jnl{Phys.~Scr}} % Physica Scripta +\def\planss{\refj@jnl{Planet.~Space~Sci.}} % Planetary Space Science +\def\procspie{\refj@jnl{Proc.~SPIE}} % Proceedings of the SPIE + +\let\astap=\aap +\let\apjlett=\apjl +\let\apjsupp=\apjs +\let\applopt=\ao diff --git a/old/references.bib b/old/references.bib new file mode 100644 index 0000000..2c7a4c0 --- /dev/null +++ b/old/references.bib @@ -0,0 +1,494 @@ + +@ARTICLE{LSSTSciBook, + author = {{LSST Science Collaboration} and {Abell}, P.~A. and {Allison}, J. and + {Anderson}, S.~F. and {Andrew}, J.~R. and {Angel}, J.~R.~P. and + {Armus}, L. and {Arnett}, D. and {Asztalos}, S.~J. and {Axelrod}, T.~S. and et al.}, + title = "{LSST Science Book, Version 2.0}", + journal = {ArXiv e-prints}, +archivePrefix = "arXiv", + eprint = {0912.0201}, + primaryClass = "astro-ph.IM", + keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Galaxy Astrophysics, Astrophysics - Solar and Stellar Astrophysics}, + year = 2009, + month = dec, + adsurl = {http://adsabs.harvard.edu/abs/2009arXiv0912.0201L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +%AAAAAAAAAAA +@ARTICLE{abraham2003a, + author = {{Abraham}, R.~G. and {van den Bergh}, S. and {Nair}, P.}, + title = "{A New Approach to Galaxy Morphology. I. Analysis of the Sloan Digital Sky Survey Early Data Release}", + journal = {\apj}, + eprint = {astro-ph/0301239}, + keywords = {Galaxies: Evolution, Galaxies: Fundamental Parameters}, + year = 2003, + month = may, + volume = 588, + pages = {218-229}, + doi = {10.1086/373919}, + adsurl = {http://adsabs.harvard.edu/abs/2003ApJ...588..218A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{abraham2014a, + author = {{Abraham}, R.~G. and {van Dokkum}, P.~G.}, + title = "{Ultra--Low Surface Brightness Imaging with the Dragonfly Telephoto Array}", + journal = {\pasp}, +archivePrefix = "arXiv", + eprint = {1401.5473}, + primaryClass = "astro-ph.IM", + keywords = {Astronomical Instrumentation}, + year = 2014, + month = jan, + volume = 126, + pages = {55-69}, + doi = {10.1086/674875}, + adsurl = {http://adsabs.harvard.edu/abs/2014PASP..126...55A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%BBBBBBBBBBB +@ARTICLE{bullock2005a, + author = {{Bullock}, J.~S. and {Johnston}, K.~V.}, + title = "{Tracing Galaxy Formation with Stellar Halos. I. Methods}", + journal = {\apj}, + eprint = {astro-ph/0506467}, + keywords = {Cosmology: Dark Matter, Galaxies: Dwarf, Galaxies: Evolution, Galaxies: Formation, Galaxies: Halos, Galaxies: Kinematics and Dynamics, Galaxy: Evolution, Galaxy: Formation, Galaxy: Halo, Galaxy: Kinematics and Dynamics, Galaxies: Local Group}, + year = 2005, + month = dec, + volume = 635, + pages = {931-949}, + doi = {10.1086/497422}, + adsurl = {http://adsabs.harvard.edu/abs/2005ApJ...635..931B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%CCCCCCCCCCC +@ARTICLE{conselice2003a, + author = {{Conselice}, C.~J. and {Bershady}, M.~A. and {Dickinson}, M. and + {Papovich}, C.}, + title = "{A Direct Measurement of Major Galaxy Mergers at z{\lt}\~{}3}", + journal = {\aj}, + eprint = {astro-ph/0306106}, + keywords = {Galaxies: Evolution, Galaxies: Formation, Galaxies: Interactions}, + year = 2003, + month = sep, + volume = 126, + pages = {1183-1207}, + doi = {10.1086/377318}, + adsurl = {http://adsabs.harvard.edu/abs/2003AJ....126.1183C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%FFFFFFFFFFF +@ARTICLE{flaugher2005a, + author = {{Flaugher}, B.}, + title = "{The Dark Energy Survey}", + journal = {International Journal of Modern Physics A}, + keywords = {Dark energy, galaxies, supernovae}, + year = 2005, + volume = 20, + pages = {3121-3123}, + doi = {10.1142/S0217751X05025917}, + adsurl = {http://adsabs.harvard.edu/abs/2005IJMPA..20.3121F}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%GGGGGGGGGGG +@ARTICLE{grogin2011a, + author = {{Grogin}, N.~A. and {Kocevski}, D.~D. and {Faber}, S.~M. and + {Ferguson}, H.~C. and {Koekemoer}, A.~M. and {Riess}, A.~G. and + {Acquaviva}, V. and {Alexander}, D.~M. and {Almaini}, O. and + {Ashby}, M.~L.~N. and {Barden}, M. and {Bell}, E.~F. and {Bournaud}, F. and + {Brown}, T.~M. and {Caputi}, K.~I. and {Casertano}, S. and {Cassata}, P. and + {Castellano}, M. and {Challis}, P. and {Chary}, R.-R. and {Cheung}, E. and + {Cirasuolo}, M. and {Conselice}, C.~J. and {Roshan Cooray}, A. and + {Croton}, D.~J. and {Daddi}, E. and {Dahlen}, T. and {Dav{\'e}}, R. and + {de Mello}, D.~F. and {Dekel}, A. and {Dickinson}, M. and {Dolch}, T. and + {Donley}, J.~L. and {Dunlop}, J.~S. and {Dutton}, A.~A. and + {Elbaz}, D. and {Fazio}, G.~G. and {Filippenko}, A.~V. and {Finkelstein}, S.~L. and + {Fontana}, A. and {Gardner}, J.~P. and {Garnavich}, P.~M. and + {Gawiser}, E. and {Giavalisco}, M. and {Grazian}, A. and {Guo}, Y. and + {Hathi}, N.~P. and {H{\"a}ussler}, B. and {Hopkins}, P.~F. and + {Huang}, J.-S. and {Huang}, K.-H. and {Jha}, S.~W. and {Kartaltepe}, J.~S. and + {Kirshner}, R.~P. and {Koo}, D.~C. and {Lai}, K. and {Lee}, K.-S. and + {Li}, W. and {Lotz}, J.~M. and {Lucas}, R.~A. and {Madau}, P. and + {McCarthy}, P.~J. and {McGrath}, E.~J. and {McIntosh}, D.~H. and + {McLure}, R.~J. and {Mobasher}, B. and {Moustakas}, L.~A. and + {Mozena}, M. and {Nandra}, K. and {Newman}, J.~A. and {Niemi}, S.-M. and + {Noeske}, K.~G. and {Papovich}, C.~J. and {Pentericci}, L. and + {Pope}, A. and {Primack}, J.~R. and {Rajan}, A. and {Ravindranath}, S. and + {Reddy}, N.~A. and {Renzini}, A. and {Rix}, H.-W. and {Robaina}, A.~R. and + {Rodney}, S.~A. and {Rosario}, D.~J. and {Rosati}, P. and {Salimbeni}, S. and + {Scarlata}, C. and {Siana}, B. and {Simard}, L. and {Smidt}, J. and + {Somerville}, R.~S. and {Spinrad}, H. and {Straughn}, A.~N. and + {Strolger}, L.-G. and {Telford}, O. and {Teplitz}, H.~I. and + {Trump}, J.~R. and {van der Wel}, A. and {Villforth}, C. and + {Wechsler}, R.~H. and {Weiner}, B.~J. and {Wiklind}, T. and + {Wild}, V. and {Wilson}, G. and {Wuyts}, S. and {Yan}, H.-J. and + {Yun}, M.~S.}, + title = "{CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {1105.3753}, + primaryClass = "astro-ph.CO", + keywords = {cosmology: observations, galaxies: high-redshift}, + year = 2011, + month = dec, + volume = 197, + eid = {35}, + pages = {35}, + doi = {10.1088/0067-0049/197/2/35}, + adsurl = {http://adsabs.harvard.edu/abs/2011ApJS..197...35G}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%JJJJJJJJJJJ +@ARTICLE{johnston2008a, + author = {{Johnston}, K.~V. and {Bullock}, J.~S. and {Sharma}, S. and + {Font}, A. and {Robertson}, B.~E. and {Leitner}, S.~N.}, + title = "{Tracing Galaxy Formation with Stellar Halos. II. Relating Substructure in Phase and Abundance Space to Accretion Histories}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {0807.3911}, + keywords = {Cosmology: Dark Matter, Galaxies: Dwarf, Galaxies: Evolution, Galaxies: Formation, Galaxies: Halos, Galaxies: Kinematics and Dynamics, Galaxy: Evolution, Galaxy: Formation, Galaxy: Halo, Galaxy: Kinematics and Dynamics, Galaxies: Local Group}, + year = 2008, + month = dec, + volume = 689, + pages = {936-957}, + doi = {10.1086/592228}, + adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...689..936J}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%KKKKKKKKKKK +@INPROCEEDINGS{kaiser2010a, + author = {{Kaiser}, N. and {Burgett}, W. and {Chambers}, K. and {Denneau}, L. and + {Heasley}, J. and {Jedicke}, R. and {Magnier}, E. and {Morgan}, J. and + {Onaka}, P. and {Tonry}, J.}, + title = "{The Pan-STARRS wide-field optical/NIR imaging survey}", +booktitle = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + year = 2010, + series = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + volume = 7733, + month = jul, + eid = {77330E}, + pages = {0}, + doi = {10.1117/12.859188}, + adsurl = {http://adsabs.harvard.edu/abs/2010SPIE.7733E..0EK}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kartaltepe2007a, + author = {{Kartaltepe}, J.~S. and {Sanders}, D.~B. and {Scoville}, N.~Z. and + {Calzetti}, D. and {Capak}, P. and {Koekemoer}, A. and {Mobasher}, B. and + {Murayama}, T. and {Salvato}, M. and {Sasaki}, S.~S. and {Taniguchi}, Y. + }, + title = "{Evolution of the Frequency of Luminous ({\gt}=L$^{*}$$_{V}$) Close Galaxy Pairs at z {\lt} 1.2 in the COSMOS Field}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {0705.2266}, + keywords = {Cosmology: Observations, Galaxies: Evolution, Galaxies: Formation, Galaxies: Interactions, Cosmology: Large-Scale Structure of Universe, Surveys}, + year = 2007, + month = sep, + volume = 172, + pages = {320-328}, + doi = {10.1086/519953}, + adsurl = {http://adsabs.harvard.edu/abs/2007ApJS..172..320K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{koekemoer2011a, + author = {{Koekemoer}, A.~M. and {Faber}, S.~M. and {Ferguson}, H.~C. and + {Grogin}, N.~A. and {Kocevski}, D.~D. and {Koo}, D.~C. and {Lai}, K. and + {Lotz}, J.~M. and {Lucas}, R.~A. and {McGrath}, E.~J. and {Ogaz}, S. and + {Rajan}, A. and {Riess}, A.~G. and {Rodney}, S.~A. and {Strolger}, L. and + {Casertano}, S. and {Castellano}, M. and {Dahlen}, T. and {Dickinson}, M. and + {Dolch}, T. and {Fontana}, A. and {Giavalisco}, M. and {Grazian}, A. and + {Guo}, Y. and {Hathi}, N.~P. and {Huang}, K.-H. and {van der Wel}, A. and + {Yan}, H.-J. and {Acquaviva}, V. and {Alexander}, D.~M. and + {Almaini}, O. and {Ashby}, M.~L.~N. and {Barden}, M. and {Bell}, E.~F. and + {Bournaud}, F. and {Brown}, T.~M. and {Caputi}, K.~I. and {Cassata}, P. and + {Challis}, P.~J. and {Chary}, R.-R. and {Cheung}, E. and {Cirasuolo}, M. and + {Conselice}, C.~J. and {Roshan Cooray}, A. and {Croton}, D.~J. and + {Daddi}, E. and {Dav{\'e}}, R. and {de Mello}, D.~F. and {de Ravel}, L. and + {Dekel}, A. and {Donley}, J.~L. and {Dunlop}, J.~S. and {Dutton}, A.~A. and + {Elbaz}, D. and {Fazio}, G.~G. and {Filippenko}, A.~V. and {Finkelstein}, S.~L. and + {Frazer}, C. and {Gardner}, J.~P. and {Garnavich}, P.~M. and + {Gawiser}, E. and {Gruetzbauch}, R. and {Hartley}, W.~G. and + {H{\"a}ussler}, B. and {Herrington}, J. and {Hopkins}, P.~F. and + {Huang}, J.-S. and {Jha}, S.~W. and {Johnson}, A. and {Kartaltepe}, J.~S. and + {Khostovan}, A.~A. and {Kirshner}, R.~P. and {Lani}, C. and + {Lee}, K.-S. and {Li}, W. and {Madau}, P. and {McCarthy}, P.~J. and + {McIntosh}, D.~H. and {McLure}, R.~J. and {McPartland}, C. and + {Mobasher}, B. and {Moreira}, H. and {Mortlock}, A. and {Moustakas}, L.~A. and + {Mozena}, M. and {Nandra}, K. and {Newman}, J.~A. and {Nielsen}, J.~L. and + {Niemi}, S. and {Noeske}, K.~G. and {Papovich}, C.~J. and {Pentericci}, L. and + {Pope}, A. and {Primack}, J.~R. and {Ravindranath}, S. and {Reddy}, N.~A. and + {Renzini}, A. and {Rix}, H.-W. and {Robaina}, A.~R. and {Rosario}, D.~J. and + {Rosati}, P. and {Salimbeni}, S. and {Scarlata}, C. and {Siana}, B. and + {Simard}, L. and {Smidt}, J. and {Snyder}, D. and {Somerville}, R.~S. and + {Spinrad}, H. and {Straughn}, A.~N. and {Telford}, O. and {Teplitz}, H.~I. and + {Trump}, J.~R. and {Vargas}, C. and {Villforth}, C. and {Wagner}, C.~R. and + {Wandro}, P. and {Wechsler}, R.~H. and {Weiner}, B.~J. and {Wiklind}, T. and + {Wild}, V. and {Wilson}, G. and {Wuyts}, S. and {Yun}, M.~S. + }, + title = "{CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey{\mdash}The Hubble Space Telescope Observations, Imaging Data Products, and Mosaics}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {1105.3754}, + primaryClass = "astro-ph.CO", + keywords = {cosmology: observations, galaxies: high-redshift}, + year = 2011, + month = dec, + volume = 197, + eid = {36}, + pages = {36}, + doi = {10.1088/0067-0049/197/2/36}, + adsurl = {http://adsabs.harvard.edu/abs/2011ApJS..197...36K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%HHHHHHHHHHH +@ARTICLE{heckman2005a, + author = {{Heckman}, T.~M. and {Hoopes}, C.~G. and {Seibert}, M. and {Martin}, D.~C. and + {Salim}, S. and {Rich}, R.~M. and {Kauffmann}, G. and {Charlot}, S. and + {Barlow}, T.~A. and {Bianchi}, L. and {Byun}, Y.-I. and {Donas}, J. and + {Forster}, K. and {Friedman}, P.~G. and {Jelinsky}, P.~N. and + {Lee}, Y.-W. and {Madore}, B.~F. and {Malina}, R.~F. and {Milliard}, B. and + {Morrissey}, P.~F. and {Neff}, S.~G. and {Schiminovich}, D. and + {Siegmund}, O.~H.~W. and {Small}, T. and {Szalay}, A.~S. and + {Welsh}, B.~Y. and {Wyder}, T.~K.}, + title = "{The Properties of Ultraviolet-luminous Galaxies at the Current Epoch}", + journal = {\apjl}, + eprint = {astro-ph/0412577}, + keywords = {Galaxies: Evolution, Galaxies: General, Galaxies: Starburst, Ultraviolet: Galaxies}, + year = 2005, + month = jan, + volume = 619, + pages = {L35-L38}, + doi = {10.1086/425979}, + adsurl = {http://adsabs.harvard.edu/abs/2005ApJ...619L..35H}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%LLLLLLLLLLL +@ARTICLE{lin2008a, + author = {{Lin}, L. and {Patton}, D.~R. and {Koo}, D.~C. and {Casteels}, K. and + {Conselice}, C.~J. and {Faber}, S.~M. and {Lotz}, J. and {Willmer}, C.~N.~A. and + {Hsieh}, B.~C. and {Chiueh}, T. and {Newman}, J.~A. and {Novak}, G.~S. and + {Weiner}, B.~J. and {Cooper}, M.~C.}, + title = "{The Redshift Evolution of Wet, Dry, and Mixed Galaxy Mergers from Close Galaxy Pairs in the DEEP2 Galaxy Redshift Survey}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {0802.3004}, + keywords = {Galaxies: Evolution, Galaxies: Interactions, Cosmology: Large-Scale Structure of Universe}, + year = 2008, + month = jul, + volume = 681, + pages = {232-243}, + doi = {10.1086/587928}, + adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...681..232L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{lotz2004a, + author = {{Lotz}, J.~M. and {Primack}, J. and {Madau}, P.}, + title = "{A New Nonparametric Approach to Galaxy Morphological Classification}", + journal = {\aj}, + eprint = {astro-ph/0311352}, + keywords = {Galaxies: Fundamental Parameters, Galaxies: High-Redshift, Galaxies: Peculiar, Galaxies: Structure}, + year = 2004, + month = jul, + volume = 128, + pages = {163-182}, + doi = {10.1086/421849}, + adsurl = {http://adsabs.harvard.edu/abs/2004AJ....128..163L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{lotz2008a, + author = {{Lotz}, J.~M. and {Davis}, M. and {Faber}, S.~M. and {Guhathakurta}, P. and + {Gwyn}, S. and {Huang}, J. and {Koo}, D.~C. and {Le Floc'h}, E. and + {Lin}, L. and {Newman}, J. and {Noeske}, K. and {Papovich}, C. and + 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{http://adsabs.harvard.edu/abs/2014ARA%26A..52..415M}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{martinez-delgado2008a, + author = {{Mart{\'{\i}}nez-Delgado}, D. and {Pe{\~n}arrubia}, J. and {Gabany}, R.~J. and + {Trujillo}, I. and {Majewski}, S.~R. and {Pohlen}, M.}, + title = "{The Ghost of a Dwarf Galaxy: Fossils of the Hierarchical Formation of the Nearby Spiral Galaxy NGC 5907}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {0805.1137}, + keywords = {Cosmology: Dark Matter, Galaxies: Dwarf, Galaxies: Evolution, Galaxies: Halos, Galaxies: Individual: NGC Number: NGC 5907, Galaxies: Interactions}, + year = 2008, + month = dec, + volume = 689, + pages = {184-193}, + doi = {10.1086/592555}, + adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...689..184M}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@INPROCEEDINGS{miyazaki2012a, + author = {{Miyazaki}, S. and {Komiyama}, Y. and {Nakaya}, H. and {Kamata}, Y. and + 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of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + year = 2012, + series = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + volume = 8446, + month = sep, + eid = {84460Z}, + pages = {0}, + doi = {10.1117/12.926844}, + adsurl = {http://adsabs.harvard.edu/abs/2012SPIE.8446E..0ZM}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%NNNNNNNNNNN +@ARTICLE{noeske2007a, + author = {{Noeske}, K.~G. and {Weiner}, B.~J. and {Faber}, S.~M. and {Papovich}, C. and + {Koo}, D.~C. and {Somerville}, R.~S. and {Bundy}, K. and {Conselice}, C.~J. and + {Newman}, J.~A. and {Schiminovich}, D. and {Le Floc'h}, E. and + {Coil}, A.~L. and {Rieke}, G.~H. and {Lotz}, J.~M. and {Primack}, J.~R. and + {Barmby}, P. and {Cooper}, M.~C. and {Davis}, M. and {Ellis}, R.~S. and + {Fazio}, G.~G. and {Guhathakurta}, P. and {Huang}, J. and {Kassin}, S.~A. and + {Martin}, D.~C. and {Phillips}, A.~C. and {Rich}, R.~M. and + {Small}, T.~A. and {Willmer}, 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{Abraham}, R. and {Merritt}, A.}, + title = "{First Results from the Dragonfly Telephoto Array: The Apparent Lack of a Stellar Halo in the Massive Spiral Galaxy M101}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1401.5467}, + keywords = {cosmology: observations, galaxies: evolution, galaxies: halos, Galaxy: halo, Galaxy: structure}, + year = 2014, + month = feb, + volume = 782, + eid = {L24}, + pages = {L24}, + doi = {10.1088/2041-8205/782/2/L24}, + adsurl = {http://adsabs.harvard.edu/abs/2014ApJ...782L..24V}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%YYYYYYYYYYY +@ARTICLE{york2000a, + author = {{York}, D.~G. and {Adelman}, J. and {Anderson}, Jr., J.~E. and + {Anderson}, S.~F. and {Annis}, J. and {Bahcall}, N.~A. and {Bakken}, J.~A. and + {Barkhouser}, R. and {Bastian}, S. and {Berman}, E. and {Boroski}, W.~N. and + {Bracker}, S. and {Briegel}, C. and {Briggs}, J.~W. and {Brinkmann}, J. and + {Brunner}, R. and {Burles}, S. and {Carey}, L. and 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b/old/science_background/chapterintro.tex similarity index 100% rename from science_background/chapterintro.tex rename to old/science_background/chapterintro.tex diff --git a/old/science_background/galaxies/galaxies.tex b/old/science_background/galaxies/galaxies.tex new file mode 100644 index 0000000..5c200a6 --- /dev/null +++ b/old/science_background/galaxies/galaxies.tex @@ -0,0 +1,448 @@ + +% LSST Extragalactic Roadmap +% Chapter: science_background +% Section: galaxies +% First draft by + +\section{Galaxy Evolution Studies with LSST} +\label{sec:sci:gal:bkgnd} + +Galaxies represent fundamental astronomical objects +outside our own Milky Way. +The large luminosities of galaxies enable their +detection to extreme distances, providing abundant +and far-reaching probes into the depths of the universe. +At each epoch in cosmological history, the color +and brightness distributions of the galaxy population +reveal how stellar populations form with time and +as a function of galaxy mass. The progressive mix of +disk and spheroidal morphological components of +galaxies communicate the relative importance of +energy dissipation and collisionless processes +for their formation. +Correlations between internal galaxy properties and +cosmic environments indicate +the ways the universe nurtures galaxies as they form. +The evolution of the +detailed characteristics of galaxies over cosmic time +reflects how fundamental astrophysics +operates to generate the rich variety of +astronomical structures observed today. + +Study of the astrophysics of galaxy formation represents +a vital science of its own, but the ready +observability of galaxies critically enables a host of +astronomical experiments in other fields. +Galaxies act as the semaphores of the +universe, encoding information about +the development of large scale +structures and the mass-energy budget of the +universe in their spatial distribution. The mass distribution +and clustering of galaxies reflect essential +properties of dark matter, including potential +constraints on the velocity and mass of particle candidates. +Galaxies famously host supermassive black holes, +and observations of active galactic nuclei provide +a window into the high-energy astrophysics of black hole +accretion processes. The porous interface between the +astrophysics of black holes, galaxies, and +dark matter structures allows for astronomers to +achieve gains in each field using the same datasets. + +The Large Synoptic Survey Telescope (LSST) will provide a +digital image of the southern sky in six bands ($ugrizy$). +The area ($\sim18,000~\mathrm{deg}^2$) and depth +($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of +the survey will enable research of such breadth +that LSST may influence essentially all extragalactic +science programs that rely primarily on photometric data. +For studies of galaxies, LSST provide both an unequaled +catalogue of billions of extragalactic sources and high-quality +multiband imaging of individual objects. This section of +the {\it Extragalactic Roadmap} presents scientific +background for studies of these galaxies with LSST to provide a +context for considering how the astronomical community can +best leverage the catalogue and imaging datasets and for +identifying any required preparatory science tasks. + +LSST will begin science operations during the next decade, +more than twenty years after the start of the Sloan +Digital Sky Survey \citep{york2000a} and subsequent precursor surveys +including PanSTARRS \citep{kaiser2010a}, the Subaru +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark +Energy Survey \citep{flaugher2005a}. Relative to these prior +efforts, extragalactic science breakthroughs +generated by LSST will likely benefit from its increased area, source +counts, and statistical samples, the constraining power of the +six-band imaging, and the survey depth and image quality. The following +discussion of LSST efforts focusing on the astrophysics of galaxies +will highlight how these features of the survey enable new science +programs. + + + +\subsection{Star Formation and Stellar Populations in Galaxies} +\label{sec:sci:gal:bkgnd:stars} + +Light emitted by stellar populations will +provide all the direct measurements made by +LSST. This information will be filtered through +the six passbands utilized by the survey +($ugrizy$), providing constraints on the +rest-frame ultraviolet SEDs of galaxies to +redshift $z\sim6$ and a probe of rest-frame +optical spectral breaks to $z\sim1.5$. By +using stellar population synthesis modeling, +these measures of galaxy SEDS will enable +estimates of the redshifts, star formation rates, +stellar masses, dust content, and +population ages for potentially +billions of galaxies. In the context of previous +extragalactic surveys, LSST +will enable new advances in our understanding +of stellar populations in galaxies by contributing +previously unachievable statistical power and an +areal coverage that samples the rarest cosmic +environments. + +A variety of ground- and space-based observations +have constrained the +star formation history of the universe over the +redshift range that LSST will likely probe +\citep[for a recent review, see][]{madau2014a}. +The statistical power of LSST will improve our +knowledge of the evolving UV luminosity function, +luminosity density, and cosmic +star formation rate. The LSST observations can +constrain how the astrophysics of gas +cooling within dark matter halos, the efficiency +of molecular cloud formation and the star formation +within them, and +regulatory mechanisms like supernova and radiative +heating give rise to these statistical features +of the galaxy population. While measurement of +the evolving UV luminosity function can +help quantify the role of these +astrophysical processes, the ability of LSST +to probe vastly different cosmic environments +will also allow for the robust quantification of any +changes in the UV luminosity function with +environmental density, and an examination of +connections between environment and the fueling +of star formation. + +Optical observations teach us about +the established stellar content of galaxies. +For stellar populations older than $\sim100$ million +years, optical observations provide +sensitivity to the spectral breaks near a +wavelength of $\lambda\approx4000\AA$ in the +rest-frame related to absorption in the +atmospheres of mature stars. +Such observations help constrain +the amount of stellar mass in galaxies. For +passive galaxies that lack vigorous star formation, +these optical observations reveal +the well-defined ``red sequence'' of +galaxies in the color-magnitude plane +that traces the succession of +galaxies from recently-merged spheroids +to the most massive systems at the +centers of galaxy clusters. For blue, +star-forming +galaxies, optical light can help +quantify the relative contribution of +evolved stars to total galaxy luminosity, +and indeed has +led to the identification of a well-defined +locus of galaxies in the parameter space of +star formation rate and stellar mass +\citep[e.g.,][]{noeske2007a}. This +relation, often called the ``star-forming +main sequence'' of galaxies, indicates that +galaxies of the same stellar mass typically +sustain a similar star-formation rate. +Determining the +physical or possibly statistical +origin of the relation remains an active +line of inquiry, guided by recently improved +data from Hubble Space Telescope over the +$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared +Deep Extragalactic Survey +\citep{grogin2011a,koekemoer2011a}. While +LSST will be comparably limited in redshift +selection, its $~30,000$ times larger area +will enable a much fuller sampling of the +star formation--stellar mass plane, allowing +for a characterization of the distribution +of galaxies that lie off the main sequence +that can help discriminate between phenomenological +explanations of the sequence. + +\subsection{Galaxies as Cosmic Structures} +\label{sec:sci:gal:bkgnd:structures} + +The structural properties of galaxies arise from +an intricate combination of important astrophysical +processes. The gaseous disks of galaxies require +substantial energy dissipation while depositing +angular momentum into a rotating structure. These +gaseous disks form stars with a +surface density that declines exponentially with +galactic radius, populating stellar orbits that +differentially rotate about the galactic center and +somehow organize into spiral features. +Many disk galaxies contain (pseduo-)bulges that form through +a combination of violent relaxation and orbital dynamics. +These disk galaxy features contrast with systems where +spheroidal stellar distributions dominate the galactic +structure. Massive ellipticals form through galaxy +mergers and accretions, and manage to forge a regular +sequence of surface density, size, and stellar velocity +dispersion from the chaos of strong gravitational +encounters. Since these astrophysical +processes may operate with great +variety as a function of galaxy mass and +cosmic environment, LSST will revolutionize studies +of evolving galaxy morphologies by providing enormous +samples with deep imaging of exquisite quality. + +The huge sample of galaxies provided by LSST will +provide a definitive view of how the sizes and +structural parameters of disk and spheroidal systems +vary with color, stellar mass, and luminosity. +Morphological studies will employ at least two +complementary techniques for quantifying the +structural properties of galaxies. Bayesian +methods can yield multi-component +parameterized models for all the galaxies +in the LSST sample, including the quantified +contribution of bulge, disk, and +spheroid structures to the observed galaxy +surface brightness profiles. The parameterized +models will supplement non-parametric measures +of the light distribution including the +Gini and M20 metrics that quantify the surface +brightness uniformity and spatial moment of +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. +Collectively, these morphological measures provided +by analyzing the LSST imaging data will enable +a consummate determination of the relation between +structural properties and other features of +galaxies over a range of galaxy mass and luminosity +previously unattainable. + +While the size of the LSST sample supplies the +statistical power for definitive morphological studies, +the sample size also enables the identification of rare +objects. This capability will benefit our efforts for +connecting the distribution of galaxy morphologies to their +evolutionary origin during the structure formation process, +including the formation of disk galaxies. +The emergence of ordered disk galaxies remains a hallmark +event in cosmic history, with so-called ``grand design'' +spirals like the Milky Way forming dynamically cold, thin +disks in the last $\sim10$ Gyr. Before thin disks emerged, +rotating systems featured ``clumpy'' mass distributions with +density enhancements +that may originate from large scale gravitational instability. +Whether the ground-based LSST can effectively probe +the exact timing and duration of the transition from +clumpy to well-ordered disks remains +unknown, but LSST can undoubtedly contribute studying the +variation in forming disk structures at the present day. +Unusual objects, such as the UV luminous local galaxies identified +by \citet{heckman2005a} that display physical features analogous to +Lyman break galaxies at higher redshifts, may provide a +means to study the formation of disks in the present day +under rare conditions only well-probed by the sheer size +of the LSST survey. + +Similarly, the characterizing the extremes of the +massive spheroid population can critically inform +theoretical models for their formation. For instance, +the most massive galaxies at the centers of galaxy clusters +contain vast numbers of stars within enormous stellar +envelopes. The definitive LSST sample can capture enough +of the most massive, rare clusters to quantify the +spatial extent of these galaxies at +low surface brightnesses, where the bound stellar +structures blend with the intracluster light of +their hosts. Another research area the LSST data +can help address regards the central densities of local +ellipticals that have seemingly decreased compared with +field ellipticals at higher redshifts. The transformation +of these dense, early ellipticals to the spheroids in the +present day may involve galaxy mergers and environmental +effects, two astrophysical processes that LSST can characterize +through unparalleled statistics and environmental probes. +By measuring the +surface brightness profiles of billions of +ellipticals LSST can determine whether any such dense +early ellipticals survive to the present day, whatever +their rarity. + +Beyond the statistical advances enabled by LSST and the +wide variation in environments probed by a survey +of half the sky, the image quality of LSST will permit +studies of galaxy structures in the very low surface +brightness regime. Observational +measures of the outer most regions of thin disks can constrain +how such disks ``end'', how dynamical effects might truncate +disks, and whether some disks smoothly transition into stellar +halos. LSST will provide such measures and help quantify the +relative importance the physical effects that influence the +low surface brightness regions in disks. Other galaxies +have low surface brightnesses throughout their stellar +structures, and the image quality and sensitivity +of LSST will enable the most complete census +of low surface brightness galaxies to date. LSST will provide +the best available constraints on the extremes of disk +surface brightness, which relates to the extremes of +star formation in low surface density environments. + +The ability of LSST to probe low surface brightnesses +also allows for characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +from streams to density inhomogeneities, originate +from the hierarchical formation process and their +morphology provides clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} +have already +demonstrated that stellar halo structures display interesting +variety +\citep[e.g.,][]{van_dokkum2014a}. +LSST, with its unrivaled entendue, can help build a statistical +sample of stellar halos and cross-reference their morphologies +with the observed properties of their central galaxies. Such +studies may determine whether the formation histories reflected +in the structures of halos also influence galaxy colors or +morphological type. The +examination of stellar halos around external galaxies may +also result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +models of the galaxy formation process on the extreme +low-mass end of the mass function. + +\subsection{Probing the Extremes of Galaxy Formation} +\label{sec:sci:gal:bkgnd:rare} + +The deep, multiband imaging LSST provides over an enormous +area will enable the search for galaxies that form in the +rarest environments, under the most unusual conditions, +and at very early times. By probing the extremes of +galaxy formation, the LSST data will push our theoretical +understanding of the structure formation process. + +The rarest, most massive early galaxies may form in +conjunction with the supermassive black holes that +power distant quasars. LSST can use the same +types of color-color selections to identify extremely +luminosity galaxies out to redshift $z\sim6$, and +monitor whether the stellar mass build-up in these +galaxies tracks the accretion history of the most +massive supermassive black holes. If stellar mass +builds proportionally to black hole mass in quasars, +then very rare luminous star forming galaxies at +early times may immediately proceed the formation +of bright quasars. LSST has all the requisite +survey properties (area, mutliband imaging, and +depth) to investigate this long-standing problem. + +The creation of LSST Deep Drilling fields will +enable a measurement of the very bright end +of the high-redshift galaxy luminosity function. +Independent determinations of the distribution of +galaxy luminosities at $z\sim6$ show substantial +variations at the bright end. The origin of +the discrepancies between various groups remains +unclear, but the substantial cosmic variance expected +for the limited volumes probed and the intrinsic +rarity of the bright objects may conspire to +introduce large potential differences between +the abundance of massive galaxies in different +areas of the sky. Reducing this uncertainty requires +deep imaging over a wide area, and the LSST Deep Drilling +fields satisfy this need by achieving sensitivities +beyond the rest of the survey. + +Lastly, the spatial rarity of extreme objects discovered +in the wide LSST area may reflect an intrinsically +small volumetric density of objects or the short duration +of an event that gives rise to the observed properties of the +rare objects. Mergers represent a critical class +of short-lived epochs in the formation histories of +individual galaxies. Current determinations of the evolving numbers +of close galaxy pairs or morphological indicators of +mergers provide varying estimates for the +redshift dependence of the galaxy merger rate +\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. +The identification of merging +galaxy pairs as a function of separation, merger +mass ratio, and environment in the LSST data will enable +a full accounting of how galaxy mergers influence +the observed properties of galaxies as a function of +cosmic time. + +\subsection{Photometric Redshifts} +\label{sec:sci:gal:bkgnd:photoz} +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-z's). While spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra, photometric redshifts, instead, estimate the rough distance to an object based on broad-band photometric colors. This can be thought of as akin to a very low-resolution spectrum sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.~the 4000\AA\ and Lyman breaks), with each broad-band filter being a single pixel in the spectrum. By relying on imaging data alone, we are able to measure photo-z's for billions of galaxies in the LSST survey, at the cost of added uncertainty in the redshift estimates, and potential redshift degeneracies. + As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-z's is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it the incorrect luminosity via the distance modulus, and can bias estimates of the luminosity function; errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to an error in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. + In order to understand the biases and uncertainties inherent to photo-z's for a particular survey, we need to train the photo-z algorithms using galaxies with known redshifts. For a full characterization, a fully representative sub-sample of the underlying galaxy population is necessary; however, in practice, this is very difficult to achieve, due to limitations in both spectroscopic instrumentation and telescope time. We can attempt to identify and remove any biases due to incomplete training data using several redshift calibration techniques, the most prominent one relying on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts. A detailed plan describing the spectroscopic needs, for training and calibration, is laid out in \citet[]{Newman2015}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be functional in the near future. As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-z training, but also to those studying galaxy formation and evolution. In addition, any insights gained on galaxy formation and evolution during the course of the LSST survey can be used to improve photo-z algorithms. For example, improved spectral energy distribution evolution models would improve photo-z performance at high redshift. Or, observable quantities such as size and surface brightness may be incorporated as Bayesian priors on the photo-z's once their distributions are well understood. This mutual benefit between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both subjects as the survey progresses. + +\subsection{Science Book} +\label{sec:sci:gal:bkgnd:scibook} + +The LSST Science Book (\citealt{LSSTSciBook}) provided +detailed descriptions of foundationl science enabled +by LSST. The LSST Galaxies Science Collaboration authored +the Chapter 9 ``Galaxies'' of the Science Book, and the +a table of contents of that chapter follow below to +provide an example list of topics in extragalactic +science that LSST data will help revolutionize. The +interested reader is referred to the LSST Science +Book for more details. + + +\begin{enumerate} +\item Measurements, Detection, Photometry, Morphology +\item Demographics of Galaxy Populations +\begin{itemize} +\item Passively evolving galaxies +\item High-redshift star forming galaxies +\item Dwarf galaxies +\item Mergers and interactions +\end{itemize} +\item Distribution Functions and Scaling Relations +\begin{itemize} +\item Luminosity and size evolution +\item Relations between observables +\item Quantifying the Biases and Uncertainties +\end{itemize} +\item Galaxies in their Dark-Matter Context +\begin{itemize} +\item Measuring Galaxy Environments with LSST +\item The Galaxy-Halo Connection +\item Clusters and Cluster Galaxy Evolution +\item Probing Galaxy Evolution with Clustering Measurements +\item Measuring Angular Correlations with LSST, Cross-correlations +\end{itemize} +\item Galaxies at Extremely Low Surface Brightness +\begin{itemize} +\item Spiral Galaxies with LSB Disks +\item Dwarf Galaxies +\item Tidal Tails and Streams +\item Intracluster Light +\end{itemize} +\item Wide Area, Multiband Searches for High-Redshift Galaxies +\item Deep Drilling Fields +\item Galaxy Mergers and Merger Rates +\item Special Populations of Galaxies +\item Public Involvement +\end{enumerate} + + + + + diff --git a/old/science_background/science_background.tex b/old/science_background/science_background.tex new file mode 100644 index 0000000..bd4f0e0 --- /dev/null +++ b/old/science_background/science_background.tex @@ -0,0 +1,20 @@ + +% LSST Extragalactic Roadmap +% Chapter: science_background +% First draft by + +\chapter[Science Background]{Science Background} +\label{ch:science_background} + +%TBD +%\input{science_background/chapterintro.tex} + + +\input{science_background/galaxies/galaxies.tex} + +%\input{science_background/black_holes/black_holes.tex} +%\input{science_background/informatics/informatics.tex} +%\input{science_background/lss/lss.tex} +%\input{science_background/strong_lensing/strong_lensing.tex} +%\input{science_background/weak_lensing/weak_lensing.tex} + diff --git a/old/structure.tex b/old/structure.tex new file mode 100644 index 0000000..d0bba70 --- /dev/null +++ b/old/structure.tex @@ -0,0 +1,63 @@ +\usepackage{amsmath} +\usepackage{amssymb} +\usepackage[top=3cm,bottom=3cm,left=3cm,right=3cm,headsep=10pt]{geometry} % Page margins +\usepackage{graphicx} % Required for including pictures + + + +\usepackage{verbatim} +\usepackage{enumitem} % Customize lists +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists +\usepackage{booktabs} % Required for nicer horizontal rules in tables +\usepackage{xcolor} % Required for specifying colors by name +\usepackage{listings} +\usepackage{color} + +%FONTS +\usepackage{anyfontsize} +\usepackage{avant} % Use the Avantgarde font for headings +\usepackage{mathptmx} % Use the Adobe Times Roman as the default text font together with math symbols from the Sym­bol, Chancery and Com­puter Modern fonts +\usepackage{microtype} % Slightly tweak font spacing for aesthetics + + + +\usepackage{calc} % For simpler calculation - used for spacing the index letter headings correctly +\usepackage{makeidx} % Required to make an index +\makeindex % Tells LaTeX to create the files required for indexing + + + +\bibliographystyle{apj} +\usepackage{natbib} + +%\usepackage{titletoc} % Required for manipulating the table of contents + + + +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists + +\def\motivation#1{\item[Motivation:] #1} +\def\activities#1{\item[Activities:] #1} +\def\deliverables#1{\item[Deliverables:] #1} + +\newenvironment{task}% +{\renewcommand\descriptionlabel[1]{\hspace{\labelsep}\textit{##1}} + \begin{description}\setlength{\itemsep}{0.15\baselineskip}} +{\end{description}} + +% Example usage: +% +% \begin{task} +% \motivation{Currently things are bad}. +% \activities{We will work to make them better}. +% \deliverables{Code to solve all problems}. +% \end{task} + +% PJM: here's a tasklist environment to take care of Michael's enumeration: + +%\def\tasktitle#1{\item{\bf #1}} +\def\tasktitle#1{\item{}} + +\newenvironment{tasklist}[1]% +{\begin{enumerate}[label=#1-\arabic{*}.,ref=\thesubsection:#1-\arabic{*},font=\bf]} +{\end{enumerate}} diff --git a/old/task_lists/agn/agn.tex b/old/task_lists/agn/agn.tex new file mode 100644 index 0000000..7705045 --- /dev/null +++ b/old/task_lists/agn/agn.tex @@ -0,0 +1,134 @@ +\section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} + +AGN are phenomena that enable us to understand the growth of BHs, understand aspects of galaxy evolution, probe the high redshift universe and study other physical activity, including accretion physics, jets, magnetic fields, etc. There are distinct aspects of the study of AGN that can best be explored by considering AGN as an evolutionary stage of galaxies rather than a distinct type of source. The tasks listed here explore aspects of AGN study that are particularly important AGN as a stage in galaxy evolution. + + +\begin{tasklist}{AGN} +\subsection{AGN feedback in clusters} +\tasktitle{AGN feedback in clusters} +\begin{task} +\label{task:agn:feedback_in_clusters} +\motivation{ +Brightest Cluster/Group Galaxies (hereafter BCGs) are the most massive galaxies in the local Universe residing at/near the centres of galaxy clusters/groups. They will therefore contain the largest supermassive black holes. These black holes can influence their host BCG, the cluster gas and other cluster members via the mechanical energy produced by their 100s kpc scale jets (AGN feedback). +\\ +For low redshift galaxy clusters it is possible to perform detailed studies of the star, gas and AGN jets to analyse the details of AGN feedback. LSST will provide a large sample of moderate to high redshift clusters in which we can measure AGN feedback statistically. By combining X-ray, radio and optical observations we can assess the average influence of the BCG's AGN on the hot Intra-cluster medium (ICM) for different sub-populations [e.g. Stott et al. 2012]. +} +\activities{ +By assembling a multi-wavelength dataset (optical, X-ray, Radio) we can obtain the BCG mass, cluster mass and ICM temperature, and the mechanical power injected into the ICM. We can use this to study the interplay between the BCG, its black hole and the cluster gas, to assess the balance of energies involved and for direct comparison with theoretical models of AGN feedback. This has been done with a few hundred clusters at z<0.3 using SDSS but we may well be able to reach z=1 and therefore look for an evolution in their interplay and therefore AGN feedback. There are also implications for cosmology too as this will help with the selection of clusters for which the X-ray properties better represent the mass of the cluster rather than the complex interplay of baryonic physics. } + +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Investigate the number of BCGs and the mass range of their clusters with redshift that LSST is likely to be able to observe. +\item Assess radio and X-ray data available for AGN Feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS etc). +\item Assess the theoretical predictions expected for the above (e.g. cosmological simulations such as EAGLE or more detailed single cluster studies). +\end{enumerate} +} +\end{task} +%\end{tasklist} + + +%\begin{tasklist}{T} +\subsection{AGN Selection from LSST Data} +\tasktitle{AGN Selection from LSST Data} +\begin{task} +\label{task:agn:selection} +\motivation{ +Active Galactic Nuclei are selected using a variety of different methods. At optical and infrared wavelengths, photometric selection of AGN candidates is driven by their distinctive colors at particular redshifts. X-ray and radio observations can also be efficient selectors of candidates for additional follow-up. With spectral data, AGN can be selected using the ratios of their emission lines. LSST will also open up, in a more practical way, the identification of AGN based on their variability. +Each of these samples probes aspects of the AGN phenomena and a better understanding of the AGN role in galaxy evolution requires that we understand how and why each of these selection methods includes or excludes particular sources. Furthermore, currently each of these methods for identifying AGN candidates requires spectral follow-up to cull these samples to positively identify the most reliably clean AGN sample. +} +\activities{ +For us to use LSST as a single way to identify the diversity of AGN, we must develop selection criteria that take advantage of the source parameters available with just LSST imaging, that is, color, morphology and variability. Already there are a number of AGN surveys with input from multiple wavelength observation and spectra. Precursor work needs to be done using these surveys to determine if AGN not easily identified using optical color selection can be selected using the additional parameters of morphology, variability and/or the additional filter that LSST provides. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Cross-matched catalog of known AGN selected and verified using different methods +\item Development of morphology parameters beyond just star/galaxy separation and an understanding of the morphology parameters to be provided by LSST level 2 products. +\item Development of color selection criteria that takes into account the morphology of the source +\item Understanding of how AGN variability looks given the nominal LSST cadence +\item Development of algorithms for color selection that take into account the variability of an AGN source +\end{enumerate} +} +\end{task} +%\end{tasklist} + + +%\begin{tasklist}{T} +\subsection{AGN Host Galaxy Properties from LSST Data} +\tasktitle{AGN Host Galaxy Properties from LSST Data} +\begin{task} +\label{task:agn:host_galaxies} +\motivation{ +We are requesting that basic morphological parameters (e.g., CAS, G-M20, etc.) be measured in the pipeline and made available as products to help in the identification of merging galaxies in LSST data. The issue here is how well this can be done when the host galaxies contain AGN that are likely identified via their variability. In other words, how well can we determine the host morphology of galaxies with variable AGN? This would be interesting for models of AGN fueling during mergers. +} +\activities{ +Simulations of the accuracy by which the pipeline (deblender) can measure the defined morphology parameters in host galaxies as a function of AGN brightness and wavelength. We could then ``vary'' the central source by expected levels in certain filters to see the effect on the morphological params. To constrain this it would be helpful to add in central sources with reasonable SEDs across the LSST bands, and a limited set of frequencies/amplitudes (based on real data - perhaps Pan-STARRS?). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Plots of the accuracy of the measured basic morphology parameters as a function of AGN brightness and wavelength. +\item Effect of AGN brightness on classification diagrams. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\subsection{AGN Variability Selection in LSST Data} +\tasktitle{AGN Variability Selection in LSST Data} +\begin{task} +\label{task:agn:variability} +\motivation{ +Most AGN exhibit broad-band aperiodic, stochastic variability across the entire EM spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, making it a powerful probe of accretion physics. The main LSST WFD survey will obtain $\sim10^8$ AGN light curves (i.e. flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. The deep drilling fields will give us AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will critically depend on the interval between observations in individual filter bands. It is of crucial importance to determine guidelines for an optimal survey strategy (from an AGN variability perspective) and determine what biases and uncertainties are introduced into AGN variability science as a result of the chosen survey strategy.} +\activities{ +Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate \& study simulations using parameters selected from these models with the observationally determined constraints to determine goodness of simulations for carrying out various types of AGN variability science - PSD models, QPO searches, binary AGN models, etc. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Observational constraints on AGN variability models. +\item MAF metrics quantifying the goodness of different survey strategies for AGN variability science. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\subsection{AGN Photometric Redshifts from LSST Data} +\tasktitle{AGN Photometric Redshifts from LSST Data} +\begin{task} +\label{task:agn:photoz} +\motivation{ +Given the large number of AGN that will be observed with LSST, many of these will not be followed up with spectral observations. However, understanding the large scale structure of the universe, requires a 3-D understanding of the distribution of these galaxies in the universe. Photometric redshifts can provide relatively accurate redshifts for large numbers of galaxies. However, it is harder to obtain accurate photometric redshifts for galaxies that contain AGN compared to those that do not. We must understand how to get accurate photometric redshifts of galaxies with AGN. +} +\activities{ +An initial activity for this need to include comprehensive review of the state of the art in obtaining photo-z’s for AGN host galaxy populations and how those compare to non-AGN galaxies. A comparison of model and/or observed AGN host SEDs with a matched set of non-host galaxies at a variety of redshifts will be used to determine color selection criteria for identifying AGN hosts. Explore whether variability can be used to break degeneracies. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Plots that show AGN host color selection criteria and where that color selection might become ambiguous (be degenerate) for non-host galaxies with different parameters. +\item Plots that show if other parameters might break degeneracies. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\subsection{AGN Merger Signature from LSST Data} +\tasktitle{AGN Merger Signature from LSST Data} +\begin{task} +\label{task:agn:mergers} +\motivation{ +Understanding the role AGN play in galaxy evolution requires identifying the phenomenon at all stages and in all types of galaxies. AGN host galaxies are often found to be disturbed suggesting that the galaxy merger process is an important trigger of AGN activity. While the ‘trainwrecks’ may be easier to find, galaxies in other merger stages can be difficult to identify and those experiencing ‘pre-merger’ harassment may be particularly hard to recognize. Preliminary work needs to be done to understand how to identify mergers from the LSST data products and whether galaxy deblending and segmentation methods and procedures are adequate or mask galaxy mergers. +} +\activities{ +Create or Identify simulated and real images that contain known galaxy mergers, these images should contain mergers with and without AGN. +Run LSST detection and identification software on these images. +Identify metrics that describe/quantify the accurate detection of galaxy mergers (with and without AGN). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Give feedback to LSST software teams about metrics and detection of galaxy mergers +\item Give feedback on structure or galaxy type that do and do not work well with current versions of LSST software +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/old/task_lists/clss/clss.tex b/old/task_lists/clss/clss.tex new file mode 100644 index 0000000..620ba9d --- /dev/null +++ b/old/task_lists/clss/clss.tex @@ -0,0 +1,332 @@ + +\section{Clusters and Large Scale Structure}\label{sec:tasks:clss} + +The cosmological process of galaxy formation inextricably links +the together, environment and large scale structure with the detailed +properties of galaxy populations. The extent of this connection +ranges from the scales of superclusters down to small groups. The +following preparatory science tasks focus on this critical connection +between galaxy formation, clusters, and large scale structure. + +\begin{tasklist}{CLSS} +\subsection{Cluster/LSS Sample Emulator} +\tasktitle{Cluster/LSS Sample Emulator} +\begin{task} +\label{task:clss:emulator} +\motivation{ +To prepare for galaxies and galaxy group/cluster science with LSST, we +need to know how many galaxies will be detected in a given range of +redshift, brightness, color, etc., and likewise how many groups and +clusters will be detected in given ranges of redshift, richness, mass, +and other physical parameters. +} +\activities{ +LSST has advanced simulations of its 10-year Wide Fast Deep survey +available from the Operations Simulator. The output databases can be +analyzed to determine the depth LSST is expected to reach in its final +detection image at each sky location, and Awan et al.~2016 +(http://adsabs.harvard.edu/abs/2016ApJ...829…50A) turns these depths +into predicted numbers of galaxies as a function of redshift and +brightness. +\\ +To predict galaxy sample sizes as a function of physical parameters, +the ``raw'' predicted galaxy numbers from Awan et al.~(2016) will be +interfaced with semi-analytical models painted on large N-body +simulations by Risa Wechsler and collaborators. This will extend the +predictions to include observed properties of color, size, morphology +and physical properties of halo mass, stellar mass, and star formation +rate. +\\ +To predict group/cluster sample sizes as a function of physical +parameters, the properties such as temperature, richness, etc., will +be painted on to dark matter halos drawn from a numerical simulation. +The properties will be based on simple scaling laws, with the user +allowed freedom to choose the parameters of the scaling laws, +including how they evolve. This will then be interfaced with the +``raw'' predicted galaxy numbers from Awan et al.~(2016), to determine +which of the groups and clusters should be detectable in the LSST +data.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Create a public LSST Extragalactic Sample Emulator with a +simple GUI. Enable user input of a range of redshift, and +physical parameters (e.g.~galaxy magnitudes, colors, size, morphology, +cluster richness, mass, temperature, etc.) to estimate the size of a +given sample detected by LSST. +\end{enumerate} +} +\end{task} + + +\subsection{Identifying and Characterizing Clusters} +\tasktitle{Identifying and Characterizing Clusters} +\begin{task} +\label{task:clss:clusters} +\motivation{ +LSST photometry will make it possible to +search for and study the galaxy populations of distant clusters and +proto-clusters over huge volumes of the high-$z$ Universe. These +clusters are testbeds for cosmology, hierarchical structure formation, +intergalactic medium heating and metal enrichment, as well as +laboratories for studying galaxy evolution. +However, standard approaches for identifying clusters, such as the red +sequence method, will be hampered by the limited wavelength coverage +of LSST. +For example, at $z \gtrsim 1.5$, near-IR photometry is required to +identify systems with Balmer/$4000$\AA\ breaks. +To maximize cluster science with LSST, we must devise new techniques +for cluster identification as well as incorporate complementary data +from projects such as \emph{Euclid}, \emph{eROSITA}, etc. +} +\activities{ +Using existing imaging datasets and simulations, algorithms need to be +developed and optimised to identify clusters at intermediate +and high redshift within the LSST footprint. +Specifically, this work should characterize the selection +function, completeness, and contamination rate for different cluster +identification algorithms. +This requires realistic light-cone simulations spanning extremely +large volumes, so as to capture significant numbers ($\gg10,000$) of +simulated galaxy clusters at high $z$. +Potential algorithms to be tested include adaptations of RedMaPPer +(Rykoff et al.~2014) as well as methods that search for galaxy +overdensities over a range of scales (e.g.~Chiang et al.~2014; Wang et +al.~2016). +In parallel, a comprehensive search for multiwavelength data +(specifically IR and X-ray imaging) is needed to aid in the search for +high-$z$ clusters and in the confirmation and characterization of +systems at all redshifts.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item The primary product of this analysis will be improved cluster +identification algorithms that can be applied to LSST data once +science operations commence. +\item In addition, this work will produce a compilation of ancillary data +that will be helpful in cluster identification and characterization, +such as X-ray (e.g.~XCS, eROSITA, etc.), SZ (Planck, SPT, ACT) and +radio (SKA and its pathfinders, SUMSS), within the LSST footprint. +\end{enumerate} +} +\end{task} + +\subsection{Developing and Optimizing Measurements of Galaxy Environment} +\tasktitle{Developing and Optimizing Measurements of Galaxy Environment} +\begin{task} +\label{task:clss:environment} +\motivation{ +Over the past decade, many studies have +shown that ``environment'' plays a important role in shaping galaxy +properties. For example, satellite galaxies in the local Universe +exhibit lower star formation rates, more bulge-dominated morphologies, +as well as older and more metal-rich stellar populations when compared +to isolated (or ``field'') systems of equivalent stellar mass (Baldry +et al.~2006; Cooper et al.~2010; Pasquali et al.~2010). +Unlike spectroscopic surveys, LSST will lack the precise line-of-sight +velocity measurements to robustly identify satellite galaxies in +lower-mass groups, where the expected photo-$z$ precision will greatly +exceed the velocity dispersion of the host halo. +Instead, LSST will likely be better suited to measuring environment by +tracing the local galaxy density (and identifying filaments). However, +LSST is unlike any previous photometric survey and may require new +approaches to measuring environment. +The challenge remains to find the measure(s) of local galaxy density +with the greatest sensitivity to the true underlying density field (or +to host halo mass, etc.), so as to enable analyses of environment's +role in galaxy evolution with LSST. +} +\activities{ +Using mock galaxy catalogs created via +semi-analytic techniques, we will compare different tracers of local +galaxy density (i.e.~''environment'') measured on mock LSST +photometric samples to the underlying real-space density of galaxies +(or to host halo mass). In addition to testing existing density +measures, such as $N^{\rm th}$-nearest-neighbor distance and counts in +a fixed aperture, we will explore new measures that may be better +suited to LSST. For each measure, we will examine the impact of +increasing survey depth and photo-$z$ precision over the course of the +survey.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item With an improved understanding of the +strengths and weaknesses of different environment measures as applied +to LSST, this effort will yield code to measure local galaxy density +(likely in multiple ways) within the LSST dataset. +\item Create a Level 3 data product for use by the entire project. +\end{enumerate} +} +\end{task} + +\subsection{Enabling and Optimizing Measurements of Galaxy Clustering} +\tasktitle{Enabling and Optimizing Measurements of Galaxy Clustering} +\begin{task} +\label{task:clss:clustering} +\motivation{ +Contemporary galaxy surveys have +transformed the study of large-scale structure, enabling high +precision measurements of clustering statistics. The correlation +function provides the most fundamental way to characterize the galaxy +distribution. The dependence of clustering on galaxy properties and +the evolution of clustering provide fundamental constraints on +theories of galaxy formation and evolution. Interpreting these +measurements provides crucial insight into the relation between +galaxies and dark matter halos. Understanding how galaxies relate to +the underlying dark matter is also essential for optimally utilizing +the large-scale distribution of galaxies as a cosmological probe. +} +\activities{ +Preparatory work will be along two main +tracks. The first one will be support work to define and characterize +the upcoming galaxy samples from LSST to enable clustering +measurements from them. Several distinct sets of information need to +be made available or be calculable from pipeline data. Such +requirements include a detailed understanding of any selection effects +impacting the observed galaxies, the angular and radial completeness +of the samples, and the detailed geometry of the survey (typically +provided in terms of random catalogs that cover the full survey area). +\\ +The second track will be the development, testing, and optimization of +algorithms for measuring galaxy clustering using LSST data. One aspect +to address is how best to handle the large data sets involved +(e.g.~the ``gold'' galaxy sample will include about $4$~billion +galaxies over $20$,$000$~square degrees). Another is to develop the +methodology to optimally incorporate the LSST photo-$z$ estimates with +the angular data to obtain ``2.5-dimensions'' for pristine clustering +measurements. +\\ +These algorithms will be tested on realistic LSST mock catalogs, which +will also later serve as a tool for obtaining error estimates on the +measurements. +This endeavor overlaps with DESC-LSS working group efforts, and +requires cooperation of the DESC-PhotoZ working group and the Galaxies +Theory and Mock Catalogs working group.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Ensuring LSST galaxy pipelines include all the necessary +information for measurements of the correlation function and related +statistics to take place once data is available +\item Developing and refining techniques for measuring galaxy clustering of +large LSST galaxy samples. Together these will enable realizing the +full potential of LSST data for large-scale structure studies and +galaxy formation inferences thereof. +\end{enumerate} +} +\end{task} + + +\subsection{Disentangling Complicated Lines of Sight} +\tasktitle{Disentangling Complicated Lines of Sight} +\begin{task} +\label{task:clss:los} +\motivation{ +Lines of sight through galaxy clusters and groups are the most +challenging lines of sight along which to measure reliable photometric +redshifts because crowding of galaxies complicates the basic process +of galaxy photometry, and the presence of significant correlated +large-scale structure (LSS) complicates interpretation of the P(z) of +the galaxies that has been computed by an algorithm that ignores the +presence of the LSS. Numerous science goals require the most robust +probabilistic statements possible as to the location of galaxies along +lines of sight through clusters, for example, identification of +background galaxies for weak-lensing, identification of faint cluster +members to study the evolution of the luminosity function in clusters, +identification of star-forming galaxies in clusters and their infall +regions to probe the physics of quenching of star formation. +} +\activities{ +The LSST will deliver the most information rich dataset ever in +relation to the masses and internal structures of clusters and their +infall regions. Moreover, the dataset can be enhanced significantly +via the addition of data at other wavelengths, including X-ray, +millimeter, and near-infrared. +\\ +A tool is therefore envisaged, that can take an input catalogue of +cluster centres that has been obtained from LSST or any other dataset +(e.g.~\emph{Planck}, \emph{eROSITA}). The tool will pull out the +basic L2 LSST photometry of objects within a cone centred on the +cluster centre, and compute the $p(z)$ of each galaxy based on a +cluster-specific algorithm. This algorithm will take account of the +following where they are available: brightness and extent of X-ray +emission, over-density of galaxies as a function of magnitude and +colour, any available spectroscopic redshifts, amplitude and extent of +any SZ decrement/increment. The algorithm will likely adopt a Bayesian +hierarchical modelling approach to forward model the problem. The +algorithm can be tested on existing datasets from surveys such as the +Local Cluster Substructure Survey (LoCuSS), XXL, HSC data processed by +DM Stack within LSST, and any others that would like to join in. +\\ +This work has links with the work on deblending/ICL, forward modelling +of cluster and groups, environmental measures, cluster detection, +complementary data, and also work in the DESC Clusters WG via $p(z)$ +of background galaxies.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A new cluster-specific photometric redshift algorithm that can be +applied to a list of cluster detections that is itself based on LSST +or external data. +\end{enumerate} +} +\end{task} + + + +\subsection{Forward Modeling LSST Clusters and Groups} +\tasktitle{Forward Modeling LSST Clusters and Groups} +\begin{task} +\label{task:clss:cluster_fm} +\motivation{ +Most of the interesting cluster and group physics from LSST and its +union with complementary surveys will be derived from studies that +explore the full range of halo mass relevant to groups and clusters: +$M_{200}\simeq10^{13}-10^{15}M_\odot$. This is a wider range than +cluster cosmologists (e.g. colleagues in DESC, with whom we +collaborate) aim to incorporate into their cosmological inference -- +they restrict attention to $M_{200}>10^{14}M_\odot$. +\\ +Another important difference between the cluster/group physics +explored here, and the dark energy-motivated DESC work, is that the +requirement on controlling systematic biases is roughly an order of +magnitude less stringent here than in DESC. Arguably, $\sim10\%$ +control of systematic biases in weak-lensing measurements of low +redshift clusters ($\gtrsim2\times10^{14}M_\odot$) has already been +achieved (Okabe et al. 2013; Applegate et al. 2014; Hoekstra et +al. 2015; Okabe \& Smith 2016). Therefore in this Science +Collaboration we have the challenge of maintaining that level of +control down to smaller masses and out to higher redshifts. +\\ +A growing number of studies are adopting an approach of forward +modelling the cluster population simultaneously with the cosmological +model to obtain constraints on scaling relations and cosmological +parameters. Here, the idea is to borrow this same approach, but adopt +a fixed cosmological model, broaden the mass range of systems +considered, and expand the forward modeling to include additional +relationships of interest. For example, simultaneously fitting +density profile models to the shear profiles, the mass-concentration +relation, and the star-formation rates of clusters and groups. +Overall, this will provide a robust Bayesian inference code with which +to constrain the physics of galaxies and hot gas in groups and +clusters, tied directly to the halo mass function via weak-lensing. +} +\activities{ +Key activities include: +% +\begin{itemize} +\item Select the elements of the cluster population to include in the model +\item Write the first version of the code, and test on simulated (toy model and n-body) data +\item Improve code and consider extending range of physics explored by adding more relations +\item Test code on existing datasets from pointed surveys (e.g. LoCuSS, others) and wide area surveys (e.g. LoCuSS, DES, others) +\item Combine this development work other work packages within Galaxies and DESC +\end{itemize} +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Bayesian inference code to simultaneously model cluster shear +profiles, scaling relations (including and beyond cosmological scaling +relations, across the full range of halo mass of groups and clusters, +to $\sim10\%$ control on systematics. +\end{enumerate} +} +\end{task} + + + +\end{tasklist} diff --git a/old/task_lists/ddf/ddf.tex b/old/task_lists/ddf/ddf.tex new file mode 100644 index 0000000..c7f0545 --- /dev/null +++ b/old/task_lists/ddf/ddf.tex @@ -0,0 +1,76 @@ +\section{Deep Drilling Fields}\label{sec:tasks:ddf} + +The LSST Drilling-Fields (DDF) are areas that have a higher cadence and deeper observations than the Deep-Wide survey. Many of the details of the observing strategy have yet to be finalized. Four Deep-Drilling fields have been selected. Whether to include any others will be part of a complex trade involving other special projects that depart from the Deep-Wide survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy are all still under study, and the Project needs input from the science collaborations to inform these decisions. The tasks outlined in this section are intended to help optimize the LSST observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy-evolution science. + +\begin{tasklist}{DDF} + +\subsection{Coordinating Ancillary Observations} +\tasktitle{Coordinating Ancillary Observations} +\begin{task} +\label{task:ddf:ancillary_obs} +\motivation{ +It is crucial that the LSST deep-drilling fields be supported by observations from other facilities. While the LSST data by themselves will be unique in having deep and accurate photometry, good image quality, and time-series sampling, the amount of information in six bands of relatively broad optical imaging is quite limited. Estimates of photometric redshifts and stellar-population parameters (e.g. mass and star-formation rate) are greatly improved with long-wavelength data. Combining these quantities with information on dust and gas from far-IR, mm and radio observations allows one to build and test models that track the flow of gas in and out of galaxies. Deep and dense spectroscopy is essential both providing precise redshifts, calibrating photometric redshifts, and measuring physical properties of galaxies. Properly supported by this additional data, the LSST DDFs will become the most valuable areas of the sky for galaxy-evolution science. The central regions of the four fields already selected are already in this category; the main challenge is filling out the much larger area subtended by the LSST field of view. +} +\activities{ +The major challenge in supporting the Deep Drilling Fields is the huge investment of telescope time. There is a need for coordination across facilities and collaborations to make the most efficient use of this time. Coordination is certainly happening somewhat haphazardly, but there has not to date been a dedicated effort to get all the potential stakeholders involved in developing a coherent plan. The LSST science collaborations can and should be taking the lead here. The SERVS program to observe the already-designated DDFs with Spitzer is a good example of where this has happened (Manduit et al. 2012), but there is much more to be done. Activities include: +\begin{itemize} +\item Workshops to discuss LSST DDF coordination +\item Proposals for major surveys or even new instrumentation to provide supporting data +\item Executing those supporting programs +\item Working to integrate the data from those programs with the LSST data +\item Working to enable DDF support through policies and strategic planning at major observatories +\end{itemize} +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Workshops on LSST DDF supporting observations +\item Annually updated roadmap of supporting observations (conceived, planned or executed) +\item Public Release of data from supporting observations +\item Level 3 software to enable use of LSST data with supporting data +\end{enumerate} +} +\end{task} + +\subsection{Observing Strategy “Cadence”} +\tasktitle{Observing Strategy “Cadence”} +\begin{task} +\label{task:ddf:cadence} +\motivation{ +The LSST DDF observing strategy will need to serve diverse needs. For galaxy-evolution science, the time series aspect of the observation is less important than the depth, image quality, and mix of filters. Optimizing the observing strategy (including timing) is influenced by non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data. For example, for many science goals, completing the observations of one DDF to the final 10-year depth in the first year could be very beneficial. But there is work to be done to justify that, select the field, and find synergies with other science areas (e.g. DESC, AGN, transients). +} +\activities{ +The LSST observing strategy is optimized using the Operations Simulator (OpsSim). The Project works with the community to develop both strawman observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpsSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Figures of Merit via MAF for use by OpSim +\item Proposed observing strategies for DDFs with rationale +\item Proposing and/or helping to assess selection of additional DDFs +\end{enumerate} +} +\end{task} + +\subsection{Data Processing} +\tasktitle{Data Processing} +\begin{task} +\label{task:ddf:data_processing} +\motivation{ +Getting the most out of the DDFs may require data processing beyond that required for the Deep-Wide Survey. There are a variety of issues that ought to be considered in trying to optimize the science output. These include different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features , deblending overlapping objects, or estimating photometric redshifts. The fields are small enough that it is conceivable to process or reprocess them making use of data from supporting observations. It will clearly be advantageous to have one “official” LSST-released catalog, but defining such a catalog to support a very broad range of science is challenging. This does not preclude having additional special-purpose catalogs, but it is clearly beneficial to the advancement of extragalactic research to have a high-quality official catalog that has “buy in” from the LSST Science Collaborations. This requires time and effort both in the Project and in the Collaborations. +} +\activities{ +A major activity here is to identify the most important DDF-specific science drivers and identify any processing requirements that are distinct from the Deep-Wide survey. This ought to be coordinated with the Project and the other Science Collaborations to provide a coherent set of specifications and priorities. +\\ +Another major activity is to develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection) This may stress the inputs to the image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low-surface brightness features. Use of the supporting data sets in level 2 or level 3 processing requires careful thought. For example, source identification and photometry can be improved using pixel-level information for either Euclid or WFIRST. However, this will not be available for all the DDFs and is not in the baseline plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The collaborations need to work with the various projects to identify a clear path forward.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Science drivers and input to the development of level 2 processing of the DDFs. +\item Specifications for galaxy-evolution oriented level-3 DDF processing +\item Specifications for data-processing using supporting data from other facilities +\item Simulations tailored to the DDFs +\item Level 3 processing code +\end{enumerate} +} +\end{task} + +\end{tasklist} + + \ No newline at end of file diff --git a/old/task_lists/galaxies/galaxies.tex b/old/task_lists/galaxies/galaxies.tex new file mode 100644 index 0000000..de49c68 --- /dev/null +++ b/old/task_lists/galaxies/galaxies.tex @@ -0,0 +1,486 @@ +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: galaxies +% First draft by + +\section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} + +The LSST design, and to a certain extent the design of the data-management +system, is optimized to carry out the core science mission. For measurements +of dark-energy, that generally means treating galaxies as ``tracer particles'' -- +using statistical measures of ellipticity and position provide statistical +constraints on large-scale structure and cosmic geometry. While many of the +DESC tasks are directly relevant to studying galaxy evolution, they are +incomplete. In particular, studies of galaxy evolution require more attention to +optimizing multi-wavelength supporting data, different kinds of spectroscopy, different +kinds of simulations and theoretical support, and greater attention to detection +and characterization of low-surface brightness features or unusual morphologies. + +The task list presented here highlights the preparation work needed in the next 3-4 +years. Of primary importance are tasks that might influence the detailed survey +design or the algorithms used in the DM to construct catalogs. These are the most +urgent. Also included are activities that can be reasonably independent of the +LSST survey design and DM optimization, but which will ensure good support for +LSST galaxy studies. + +%\begin{tasklist}{G} +%\subsection{Example Task List} +%\tasktitle{Example Task List} +%\begin{task} +%\label{task:label_for_this_task} +%\motivation{Put Science Motivation Here} +%\activities{Described Activities Here} +%\deliverables{ +% Deliverables over the next several years from the activities described above include the following: +% \begin{enumerate} +% \item a deliverable +% \item another deliverable +% \end{enumerate} +%} +%\end{task} +%\end{tasklist} + +\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} + +\begin{tasklist}{G-TAS} +\tasktitle{Techniques for finding low-surface-brightness features or galaxies} +% Tidal streams +% Intracluster diffuse light +\begin{task} +\label{task:gal:lsb} +\motivation{ +A huge benefit of LSST relative to prior large-area surveys will be its ability to detect +low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and +other features associated with past and ongoing mergers, it includes intra-cluster and +intra-group light, and it includes relatively nearby, extended low-surface-brightness galaxies. +Prior to LSST, typical studies of the low-surface-brightness universe have focused +on relatively small samples, often selected by criteria that are difficult to quantify +or reproduce in theoretical models. Measurements of the LSB features themselves themselves +are challenging, often requiring hand-tuning and interactive scientific judgment. This is +important for accurately quantifying what we observe, but such interactive tuning +of the measurements (a) is not something that can be applied on the LSST scale and (b) +is difficult to apply to theoretical models. For LSST it is crucial that we automate +the detection and characterization of LSB features, at least to the point where samples +for further study can be selected via database queries, and where the completeness of +samples returned from such queries can be quantified. +} + +\activities{ +Several activities are of crucial importance: (1) simulating realistic LSB features, (2) +using the simulations to optimize detection and measurement, (3) ensuring that LSST +level-2 processing strategies and observing strategies are at least cognizant +of needs of LSB science and (4) developing a strategy for finding and measuring LSB features through +some combination of level 2 measurements, database queries, and level 3 processing.\\ +It is important to insert realistic low-surface-brightness +features into LSST simulated images and try to extract and measure them, exploring +different techniques or algorithms for doing the detection and measurement. Because the LSB objects +are sparse on the sky, making realistic LSST sky images is probably not the most efficient +way to accomplish this; more targeted simulations with a higher density of +LSB objects are needed. The simulated observations need to be realistic in their +treatment of scattered light, particularly scattering from bright stars which +may or may not be in the actual field of view of the telescope. +Scattering from bright stars is likely to be the primary source of contamination +when searching for extended LSB features. Ideally, the LSST scattered-light model, +tuned by repeated observations, will be sufficiently good that these contaminants +can be removed or at least flagged at level 2. Defining the metrics for ``sufficiently good,'' +based on analysis of simulations, is an important activity that needs early work to +help inform LSST development. Including Galactic cirrus in the simulations is important +for very large-scale LSB features. Including a cirrus model as part of the LSST background +estimation is worth considering, but it is unclear yet whether the science benefit +can justify the extra effort. \\ +Because the LSST source extraction is primarily +optimized for finding faint, barely-resolved galaxies, it is going to be challenging to +optimize simultaneously for finding large LSB structures and cataloging them as +one entity in the database. For very large structures, analysis of the LSST ``sky background'' +map, might be the most productive approach. We need to work with the LSST project +to make sure the background map is stored in a useful form, and that background +measurements from repeated observations can be combined to separate the fluctuating +foreground and scattered light from the astrophysically interesting signal from extended +LSB structures. Then, we need strategies for measuring these background maps, characterizing +structures, and developing value-added catalogs to supplement the level 2 database.\\ +For smaller structures, it is likely that the database will contain pieces +of the structure, either as portions of a hierachical +family of deblended objects, or cataloged as separate objects. Therefore, we need to +develop strategies for querying the database to find such structures and either extract +the appropriate data for customized processing, or develop ways to put back together +the separate entries in the database. A possible value-added catalog, for example, from +the galaxies collaboration might be an extra set of fields for the database to indicate +which separate objects are probably part of the same physical entity. This would +be sparsely populated in the first year or two of LSST, but by the end of the survey +could be a useful resource for a wide variety of investigations. +} + +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item realistic inputs of LSB galaxies or LSB features for the LSST image simulations; +\item custom simulations; +\item algorithms for finding and measuring LSB features; +\item input to the Project on scattered-light mitigation and modeling strategies; +\item input to the project on photometric and morphological parameters to measure/store at level 2; +\item query strategies and sample queries for finding LSB structures; and +\item a baseline concept for a value-added database of LSB structures +\end{enumerate} +} +\end{task} + +\subsection{Techniques for identifying and deblending overlapping galaxies} +\tasktitle{Techniques for identifying and deblending overlapping galaxies} +\begin{task} +\label{task:gal:deblending} +\motivation{ +The Level 2 data products are the most relevant starting point +for galaxy-evolution science. In the LSST nomenclature, {\tt Objects} +represent astrophysical entities (stars, galaxies, quasars, etc.), while +{\tt Sources} represent their single-epoch observations. +The master list of Objects in Level 2 will be generated by associating +and deblending the list of single-epoch source detections and the +lists of sources detected on coadds. The exact strategies for doing +this are still under active development by the LSST project, and +engagement with the science community is essential. While each +data release will have unique object IDs, it will be a huge impediment +for LSST science if the first few generations of catalogs turn out +severely the limit the science that can be done via database queries. \\ +For galaxies science, the issue of deblending is of critical importance. +For example, searches for high-redshift galaxies via color selection +or photometric redshifts involve model or template spectra that make +the prior assumption that the object in question is a single object at +one redshift, not a blend of two objects at two different redshifts. +Therefore to get a reliable estimate of the evolution of classes of galaxies +over redshift, we need to (a) have reasonably clean catalogs to start with +and (b) be able to model the effects of blending on the sample selection +and derivation of redshift and other parameters. This is critical +not just for galaxy-evolution science, but for lensing and large-scale +structure studies. This is just one example. Another is the evolution +of galaxy morphologies, where the effects of blending and confusion +may well be the dominant source of uncertainty. \\ +The plan for the level-2 catalogs is that sources are hierarchically +deblended and that this hierarchy is maintained in the catalog. +Scientifically important decisions are still to be made about whether +and how to use color information in the deblending, and how to divide +the flux between overlapping components. Even if the Project is doing +the development work, engagement with the community is important for +developing tests and figures of merit to optimize the science return. +} +\activities{ +Preparations for LSST in this area involve working both with simulations +and real data. The current LSST image simulations already have realistic source densities, +redshift distributions, sizes, and color distributions. However, the +input galaxies do not have realistic morphologies. At least some simulations +with realistic morphologies are needed, especially for the Deep Drilling Fields. +Inputs should come both from hydrodynamical simulations (where ``truth'' is known), +{\it Hubble} images, and images from precursor surveys such as CFHTLS, DES and HyperSuprimeCam. +The science collaborations should help provide and vet inputs. \\ +More challenging is to come up with techniques and algorithms to improve the +deblending. When two galaxies at different redshifts overlap, using observations +from all the LSST filters and perhaps even EUCLID and WFIRST might +help to disentangle them. Some attempts have been made over the past few years +to incorporate color information into the deblending algorithm, but this needs +much more attention, not only for developing and testing algorithms, but for +deciding on figures-of-merit for their performance. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item providing realistic galaxy image inputs to the ImSim team; +\item developing tests and figures of merit to quantify the effects on several science objectives; +\item assessing the current baseline plan for level-2 deblending and for parameter estimation for blended objects; and +\item developing prototype implementations of deblending algorithms that take advantage of the LSST color information. +\end{enumerate} +} +\end{task} + +\subsection{Optimizing Galaxy Morphology Measurements} +\tasktitle{Optimizing Galaxy Morphology Measurements} +% techniques for identifying mergers +% Bayesian techniques for inference from large data sets +% Merging human classification and machine learning +\begin{task} +\label{task:gal:morphology} +\motivation{ +Measurements of galaxy morphologies are an important tool for constraining models +of galaxy evolution. While fairly simple measures of galaxy ellipticity and position +angles may be sufficient for the Dark Energy science goals, other kinds of +measurements are needed for galaxy-evolution science. The ``multifit'' approach of +fitting simple parametric models to galaxy profiles has been the baseline plan. +This will be useful but insufficient. For well-resolved galaxies it is desirable +to have separate measures of bulge and disk, and spiral-arm structure, measures of +concentration, asymmetry, and clumpiness. These ought to be measured as part of +the level 2 processing, to enable database queries to extract subclasses of galaxies. +Both parametric and non-parametric measures are desirable. +While there will no doubt be optimization in level 3 processing, it is important +to have enough information in the level 2 output products to pick reasonable subsets +of galaxies. +} +\activities{The preparation work, therefore, focuses on defining measures to enable +these queries. Two aspects of LSST data make this a significant research project: +the fact that LSST provides multi-band data with a high degree of uniformity, and the +fact that the individual observations will have varying point-spread functions. +The former offers the opportunity to use much more information than has been +generally possible. The latter means that it will take some effort to optimize and +calibrate the traditional non-parametric measure of morphology (e.g. the CAS, GINI and M20 parameters), +develop new LSST-optimized parameters, and optimize their computation to avoid +taxing the level-2 pipeline.\\ +Given the very large data set and the uncertainty in how to use specific morphological +parameters to choose galaxies in certain physical classes (e.g. different merger +stages or stages of disk growth), it is important to have extensive +training both from hydrodynamical simulations +with dust (where physical truth is known, even if the models are imperfect) and +from observations where kinematics or other information provide a good +understanding of the physical nature of the object. These training sets ought to +be classified by humans (still the gold-standard for image classification) and via +machine-learning techniques applied to the morphological measurements. A series +of ``classification challenges'' prior to the LSST survey could help to refine the techniques. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item providing realistic galaxy image inputs for classification tests to the ImSim team; +\item human classification of the images; +\item machine-learning algorithms to be tested and developed into suitable SQL queries; +\item developing a menu of candidate morphological measurements for level 2 and level 3 processing; and +\item developing tests and figures of merit to quantify the effects on several science objectives. +\end{enumerate} +} +\end{task} + +\subsection{Optimizing Galaxy Photometry} +\tasktitle{Optimizing Galaxy Photometry} +% background subtraction +% optimal co-adds +% best flux estimator +% image quality metrics +% forced photometry with separate central point source (important for AGN) +% Using high-resolution priors where available +\begin{task} +\label{task:gal:photometry} +\motivation{ +Systematic uncertainties will dominate over random uncertainties for almost any +research question one can imagine addressing with LSST. The most basic measurement +of a galaxy is its flux in each band, but this is a remarkably subtle measurement +for a variety of reasons: galaxies do not have well-defined edges, their shapes +vary, they have close neighbors, they cluster together, and lensing affects both +their brightness and clustering. These factors all affect photometry in systematic +ways, potentially creating spurious correlations that can obscure or masquerade as +astrophysical effects. For example, efforts to measure the effect of neighbors +on galaxy star-formation rates can be thrown off if the presence of a neighbor +affects the basic photometry. Measurements of galaxy magnification or measurements +of intergalactic dust can be similarly affected by systematic photometric biases. +It is thus important to hone the photometry techniques prior to the survey to +minimize and characterize the biases. Furthermore, there are science topics that +require not just photometry for the entire galaxy, but well-characterized photometry +for sub-components, such as a central point-source or a central bulge. +} +\activities{ +The core photometry algorithms will end up being applied in level 2 processing, +so it is important that photometry be vetted for a large number of potential +science projects before finalizing the software. Issues include the following. +(1) Background estimation, which, for example, can greatly affect the photometry +for galaxies in clusters or dwarfs around giant galaxies. (2) Quantifying the +biases of different flux estimators vs. (for example) distances to and fluxes +of their neighbors. (3) Defining optimal strategies to deal with the varying +image quality. (4) Defining a strategy for forced photometry of a central point +source. For time-varying point-sources, the image subtractions will give a +precise center, but will only measure the AC component of the flux. Additional +measurements will be needed to give the static component. (5) Making use +of high-resolution priors from either Euclid or WFIRST, when available. +Because photometry is so central to much of LSST science, there will need to +be close collaboration between the LSST Project and the community. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item developing metrics for various science cases to help evaluate the level 2 photometry; +\item providing realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies); +\end{enumerate} +Deliverables over the longer term include develping optimal techniques for forced photometry +using priors from the space missions. +} +\end{task} + +\subsection{Optimizing Measurements of Stellar Population Parameters} +\tasktitle{Optimizing Measurements of Stellar Population Parameters} +% Strategies for dealing with strong covariance of parameter estmates +\begin{task} +\label{task:gal:stellarpops} +\motivation{ +The colors of galaxies carry information about their star-formation histories, +each interval of redshift being a snapshot of star-formation up until that time. +Unfortunately, estimates of star-formation rates and star-formation histories +for a single galaxy based on only the LSST bands will be highly uncertain, +due largely to degeneracies between age, dust extinction and metallicity. +Strategies for overcoming the degeneracies include hierarchical modeling -- using +ensembles of galaxies to constrain the hyper-parameters that govern +the star-formation histories of sets of galaxies rather than individuals, +and using ancillary data from other wavelengths. +} +\activities{ +Activities in this area include developing scalable techniques for +hierarchical Bayesian inference on very large data sets. These can be +tested on semi-analytical or hydrodynamical models, where the answer is known, +even if it does not correctly represent galaxy evolution. The models should +also be analyzed to find simple analytical expressions for star-formation +histories, chemical evolution and the evolution and behavior of dust to +make the Bayesian inference practical.\\ +Another important activity is to identify the ancillary data sets and +observing opportunities, especially for the deep fields. +} +\deliverables{ +Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item developing and refining techniques for constraining star-formation histories of large ensembles of galaxies; +\item providing model inputs to guide in developing these techniques; +\item refining the science requirements for ancillary multi-wavelength data to support LSST. +\end{enumerate} +} +\end{task} + + +\begin{comment} + +\subsection{Software Integration} +\tasktitle{Software Integration} +% Level 2 and Level 3 software +\begin{task} +\label{task:gal:integration} +\motivation{ +The LSST Project is responsible for level 2 data processing, and the community +is expected to any processing beyond that as level 3. Furthermore, some algorithms developed +as part of the level 3 effort are expected to migrate to level 2. There needs +to be strong coordination between the Project and the community for this concept +to work. This includes training in developing level 3 software and community engagement in +defining the requirements and interfaces. +} +\activities{ +The most urgent activity is to develop some early prototypes of level 3 software +so that the interfaces can be worked out on realistic use cases. +} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{Precursor Observations or Synergy with Other Facilities} \label{sec:tasks:gal:precursor} + +\begin{tasklist}{G-PO} +\tasktitle{Redshift surveys in the Deep Drilling fields} +\begin{task} +\label{task:gal:redshift_surveys_dd_fields} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Ancillary Data in Deep Drilling fields} +\begin{task} +\label{task:gal:ancillary_data_dd_fields} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Photometric redshift training and calibration} +% Emphasize differences in requirements relative to DE +\begin{task} +\label{task:gal:photz_calibration} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Joint use of spectroscopic and photometric redshifts} +\begin{task} +\label{task:gal:spec_plus_phot_redshifts} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulations} + +\begin{tasklist}{G-TS} +\tasktitle{Image simulations of galaxies with complex morphologies} +% Mergers +% Tidal features +% Stellar halos +% Vary the galaxy-evolution model +\begin{task} +\label{task:gal:image_simulations} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Rare objects} +% extreme over/underdensities +% massive early galaxies +% extremely supermassive black holdes +\begin{task} +\label{task:gal:rare_objects} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Cosmic Variance estimators} +% Develop simple tools...encourage their use +\begin{task} +\label{task:gal:cv_estimators} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Nearby dwarfs: surface brightness fluctuations} +\begin{task} +\label{task:gal:dwarf_sb_fluctuations} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Testing group and void finders} +\begin{task} +\label{task:gal:group_finders} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\end{tasklist} + +\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} + +\begin{tasklist}{G-DDS} +\tasktitle{Data structures to characterize survey biases and completeness} +\begin{task} +\label{task:gal:data_structures} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Queries to find unusual class of objects} +% mergers +% tidal streams +% nearby dwarf candidates +% morphologically disturbed close pairs +\begin{task} +\label{task:gal:queries} +\motivation{} +\activities{} +\deliverables{} +\end{task} + +\tasktitle{Compact representations of likelihood functions} +\begin{task} +\label{task:gal:likelihoods} +\motivation{} +\activities{} +\end{task} + +\end{comment} + +\end{tasklist} diff --git a/old/task_lists/high_z/high_z.tex b/old/task_lists/high_z/high_z.tex new file mode 100644 index 0000000..214509a --- /dev/null +++ b/old/task_lists/high_z/high_z.tex @@ -0,0 +1,59 @@ +\section{High-Redshift Galaxies}\label{sec:tasks:high_z} + +Observations of distant galaxies provide critical information +into the efficiency of the galaxy formation process, the end +of the reionization era, the early enrichment of the intergalactic +medium, and the initial conditions for the formation of modern +galaxies at later times. Through its wide area and sensitivity +in $zy$ LSST will probe galaxies out to $z\sim7$, and will probe +yet further in conjuction with future wide-area infrared surveys. +The following science tasks address outstanding preparatory work +for maximizing high-redshift science with LSST. + +\begin{tasklist}{HZ} + +\subsection{Optimizing Galaxy Photometry for High-Redshift Sources} +\tasktitle{Optimizing Galaxy Photometry for High-Redshift Sources} +\begin{task} +\label{task:high_z:photometry} +\motivation{ +The identification and study of high-redshift galaxies with LSST hinges on reliable, accurate and optimal measurements of the galaxy flux in all LSST passbands. +Galaxies at redshifts above 7 will only be detected in the LSST y-band and will be non-detections or ``drop-outs'' in the other LSST filters. Galaxies at redshifts above 8 will not be detected at all in the LSST filters but combining LSST with infrared surveys such as Euclid and WFIRST would enable this population to be identified. It is particularly important to have robust flux measurements and robust flux limits for the undetected high-redshift galaxies in the blue LSST filters so this information can be utilized in the high-redshift galaxy selection. Since Euclid and WFIRST are space-based missions with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogenous flux measurements for sources across the different surveys. +\\ +It is not clear if the current Level 2 data products package will meet all the requirements for high-redshift science with LSST and this therefore needs to be investigated before the start of the survey. +} +\activities{ +Firstly, we need to get a clearer picture of what constitutes the LSST Level 2 data products so we can assess whether these will be adequate for the high-redshift science. Issues that we need to understand are: 1) Will photometric catalogues be produced using the reddest LSST (e.g. y-band) images as the detection image? This is critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. 2) When computing model galaxy fluxes, will negative fluxes be stored? Negative fluxes for undetected galaxies together with their corresponding errorbars, provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. + \\ +The second major activity will be determining the best approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection. We will need to determine the optimal measure of an optical-IR colour for sources from these two datasets. There is the additional complication that sources that are resolved in the Euclid/WFIRST data could be blended in LSST and will therefore need to be accurately de-blended, perhaps using the high-resolution IR data as a prior, before a reliable flux and colour measurement can be made. Tests can be run using existing datasets e.g. from the Dark Energy Survey (DES) and HST.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Determine what constitutes LSST Level 2 data products and document what additional data products will be required for high-redshift science. +\item Develop tools to produce optimal combined photometry from ground and space-based surveys and test these on existing datasets. +\end{enumerate} +} +\end{task} + +\subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} +\tasktitle{High-Redshift Galaxies and Interlopers in LSST Simulations} +\begin{task} +\label{task:high_z:interlopers} +\motivation{ + Before the start of LSST operations, it is important that we are able to test our selection methods for high-redshift galaxies on high-fidelity simulations. Given the wide-field coverage of LSST, it will be uniquely positioned to uncover large samples of the most luminous and massive high-redshift galaxies at the Epoch of Reionisation and beyond. The most significant obstacle to selecting clean samples of such sources from the photometric data, is the presence of significant populations of interlopers e.g. cool stars in our own Milky Way and low-redshift, dusty and/or red galaxies, both of which can mimic the colours of high-redshift sources. Using the LSST simulations, we want to be able to devise the most effective way of separating these different populations, and utilising both photometric and morphological information for the sources. Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA infrared surveys, we expect at least some of the most luminous z > 6 galaxies to be spatially resolved in the LSST images. +} +\activities{ +Liaise with the LSST simulations working group to ensure that high-redshift galaxies have been incorporated into the simulations with a representative set of physical properties (e.g. star formation histories, UV-slopes, emission line equivalent widths, dust extinction, metallicity). It is also important that the high-redshift galaxies have the correct number density and size distribution in the simulations. The latter will allow us to investigate how effectively we can use morphology to separate these galaxies from interlopers. +\\ +In addition to the high-redshift galaxies, it is equally important from a high-redshift science perspective, that interlopers have been incorporated into the simulations with the correct number densities and colours. Interlopers of particular relevance to the high-redshift searches will be cool stars in our own Milky Way (e.g. L and T-dwarf stars) as well as populations of very red, massive and/or dusty galaxies at lower redshifts of $z\sim2$. +\\ +Finally, we may want to consider whether to include colour information in the infrared filters (e.g. those from Euclid/WFIRST) in the simulations as this information will undoubtedly help with the high-redshift selection. + } +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Incorporate high-z galaxies into LSST simulations with a realistic and representative set of properties. +\item Incorporate brown dwarfs into LSST simulations +\item Extend simulations to other datasets beyond LSST (e.g. Euclid/WFIRST filters). +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/old/task_lists/lsb/lsb.tex b/old/task_lists/lsb/lsb.tex new file mode 100644 index 0000000..b75b9c6 --- /dev/null +++ b/old/task_lists/lsb/lsb.tex @@ -0,0 +1,176 @@ +\section{Low-Surface Brightness Science}\label{sec:tasks:lsb} + +The exquisite data quality of LSST will enable a new regime in +low-surface brightness (LSB) science over large areas of the sky. The capability +to conduct unparalleled LSB science with LSST will uncover new +evidence for and measures of the cosmic merger rate, reveal the +signature of hierarchical structure formation in extragalactic stellar +halos, and probe the LSB outskirts around other galaxies. The following +science tasks provide an enumeration of preparatory research tasks for +leveraging fully the LSST dataset for LSB science. + +\begin{tasklist}{LSB} +\subsection{Techniques for Finding Low-Surface Brightness Tidal Features} +\tasktitle{Techniques for Finding Low-Surface Brightness Tidal Features} +\begin{task} +\label{task:lsb:tidal_features} +\motivation{ +A key advantage of LSST over previous large-area surveys (e.g. the SDSS) is its ability to detect low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and other features associated with past and ongoing interactions, intra-cluster and intra-group light, and nearby, extended low- surface-brightness galaxies. +\\ +Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected by criteria that are difficult to quantify (e.g. visual inspection that can somewhat subjective) or reproduce in theoretical models. Automated (algorithmic) measurements of the LSB features themselves can be challenging and many past studies have relied on visual inspection for the identification and characterization of features (which may not easily applied on the LSST scale). For LSST it is highly desirable that we automate the detection and characterization of LSB features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. +} +\activities{ +Several activities are of crucial importance: +\begin{enumerate} +\item Simulating realistic LSST images and LSB features (using, e.g., high-resolution hydro simulations) +\item Identifying precursor datasets that can be used as proxies for developing LSB tools for use on LSST data +\item Using the simulations to develop algorithms for detection and measurement of LSB features +\item Applying these algorithms to the precursor datasets to test their suitability +\item Ensuring that LSST level-2 processing strategies and observing strategies are aligned with the needs of LSB science +\item Developing a strategy for finding and measuring LSB features through a combination of level 2 measurements, database queries, and level 3 processing +\end{enumerate} +It is important to produce realistic LSST images from e.g. the current generation of hydro-dynamical cosmological simulations (which faithfully incorporate both the evolution of large-scale structure and the interplay between baryons and dark matter during interactions). Scattering from bright stars (which may or may not be in the actual field of view of the telescope) is likely to be the primary source of contamination when searching for extended LSB features. Ideally, the LSST scattered-light model, tuned by repeated observations, will be sufficiently good that these contaminants can be removed or at least flagged at level 2. Defining the metrics for “sufficiently good,” based on analysis of simulated images, is an important activity that needs early work to help inform LSST development. +\\ +Including Galactic cirrus in the simulations will be important when developing strategies for detecting for large-scale LSB features. Including a cirrus model as part of the LSST background estimation is worth considering, but it is unclear yet whether the science benefit can justify the extra effort. +\\ +Because the LSST source extraction is primarily optimized for finding faint, barely-resolved galaxies, it will be challenging to optimize simultaneously for finding large LSB structures and cataloging them as one entity in the database. For very large structures, analysis of the LSST “sky background” map, might be the most productive approach. We need to work with the LSST project to make sure the background map is stored in a useful form, and that background measurements from repeated observations can be combined to separate the fluctuating foreground and scattered light from the astrophysically interesting signal from extended LSB structures. Then, we need strategies for measuring these background maps, characterizing structures, and developing value-added catalogs to supplement the level 2 database. +\\ +For smaller structures, it is likely that the database will contain pieces of the structure, either as portions of a hierarchical family of deblended objects, or catalogued as separate objects. Therefore, we need to develop strategies for querying the database to identify galaxies which are likely to have such structures. E.g. in galaxies that have LSB tidal features around them, the main body of the galaxy is likely to be disturbed and therefore asymmetric. Measures of asymmetry will therefore be useful for flagging such systems. We then need to have a strategy for either extracting the appropriate data for customized processing, or develop ways to put back together the separate entries in the database. A possible value-added catalog, for example, from the galaxies collaboration might be an extra flag in the database to indicate that a galaxy is likely to have LSB tidal features and an extra set of fields for the database to indicate which separate objects are probably part of the same physical entity. +\\ +This would be relatively sparsely populated in the initial stages of LSST. Estimates from the Stripe 82, indicate that 15\% of galaxies carry LSB tidal features (LSST will reach Stripe 82 in a single shot) but by the end of the survey will become a key resource for a wide variety of investigations. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Realistic mock LSST images from hydro cosmological simulations (including re-simulations of individual objects were necessary) with spatial resolutions of tens of parsecs. +\item Algorithms for finding galaxies with LSB features and for measuring the properties of these features. +\item Input to the Project on scattered-light mitigation and modeling strategies from the simulations. +\item Input to the Project on photometric and morphological parameters (e.g. asymmetry, residual flux fractions etc) to measure and store in the level 2 database. +\item Query strategies and sample queries for finding LSB structures. +\item A baseline concept for a value-added database of LSB structures. +\end{enumerate} +} +\end{task} + + +\subsection{Low-Surface Brightness Galaxies} +\tasktitle{Low-Surface Brightness Galaxies} +\begin{task} +\label{task:lsb:galaxies} +\motivation{ +Our objective is to investigate the most relevant and challenging aspects of the Low Surface Brightness (LSB) Universe. This has a direct baring on the range of galaxies initially formed, the properties that they have during and after their assembly, their connection to the cosmic web and ultimately to the nature of dark matter, which plays a large part in all of these processes. +\\ +By LSB we mean objects that have surface brightnesses much less than that of the background night sky and that which is typical of the Milky Way galaxy we live within. Many authors have previously shown how difficult it is to detect objects of LSB and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to the spiral galaxy that we live within. Thus the Universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? +\\ +The problem is that astronomical observations always include a signal from a background, a level we need to detect our sources above. For ground based observations the background arises locally from the atmosphere and our proximity to the Sun, scattered light from the solar system, diffuse star light from the Galaxy and a small contribution from other galaxies in the Universe. For an astronomical object to be detected it must stand out above the noise level in this background. If this noise was purely due to photon statistics then very simply all we would need to do is collect as many photons as possible and the signal would gradually appear out of the noise. However, we currently know that it is nowhere near this simple because of scattered light across the field of view (FOV), instrumental calibration uncertainties and real fluctuations in the cosmic background. For these reasons there has previously been little progress in making a definitive study of the extent and brightness limits of the LSB Universe. +\\ +Additionally, this LSB universe include a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model. The galaxy mass function at masses less than Mh ~ 1010 Msun systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via HI surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies are still quite easy to detect in LSST images. +\\ +The challenge is to identify them as nearby dwarfs and estimate their distances and hence luminosities. The dwarfs in question are low-surface-brightness galaxies, so many of the source-detection issues are common to the more general problem of detecting LSB features. LSST data allow us to focus on different issues. For certain distances and luminosities, typical dwarf spheroidal galaxies will be distinct from the vast majority of background galaxies in the radius vs apparent magnitude plane. However, there will often be overlapping background galaxies, so it is important that the de-blending and cataloging steps try to remove the overlaps and allow one to query for galaxies in the right portion of the color-size-brightness manifold. Once candidates are identified, it should be possible to tease out approximate distances for many dwarf galaxies via surface-brightness fluctuations (SBF). Once again this requires careful treatment of the background galaxies, but this step is now Level 3 processing, so can be customized much more than the detection step. More ambitiously, it is conceivable that machine-learning techniques could be trained to identify semi-resolved nearby dwarf galaxies given a suitable training set from LSST-precursor observations. +\\ +On the other extreme of LSB objects, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disc of stars and an impressive system of spiral arms only revealed in 2015. The central bulge of the galaxy is prominent, but the stellar disc and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB discs? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting SB of the LSST combined with the large FOV make this instrument unique to probe the existence of large LSBs, similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant discs like Malin 1 only make this problem worse. This is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. In addition we will be exploring the very outer regions of galaxies and so will be able to explore the connection between the decreasing surface density of baryons and the increasing significance of the dark matter component of galaxies. +\\ +One reason why this subject has made little progress over the last few years is because of the limited amount of deep large area data available. Most previous deep (CCD) surveys have been specifically designed to investigate the distant Universe and so, like the Hubble Deep Field, have concentrated on long exposures over small areas of sky. The extensive sky survey that LSST will carry out will become the state-of-the-art for years to come and offers a new and enormous LSB discovery potential. As a pointer to these exciting discoveries there have recently been relatively small-scale observations that indicate that a hidden LSB galaxy population does exit. An example is the population of LSB galaxies recently detected in the Coma and Fornax clusters, galaxies not only with astonishing LSB (>27 B mag arcsec-2), but also with some of them exhibiting effective radii similar to that of the Milky Way. This is despite both Coma and Fornax being two of the previously most studies regions of the nearby Universe. +\\ +To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5\mathrm{mag}~\mathrm{arcsec}^2$ and that from a space telescope typically an order of magnitude fainter $\approx25.0\mathrm{mag}~\mathrm{arcsec}^2$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0\mathrm{mag}~\mathrm{arcsec}^2$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28\mathrm{mag}~\mathrm{arcsec}^2$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32\mathrm{mag}~\mathrm{arcsec}^2$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into high surface brightness stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26\mathrm{mag}~\mathrm{arcsec}^2$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the Universe using LSST to at least a surface brightness level of $30\mathrm{mag}~\mathrm{arcsec}^2$. +} +\activities{ +\begin{enumerate} +\item Production of simulated data that can be passed through the LSST data reduction pipeline. +\item Analysis of simulated images to ensure that LSB features can be accurately preserved and measured. +\item The development of new object detection software specifically designed for the detection of LSB features, in particular: +\begin{itemize} +\item Objects with large size. +\item Objects near or melted with large size, bright galaxies. +\item Objects with patterns similar to galaxy streams. +\item Highly irregular and distorted objects. +\end{itemize} +\item Identification of precursor data sets that can be used to test our methods. We can use data generated using numerical simulations to look at the types of galaxies produced that have sufficient angular momentum to become LSB discs. These discs can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. We will develop new methods of detecting LSB objects. These will include pixel clustering methods and the labeling of pixels with certain properties i.e. surface brightness level, SED shape, proximity to other similar pixels etc. We will trial our methods on other currently available data sets (KIDS, CFHT etc). +\item Simulate realistic LSST images of nearby dwarf galaxies. +\item Identify nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools. +\item Develop and test the database search queries for finding candidates of several shapes and sizes. +\item Develop and test a measurement of semi-resolved ``texture'' as a candidate level 2 measurement. +\end{enumerate} +The use of ``texture'' as a means of identifying candidate nearby dwarf galaxies is something that needs near-term attention if it is to make it into level 2 processing early in the survey. This can be developed and tested on the semi- resolved-galaxy simulations, but it is also essential to test it on precursor data sets from DES, CFHTLS or HSC. +\\ +As a natural consequence of the effort that the members of this team are going to invest on the discovery and catalogue, we can foresee a long-term group effort for continuing the research once deliverables are available. A natural strategy, will be to perform several follow ups with large aperture telescopes available in Chile, with powerful instruments capable of obtaining optical, near-IR spectra, sub-mm, mm and IFU data for LSB objects. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Realistic mock LSST images. +\item An assessment of the influence of the PSF, scattered light and other instrument signals that may affect our ability to detect LSB features +\item An assessment of the effect of proposed pipeline on the detection and measurement of LSB features. +\item A baseline concept for the construction of a database of LSB features detected using LSST data. +\begin{itemize} +\item Realistic inputs of dwarf galaxies for the LSST image simulations. +\item Realistic postage-stamp simulations of semi-resolved dwarf galaxies. +\item Training set of nearby dwarfs from LSST precursor data. +\item Figures of Merit for detection and selection algorithms +\item Run LSST pipeline on both simulations and precursor data and assess performance. +\end{itemize} +\item Optimized algorithms measuring surface brightness fluctuation distances. +\item A new LSB object detection package, friendly adapted for the user. +\end{enumerate} +} +\end{task} + + + +\subsection{Probing the Faint Outskirts of Galaxies with LSST} +\tasktitle{Probing the Faint Outskirts of Galaxies with LSST} +\begin{task} +\label{task:lsb:faint_outskirts} +\motivation{ +The outskirts of nearby galaxies, loosely defined as the regions below $25-26\mathrm{mag}~\mathrm{arcsec}^2$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). +\\ +The main science driver here is understanding the assembly, formation, and evolution of galaxies. This can be studied through imaging and subsequent parametrization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar haloes. From numerical modelling we know that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo, are tightly related to the accretion and merging history. This is illustrated by the imaging of the stars in the outskirts of M31 and other local group galaxies, which show detailed structure. +\\ +Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to local group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams may be less affected by overall PSF, but more by foreground cirrus. +} +\activities{ +Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modelling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyse the outskirts. Dithering and rotation of individual imaging will need to be modelled before stacking multiple imaging. +\\ +Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Information on the stability and spatial constancy of the LSST PSF. +\item Improved control over systematics for LSB science, and other fields including weak lensing. +\end{enumerate} +} +\end{task} + + + +\subsection{Low-Surface Brightness Intracluster Light} +\tasktitle{Low-Surface Brightness Intracluster Light} +\begin{task} +\label{task:lsb:icl} +\motivation{ +The Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. It is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. +\\ +Some outstanding scientific questions, which LSST could solve: +\begin{itemize} +\item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? +\item Does it contain significant substructure? +\item What is its surface brightness profile and does it have a colour dependence, which would indicate age/metallicity gradients? +\item Where does the ICL begin and the large diffuse cD halo of the Brightest Cluster Galaxy (BCG) end and do they have the same origin? +\end{itemize} +} +\activities{ +The preparation work for the ICL component of the LSB case involves investigating LSST specific issues for large LSB features and the known properties of the ICL itself. +\\ +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce low surface brightness signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for the LSB team to liaise with LSST strategy, telescope, instrument and data reduction teams. +\\ +The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Investigate any telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. +\item Investigate observation specific issues that affect the measurement of large LSB features: dither pattern strategy. +\item Investigate image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. +\item Feasibility: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? +\item Investigate stacking clusters to obtain faint ICL - this is difficult as will require very strong masking of even the faintest observable cluster members. +\end{enumerate} +} +\end{task} +\end{tasklist} \ No newline at end of file diff --git a/old/task_lists/photo_z/photo_z.tex b/old/task_lists/photo_z/photo_z.tex new file mode 100644 index 0000000..2166542 --- /dev/null +++ b/old/task_lists/photo_z/photo_z.tex @@ -0,0 +1,157 @@ +\section{Photometric Redshifts}\label{sec:tasks:photo_z} + +For a photometric survey like LSST, the ability to measure +vast distances to galaxy samples, understand the time evolution +and spatial clustering of galaxy populations, surmise the +stellar mass, age, and metallicity of objects, and to identify +unusual objects at various cosmic epochs relies heavily on +methodologies for constructing photometric redshifts from the data. +The following important preparatory science tasks address both the +systematic uncertainties on photometric redshifts associated +with the LSST observatory and with the requisite +stellar population synthesis models. + +\begin{tasklist}{PZ} +\subsection{Impact of Filter Variations on Galaxy photo-z Precision} +\tasktitle{Impact of Filter Variations on Galaxy photo-z Precision} +\begin{task} +\label{task:photo_z:filter_variations} +\motivation{ +For accurate photometric redshifts, well calibrated photometry is essential. Variations in the telescope system, particularly the broad-band ugrizy filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of local environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane. Such corrections will be SED dependent, and may leave residuals, particularly for specific populations with unusual SEDs. Tests of the amplitude of these residuals, and the impact on photo-z as a whole, and for particular object classes, is an important consideration. Beyond this, if the variations turn out to be very well calibrated, they could potentially be used to further improve, rather than degrade, photo-z performance. The variations in filter response can offer up additional a small amount of extra information on the object SED, given the slight variation in effective filter wavelength, particularly for objects with strong narrow features, i.e. emission lines. Tests of how much information is gained can inform whether or not the extra computational effort used in computing photo-z’s from many slightly different filters as opposed to measurements corrected to the six fiducial filters of the survey. +} +\activities{ +Tests of the SED-dependent residuals in photometric redshifts induced by photometric calibration systematics.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Improved photometric calibration for LSST across all pass bands. +\item Identification of SED classes where photometric redshift failures are prominent. +\end{enumerate} +} +\end{task} + +\subsection{Photometric Reshifts in the LSST Deep Drilling Fields} +\tasktitle{Photometric Reshifts in the LSST Deep Drilling Fields} +\begin{task} +\label{task:photo_z:ddf} +\motivation{ +The LSST Deep Drilling Fields present different challenges than the main survey, including more confusion between sources, and the ability to use the best subsets of the images due to their being many repeat observations. These properties allow investigations of galaxies of brightness close to the noise in the main survey at higher signal to noise. +} +\activities{ +Assessing robustness of photo-zs with spectroscopic surveys will be difficult at the faintest fluxes, but the relationship to clustering redshifts is critically important. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item {\bf TBD} +\item {\bf TBD} +\end{enumerate} +} +\end{task} + +\subsection{Multivariate Physical Properties of Galaxies from Photometric Redshifts} +\tasktitle{Multivariate Physical Properties of Galaxies from Photometric Redshifts} +\begin{task} +\label{task:photo_z:physical_properties} +\motivation{ +The knowledge of the derived physical properties underlies much of the work involving galaxies and their evolution. Derived physical properties include, among others: star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity. When it comes to scientific analysis, in recent years the derived physical properties have largely supplanted fluxes and luminosities in the UV, optical and near-IR bands. This is because derived properties require no redshift (K) corrections, are dust-corrected, and are therefore easier to relate across surveys and studies and to compare with the models. Stellar mass has emerged as a parameter of choice for selecting galaxy types and making apple-to-apple comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a rough estimate of galaxy’s SF history. Dust attenuation and stellar metallicity are also indicative of various processes important for understanding galaxy evolution. +} +\activities{ +Deriving physical properties, usually accomplished by spectral energy distribution (SED) fitting, is an involved process and the results depend on the number of factors, including: underlying population models, assumed dust attenuation law, assumed star formation histories, choice of model priors, choice of IMF, emission line corrections, choice of input fluxes, type of flux measurements, treatment of flux errors, SED fitting methodology, interpretation of the resulting probability distribution functions (PDF) (e.g., Salim et al. 2016). In the case of LSST, the additional challenge is that the redshifts are for the most part photometric, and carry a PDF (a measure of uncertainty) of their own. In principle, the redshifts could be determined as part of the SED fitting (and vice versa, physical parameters can be obtained from some photo-z codes), but it is not clear whether this joint approach is the best. Alternatives are to use empirical training sets to obtain the photo-z (some “best” estimate or a PDF) and then feed it into the SED fitting code. +\\ +Activities will consist of testing whether the determination of physical parameters and photo-z should be performed jointly or not, based on training sets with spectroscopic redshifts, at a range of redshifts. Furthermore, testing should be performed on mock galaxies to understand which choices of methods and assumptions (specifically related to LSST data) produces the best results in the sense of retrieving the “known” properties. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-z and properties, together with the software to be used. +\item With LSST data: the production of catalogs of properties to be used by the collaboration. +\end{enumerate} +} +\end{task} + +\subsection{Identifying Spectroscopic Redshift Training Sets for LSST} +\tasktitle{Identifying Spectroscopic Redshift Training Sets for LSST} +\begin{task} +\label{task:photo_z:specz_training_sets} +\motivation{ +Require deep spectroscopic redshift data in order to help train algorithms, improve algorithms with clustering etc, and also provide a basis for determining accuracy of photo-z algorithms. +} +\activities{Collate existing spectroscopic redshift data over both DDF and wider fields, along with selection biases for each spectroscopic data set. Assess robustness of existing data, determine colour space where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item {\bf TBD} +\item {\bf TBD} +\end{enumerate} +} +\end{task} + +\subsection{Develop Techniques to Identify Specific Sub-Populations of Galaxies} +\tasktitle{Develop Techniques to Identify Specific Sub-Populations of Galaxies} +\begin{task} +\label{task:photo_z:subpops} +\motivation{ Studying properties related with the star formation activity of galaxies, such as color and specific star formation rate (sSFR), as a function of mass, environment and redshift is relevant for understanding the different physical processes in galaxy formation and evolution. The aim is to develop techniques in order to identify specific sub-populations with the aforementioned properties (e.g. blue/star-forming and red/quenched galaxies) based on photometric data. Another interesting sub-population is galaxies which contain an active nucleus. The identification of AGN candidates will also be explored. +\\ +This task is potentially cross-cutting with the theory/mock catalogs, machine learning, clusters, lss, AGN, and DESC working groups and collaborations. +} +\activities{ +We can use simulations and mock catalogs to obtain prior estimates of the calibrations used to identify specific galaxy sub-populations. These calibrations will depend on mass and redshift (z). One technique to explore is fitting two Gaussians to the corresponding color and sSFR distributions in different mass and redshift bins to identify populations of red and blue galaxies. It is important that the mass definition assumed in the mocks be comparable to that estimated for observations. Note that the stellar mass would be used as the alpha parameter in the joint probability distribution functions, p(z,alpha). +\\ +Furthermore, we will make efforts to identify AGNs to obtain a sample of AGN candidates and, also, isolate them from “normal” galaxy samples without AGNs. The information of color and star formation described above can be used for this aim. +\\ +The techniques can be probed as a function of environment, which can be defined using different approaches at both small and large scales (e.g. number of neighbor galaxies, location in large-scale structures such as filaments, voids, knots, or Voronoi tessellation techniques). This would enable the characterization of galaxy sub-populations according to the environment. The resulting galaxy sub-populations can be used as training sets to be implemented on machine learning models. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Obtaining mass from mock catalogs compatible with the mass used in p(z,mass). +\item Developing techniques that depend on this mass and redshift using mock catalogs for selecting samples with red/blue colors. +\item Developing multiple techniques that depend on this mass and redshift using mock catalogs for selecting star-forming/quenched samples. +\item Developing techniques that may depend on star formation, color and redshift for selecting AGN samples. +\item Defining several environment estimators in simulated datasets. +\item Probing techniques in b), c) and d) as a function of the environments defined in e). +\item Obtaining training sets to be implemented on machine learning models. +\end{enumerate} +} +\end{task} + +\subsection{Simulations with Realistic Galaxy Colors and Physical Properties} +\tasktitle{Simulations with Realistic Galaxy Colors and Physical Properties} +\begin{task} +\label{task:photo_z:color_simulations} +\motivation{ +As representative samples of spectroscopic redshifts will be very difficult to compile for LSST, simulations will play a key role in calibrating estimates of physical properties such as galaxy stellar mass, star formation rate, and other properties. This is particularly problematic for photometric surveys, where photometric redshift and physical property estimates must be calculated jointly. In addition, we must include prominent effects that will influence the expected photometric performance, for example the presence of an active galactic nucleus can significantly impact the color of a galaxy and the inferred values for the physical parameters, so models of AGN components of varying strength must be included in the simulations. Many current generation simulations cannot or do not simultaneously match observed color distributions and physical property characteristics for the galaxy population at high redshift. As photo-z algorithms are highly dependent on accurate photometry, realistic color distributions are required to test the bivariate redshift-physical property estimates. Working with the galaxy simulations and high redshift galaxy working groups to develop new simulations with more accurate high redshift colors is a priority. These photo-z needs are not unique, and the improved simulations will benefit the wider Collaboration as a whole. +} +\activities{ +The main activity for this task is to bring together the knowledge gained from observational studies of high redshift galaxies to act as input for improved simulation metrics. This will require expertise from the photo-z group, the high redshift galaxies group, the AGN group, and the simulations group. In order to test whether mock high-z populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions. Assuming that the simulations are valid beyond the test intervals, we can then test bivariate photo-z/physical process determinations to develop improved algorithms. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Determination of a list of which physical parameters are important for galaxy science. +\item Compiling observable datasets that can be used as comparators for simulated datasets. +\item Developing a set of metrics to compare simulations to the observational data. +\item Use the metrics in deliverable B to create updated simulations with more realistic parameter distributions. +\item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc.). +\end{enumerate} +} +\end{task} + +\subsection{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} +\tasktitle{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} +\begin{task} +\label{task:photo_z:size_and_sb_priors} +\motivation{ +Photometric redshift algorithms traditionally use galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information in the form of the galaxy’s size/shape/surface brightness (SB) profile adds additional information that can aid in constraining both the redshift and type of the galaxy, breaking potential degeneracies that using colors alone would miss. Adding type information beyond just the rest frame SED may help to constrain bivariate galaxy properties that correlate with morphological type as well. If sufficient training samples are available, a Bayesian prior on colors and SB profile, p(z|C,SB), can be constructed that should lead to improved photometric redshifts. +} +\activities{ +The primary activity in this task is to develop an algorithm to compute a parameterized SB profile fit (e.g. Sersic index, though other measures may be appropriate) for a large number of galaxies. The algorithm must be fast enough to compute SB profiles for large numbers of galaxies. Simulated datasets may be necessary to calibrate this code in the limits of galaxy sizes approaching the size of the PSF, and in the limit of low signal-to-noise ratios. With SB measurements in hand, the computation of a Bayesian prior on redshift given galaxy photometry and SB. This can be done with either simulated datasets, or real observations with spectroscopic redshifts. Tests will then show the performance of such a prior relative to using galaxy photometry alone. +} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A fast, scalable algorithm for measuring the surface brightness profile of galaxies. +\item A cross matched catalog with objects at known redshifts and measured surface brightness profiles. +\item A Bayesian prior $p(z|C,SB)$ that can be used to improve photo-z measurements. +\end{enumerate} +} +\end{task} +\end{tasklist} + + + diff --git a/old/task_lists/task_lists.tex b/old/task_lists/task_lists.tex new file mode 100644 index 0000000..fbbea34 --- /dev/null +++ b/old/task_lists/task_lists.tex @@ -0,0 +1,30 @@ + +% LSST Extragalactic Roadmap +% Chapter: task_lists +% First draft by + +\chapter[Task Lists by Science Area]{Task Lists by Science Area} +\label{ch:task_lists} + +%\input{task_lists/chapter_intro.tex} +%\input{task_lists/black_holes/black_holes.tex} +%\input{task_lists/informatics/informatics.tex} +%\input{task_lists/lss/lss.tex} +%\input{task_lists/strong_lensing/strong_lensing.tex} +%\input{task_lists/weak_lensing/weak_lensing.tex} + +\input{task_lists/agn/agn.tex} +\newpage +\input{task_lists/clss/clss.tex} +\newpage +\input{task_lists/ddf/ddf.tex} +\newpage +\input{task_lists/galaxies/galaxies.tex} +\newpage +\input{task_lists/high_z/high_z.tex} +\newpage +\input{task_lists/lsb/lsb.tex} +\newpage +\input{task_lists/photo_z/photo_z.tex} +\newpage +\input{task_lists/tmc/tmc.tex} diff --git a/old/task_lists/tmc/tmc.tex b/old/task_lists/tmc/tmc.tex new file mode 100644 index 0000000..bd4ba11 --- /dev/null +++ b/old/task_lists/tmc/tmc.tex @@ -0,0 +1,89 @@ +\section{Theory and Mock Catalogs}\label{sec:tasks:tmc} + +A critical challenge for interpreting the vast LSST dataset +in the context of a cosmological model for galaxy formation +is the development of theory, both in the practical applications +of realistic simulations and the engineering of new physical +models for the important processes that govern the observable +properties of galaxies. The following preparatory science tasks +for LSST-related theoretical efforts range from understanding the +detail properties of galaxies that LSST will uncover to predicting +the large-scale properties of galaxy populations that LSST will probe +on unprecedented scales. + + +\begin{tasklist}{TMC} +\subsection{Image Simulations of Galaxies with Complex Morphologies} +\tasktitle{Image Simulations of Galaxies with Complex Morphologies} +\begin{task} +\label{task:tmc:complex_morphology} +\motivation{ +LSST images will contain significant information about the dynamical state of galaxies. In principle, this can be exploited to learn about their formation and evolutionary histories. Examples of such features include spiral arms, tidal tails, double nuclei, clumps, warps, and streams. A wide variety of analysis and modeling techniques can be applied to determine the past, present, or future states of observed galaxies with complex morphologies, and therefore improve our understanding of galaxy assembly. +} +\activities{ +Activities include creating synthetic LSST observations containing a wide variety of galaxies with complex morphologies, for the purpose of testing analysis algorithms such as de-blending, photometry, and morphological characterization. Supporting activities include creating databases of galaxy images from models (such as cosmological simulations) or existing optical data, analyzing them using LSST software or prototype algorithms, and distributing the findings of these studies. These analyses can be performed on small subsets of the sky and do not necessarily have to include very-large-area image simulations or match known constraints on source density. Results will include predicting the incidence of measured morphological features, optimizing level-3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Creating synthetic LSST images of galaxies with complex morphology from simulations. +\item Creating synthetic LSST images based on prior observations in similar filters. +\item Making these LSST-specific complex galaxy data products widely available. +\item Publicizing results of algorithm tests based on these simulations. +\item Assessing level-3 measurements to propose and/or apply to maximize the return of LSST catalogs for complex galaxy morphology science. +\end{enumerate} +} +\end{task} + + +\subsection{New Theoretical Models for the Galaxy Distribution} +\tasktitle{New Theoretical Models for the Galaxy Distribution} +\begin{task} +\label{task:tmc:galaxy_distribution} +\motivation{ +Our aim is to bring together key areas of expertise to meet the challenge of building synthetic, computer generated mock surveys which will be used in the preparation for Galaxy science with LSST. Surveys like LSST will collect more data than is contained in the current largest survey, the SDSS, every night for ten years. The analysis of such data demands a complete overhaul of traditional techniques and will require the incorporation of ideas from different disciplines. The mock catalogs we will produce offer the best means to test and constrain theoretical models using observational data. +Computer mock catalogs play a well established role in modern galaxy surveys. For the first time, the scientific potential of the new surveys will be limited by systematic errors rather than sampling errors driven by the volume mapped. The signals from viable, competing cosmological models are already extremely close. Distinguishing between the models requires that we build the best possible theoretical predictions to understand the measurements and how they should be analyzed. We also need to understand the errors on the measurements. +} +\activities{ +Develop a new state-of-the-art in physical models of the galaxy distribution combining models of the physics of galaxy formation with high resolution N-body simulations which track the hierarchical growth of structure in the matter distribution. The key task is to take the results of calculations in moderate volume cosmological N-body simulations and to develop schemes to embed this information into very large volume simulations. The large volume simulations will be bigger than the target survey, allowing a robust assessment of the systematic errors on large-scale structure measurements.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Physically motivated mock galaxy catalogues on volumes larger than will be sampled by LSST, with a consistently evolving population of galaxies. +\item Base catalogues of dark matter haloes and their merger trees that will be available for other theoretical models of populating these with galaxies (halo and subhalo occupation/abundance matching techniques). +\item Small volume simulations for further tests. +\end{enumerate} +} +\end{task} + +\subsection{Design of New Empirical Models for the Galaxy Distribution.} +\tasktitle{Design of New Empirical Models for the Galaxy Distribution.} +\begin{task} +\label{task:section:title} +\motivation{ +We will explore the galaxy-halo connection, using the simulations of the galaxy formation process as encapsulated in physically motivated models to build better empirical models. Empirical models can be adjusted to reproduce observational results as closely as possible, whereas physical models are computationally expensive, so only a small number of examples can be run, and the results cannot be tuned in the same way. Empirical models also have the advantage of being extremely fast, allowing large parameter spaces to be explored. +} +\activities{ +There are two stages here: one is to test current models to see how well they can reproduce the predictions of physical models and the second is to use the physical models to devise new parametrizations to describe galaxy selections for which there is little or no current observational data. This is particularly relevant for upcoming surveys which will probe regimes that remain largely unmapped.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item The evolution of the clustering predicted by the physical models may allow us to model how parameters should change in the empirical models, thereby reducing the number of parameters which we need to fit and to populate catalogs on the observer’s past lightcone. +\end{enumerate} +} +\end{task} + + +\subsection{Estimating Uncertainties for Large-Scale Structure Statistics} +\tasktitle{Estimating Uncertainties for Large-Scale Structure Statistics} +\begin{task} +\label{task:tmc:uncertainties} +\motivation{ +The ability to interpret the relation between galaxies and the matter density field will depend critically on how well we understand the errors on large-scale structure measurements. The accurate estimation of the covariance on a large-scale structure measurement such as the correlation function would require tens of thousands of simulations. +} +\activities{ +Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, based for example on perturbation theory. +Coordinate with WGs of the Dark Energy Science Collaboration as these covariance matrices can also be applied to Cosmological parameter constraints.} +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Physically motivated estimates of covariance matrices for galaxy occupation (and other) parameter searches. +\end{enumerate} +} +\end{task} +\end{tasklist} diff --git a/references.bib b/references.bib index 2c7a4c0..8d1938f 100644 --- a/references.bib +++ b/references.bib @@ -1,4 +1,3 @@ - @ARTICLE{LSSTSciBook, author = {{LSST Science Collaboration} and {Abell}, P.~A. and {Allison}, J. and {Anderson}, S.~F. and {Andrew}, J.~R. and {Angel}, J.~R.~P. and @@ -14,8 +13,35 @@ @ARTICLE{LSSTSciBook adsurl = {http://adsabs.harvard.edu/abs/2009arXiv0912.0201L}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } - +@ARTICLE{LSSTDESC, + author = {{LSST Dark Energy Science Collaboration}}, + title = "{Large Synoptic Survey Telescope: Dark Energy Science Collaboration}", + journal = {ArXiv e-prints}, +archivePrefix = "arXiv", + eprint = {1211.0310}, + primaryClass = "astro-ph.CO", + keywords = {Astrophysics - Cosmology and Extragalactic Astrophysics, High Energy Physics - Experiment}, + year = 2012, + month = nov, + adsurl = {http://adsabs.harvard.edu/abs/2012arXiv1211.0310L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} %AAAAAAAAAAA +@ARTICLE{abraham1994a, + author = {{Abraham}, R.~G. and {Valdes}, F. and {Yee}, H.~K.~C. and {van den Bergh}, S. + }, + title = "{The morphologies of distant galaxies. 1: an automated classification system}", + journal = {\apj}, + keywords = {Astronomical Models, Computerized Simulation, Galactic Clusters, Image Classification, Mathematical Models, Morphology, Sky Surveys (Astronomy), Astronomical Photometry, Atmospheric Effects, Atmospheric Turbulence, Charge Coupled Devices, Monte Carlo Method, Seeing (Astronomy)}, + year = 1994, + month = sep, + volume = 432, + pages = {75-90}, + doi = {10.1086/174550}, + adsurl = {http://adsabs.harvard.edu/abs/1994ApJ...432...75A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + @ARTICLE{abraham2003a, author = {{Abraham}, R.~G. and {van den Bergh}, S. and {Nair}, P.}, title = "{A New Approach to Galaxy Morphology. 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Methods and measurements of accurate galaxy cluster weak-lensing masses}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1208.0605}, + keywords = {gravitational lensing: weak, methods: data analysis, methods: statistical, galaxies: clusters: general, galaxies: distances and redshifts, cosmology: observations}, + year = 2014, + month = mar, + volume = 439, + pages = {48-72}, + doi = {10.1093/mnras/stt2129}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.439...48A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{atkinson2013, + author = {{Atkinson}, A.~M. and {Abraham}, R.~G. and {Ferguson}, A.~M.~N. + }, + title = "{Faint Tidal Features in Galaxies within the Canada-France-Hawaii Telescope Legacy Survey Wide Fields}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1301.4275}, + keywords = {astronomical databases: miscellaneous, catalogs, galaxies: general, galaxies: interactions, galaxies: peculiar, galaxies: statistics}, + year = 2013, + month = mar, + volume = 765, + eid = {28}, + pages = {28}, + doi = {10.1088/0004-637X/765/1/28}, + adsurl = {http://adsabs.harvard.edu/abs/2013ApJ...765...28A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{awan2016a, + author = {{Awan}, H. and {Gawiser}, E. and {Kurczynski}, P. and {Jones}, R.~L. and + {Zhan}, H. and {Padilla}, N.~D. and {Mu{\~n}oz Arancibia}, A.~M. and + {Orsi}, A. and {Cora}, S.~A. and {Yoachim}, P.}, + title = "{Testing LSST Dither Strategies for Survey Uniformity and Large-scale Structure Systematics}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1605.00555}, + keywords = {dark energy, large-scale structure of universe, surveys}, + year = 2016, + month = sep, + volume = 829, + eid = {50}, + pages = {50}, + doi = {10.3847/0004-637X/829/1/50}, + adsurl = {http://adsabs.harvard.edu/abs/2016ApJ...829...50A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} %BBBBBBBBBBB +@ARTICLE{baldry2006a, + author = {{Baldry}, I.~K. and {Balogh}, M.~L. and {Bower}, R.~G. and {Glazebrook}, K. and + {Nichol}, R.~C. and {Bamford}, S.~P. and {Budavari}, T.}, + title = "{Galaxy bimodality versus stellar mass and environment}", + journal = {\mnras}, + eprint = {astro-ph/0607648}, + keywords = {galaxies: evolution, galaxies: fundamental parameters, galaxies: luminosity function, mass function}, + year = 2006, + month = dec, + volume = 373, + pages = {469-483}, + doi = {10.1111/j.1365-2966.2006.11081.x}, + adsurl = {http://adsabs.harvard.edu/abs/2006MNRAS.373..469B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{barth2007, + author = {{Barth}, A.~J.}, + title = "{A Normal Stellar Disk in the Galaxy Malin 1}", + journal = {\aj}, + eprint = {astro-ph/0701018}, + keywords = {galaxies: individual: Malin 1, galaxies: spiral, galaxies: structure}, + year = 2007, + month = mar, + volume = 133, + pages = {1085-1091}, + doi = {10.1086/511180}, + adsurl = {http://cdsads.u-strasbg.fr/abs/2007AJ....133.1085B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{bowler2017a, + author = {{Bowler}, R.~A.~A. and {Dunlop}, J.~S. and {McLure}, R.~J. and + {McLeod}, D.~J.}, + title = "{Unveiling the nature of bright z {\sime} 7 galaxies with the Hubble Space Telescope}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1605.05325}, + keywords = {galaxies: evolution, galaxies: formation, galaxies: high-redshift}, + year = 2017, + month = apr, + volume = 466, + pages = {3612-3635}, + doi = {10.1093/mnras/stw3296}, + adsurl = {http://adsabs.harvard.edu/abs/2017MNRAS.466.3612B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + @ARTICLE{bullock2005a, author = {{Bullock}, J.~S. and {Johnston}, K.~V.}, title = "{Tracing Galaxy Formation with Stellar Halos. I. Methods}", @@ -62,6 +186,55 @@ @ARTICLE{bullock2005a adsnote = {Provided by the SAO/NASA Astrophysics Data System} } %CCCCCCCCCCC +@ARTICLE{chiang2014a, + author = {{Chiang}, Y.-K. and {Overzier}, R. and {Gebhardt}, K.}, + title = "{Discovery of a Large Number of Candidate Protoclusters Traced by \~{}15 Mpc-scale Galaxy Overdensities in COSMOS}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1312.4747}, + keywords = {cosmology: observations, galaxies: clusters: general, galaxies: evolution, galaxies: high-redshift}, + year = 2014, + month = feb, + volume = 782, + eid = {L3}, + pages = {L3}, + doi = {10.1088/2041-8205/782/1/L3}, + adsurl = {http://adsabs.harvard.edu/abs/2014ApJ...782L...3C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{choi2012a, + author = {{Choi}, A. and {Tyson}, J.~A. and {Morrison}, C.~B. and {Jee}, M.~J. and + {Schmidt}, S.~J. and {Margoniner}, V.~E. and {Wittman}, D.~M. + }, + title = "{Galaxy-Mass Correlations on 10 Mpc Scales in the Deep Lens Survey}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1208.3904}, + keywords = {cosmology: observations, dark matter, galaxies: evolution, gravitational lensing: weak, large-scale structure of universe}, + year = 2012, + month = nov, + volume = 759, + eid = {101}, + pages = {101}, + doi = {10.1088/0004-637X/759/2/101}, + adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...759..101C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{conselice2000a, + author = {{Conselice}, C.~J. and {Bershady}, M.~A. and {Jangren}, A.}, + title = "{The Asymmetry of Galaxies: Physical Morphology for Nearby and High-Redshift Galaxies}", + journal = {\apj}, + eprint = {astro-ph/9907399}, + keywords = {GALAXIES: PHOTOMETRY, GALAXIES: STRUCTURE, Galaxies: Photometry, Galaxies: Structure}, + year = 2000, + month = feb, + volume = 529, + pages = {886-910}, + doi = {10.1086/308300}, + adsurl = {http://adsabs.harvard.edu/abs/2000ApJ...529..886C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{conselice2003a, author = {{Conselice}, C.~J. and {Bershady}, M.~A. and {Dickinson}, M. and {Papovich}, C.}, @@ -77,7 +250,179 @@ @ARTICLE{conselice2003a adsurl = {http://adsabs.harvard.edu/abs/2003AJ....126.1183C}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{cooper2010a, + author = {{Cooper}, M.~C. and {Coil}, A.~L. and {Gerke}, B.~F. and {Newman}, J.~A. and + {Bundy}, K. and {Conselice}, C.~J. and {Croton}, D.~J. and {Davis}, M. and + {Faber}, S.~M. and {Guhathakurta}, P. and {Koo}, D.~C. and {Lin}, L. and + {Weiner}, B.~J. and {Willmer}, C.~N.~A. and {Yan}, R.}, + title = "{Absence of evidence is not evidence of absence: the colour-density relation at fixed stellar mass persists to z \~{} 1}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1007.1967}, + primaryClass = "astro-ph.CO", + keywords = {galaxies: evolution, formation, statistics, large-scale structure of Universe}, + year = 2010, + month = nov, + volume = 409, + pages = {337-345}, + doi = {10.1111/j.1365-2966.2010.17312.x}, + adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.409..337C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%DDDDDDDDDDD +@ARTICLE{darg2010a, + author = {{Darg}, D.~W. and {Kaviraj}, S. and {Lintott}, C.~J. and {Schawinski}, K. and + {Sarzi}, M. and {Bamford}, S. and {Silk}, J. and {Andreescu}, D. and + {Murray}, P. and {Nichol}, R.~C. and {Raddick}, M.~J. and {Slosar}, A. and + {Szalay}, A.~S. and {Thomas}, D. and {Vandenberg}, J.}, + title = "{Galaxy Zoo: the properties of merging galaxies in the nearby Universe - local environments, colours, masses, star formation rates and AGN activity}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {0903.5057}, + keywords = {catalogues, galaxies: elliptical and lenticular, cD, galaxies: evolution, galaxies: general, galaxies: interactions, galaxies: spiral}, + year = 2010, + month = jan, + volume = 401, + pages = {1552-1563}, + doi = {10.1111/j.1365-2966.2009.15786.x}, + adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.401.1552D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{driver2009a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2009A%26G....50e..12D}, + Archiveprefix = {arXiv}, + Author = {{Driver}, S.~P. and {Norberg}, P. and {Baldry}, I.~K. and {Bamford}, S.~P. and {Hopkins}, A.~M. and {Liske}, J. and {Loveday}, J. and {Peacock}, J.~A. and {Hill}, D.~T. and {Kelvin}, L.~S. and {Robotham}, A.~S.~G. and {Cross}, N.~J.~G. and {Parkinson}, H.~R. and {Prescott}, M. and {Conselice}, C.~J. and {Dunne}, L. and {Brough}, S. and {Jones}, H. and {Sharp}, R.~G. and {van Kampen}, E. and {Oliver}, S. and {Roseboom}, I.~G. and {Bland-Hawthorn}, J. and {Croom}, S.~M. and {Ellis}, S. and {Cameron}, E. and {Cole}, S. and {Frenk}, C.~S. and {Couch}, W.~J. and {Alister}, W.~G. and {Proctor}, R. and {De Propris}, R. and {Doyle}, I.~F. and {Edmondson}, E.~M. and {Nichol}, R.~C. and {Thomas}, D. and {Eales}, S.~A. and {Jarvis}, M.~J. and {Kuijken}, K. and {Lahav}, O. and {Madore}, B.~F. and {Seibert}, M. and {Meyer}, M.~J. and {Staveley-Smith}, L. and {Phillipps}, S. and {Popescu}, C.~C. and {Sansom}, A.~E. and {Sutherland}, W.~J. and {Tuffs}, R.~J. and {Warren}, S.~J.}, + Date-Added = {2017-04-25 15:30:19 +0000}, + Date-Modified = {2017-04-25 15:30:19 +0000}, + Doi = {10.1111/j.1468-4004.2009.50512.x}, + Eprint = {0910.5123}, + Journal = {Astronomy and Geophysics}, + Month = oct, + Number = 5, + Pages = {050000-5}, + Title = {{GAMA: towards a physical understanding of galaxy formation}}, + Volume = 50, + Year = 2009 +} +@ARTICLE{driver2011a, + author = {{Driver}, S.~P. and {Hill}, D.~T. and {Kelvin}, L.~S. and {Robotham}, A.~S.~G. and + {Liske}, J. and {Norberg}, P. and {Baldry}, I.~K. and {Bamford}, S.~P. and + {Hopkins}, A.~M. and {Loveday}, J. and {Peacock}, J.~A. and + {Andrae}, E. and {Bland-Hawthorn}, J. and {Brough}, S. and {Brown}, M.~J.~I. and + {Cameron}, E. and {Ching}, J.~H.~Y. and {Colless}, M. and {Conselice}, C.~J. and + {Croom}, S.~M. and {Cross}, N.~J.~G. and {de Propris}, R. and + {Dye}, S. and {Drinkwater}, M.~J. and {Ellis}, S. and {Graham}, A.~W. and + {Grootes}, M.~W. and {Gunawardhana}, M. and {Jones}, D.~H. and + {van Kampen}, E. and {Maraston}, C. and {Nichol}, R.~C. and + {Parkinson}, H.~R. and {Phillipps}, S. and {Pimbblet}, K. and + {Popescu}, C.~C. and {Prescott}, M. and {Roseboom}, I.~G. and + {Sadler}, E.~M. and {Sansom}, A.~E. and {Sharp}, R.~G. and {Smith}, D.~J.~B. and + {Taylor}, E. and {Thomas}, D. and {Tuffs}, R.~J. and {Wijesinghe}, D. and + {Dunne}, L. and {Frenk}, C.~S. and {Jarvis}, M.~J. and {Madore}, B.~F. and + {Meyer}, M.~J. and {Seibert}, M. and {Staveley-Smith}, L. and + {Sutherland}, W.~J. and {Warren}, S.~J.}, + title = "{Galaxy and Mass Assembly (GAMA): survey diagnostics and core data release}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1009.0614}, + keywords = {surveys, galaxies: distances and redshifts, galaxies: fundamental parameters, galaxies: general, galaxies: statistics}, + year = 2011, + month = may, + volume = 413, + pages = {971-995}, + doi = {10.1111/j.1365-2966.2010.18188.x}, + adsurl = {http://adsabs.harvard.edu/abs/2011MNRAS.413..971D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{driver2016a, + author = {{Driver}, S.~P. and {Wright}, A.~H. and {Andrews}, S.~K. and + {Davies}, L.~J. and {Kafle}, P.~R. and {Lange}, R. and {Moffett}, A.~J. and + {Mannering}, E. and {Robotham}, A.~S.~G. and {Vinsen}, K. and + {Alpaslan}, M. and {Andrae}, E. and {Baldry}, I.~K. and {Bauer}, A.~E. and + {Bamford}, S.~P. and {Bland-Hawthorn}, J. and {Bourne}, N. and + {Brough}, S. and {Brown}, M.~J.~I. and {Cluver}, M.~E. and {Croom}, S. and + {Colless}, M. and {Conselice}, C.~J. and {da Cunha}, E. and + {De Propris}, R. and {Drinkwater}, M. and {Dunne}, L. and {Eales}, S. and + {Edge}, A. and {Frenk}, C. and {Graham}, A.~W. and {Grootes}, M. and + {Holwerda}, B.~W. and {Hopkins}, A.~M. and {Ibar}, E. and {van Kampen}, E. and + {Kelvin}, L.~S. and {Jarrett}, T. and {Jones}, D.~H. and {Lara-Lopez}, M.~A. and + {Liske}, J. and {Lopez-Sanchez}, A.~R. and {Loveday}, J. and + {Maddox}, S.~J. and {Madore}, B. and {Mahajan}, S. and {Meyer}, M. and + {Norberg}, P. and {Penny}, S.~J. and {Phillipps}, S. and {Popescu}, C. and + {Tuffs}, R.~J. and {Peacock}, J.~A. and {Pimbblet}, K.~A. and + {Prescott}, M. and {Rowlands}, K. and {Sansom}, A.~E. and {Seibert}, M. and + {Smith}, M.~W.~L. and {Sutherland}, W.~J. and {Taylor}, E.~N. and + {Valiante}, E. and {Vazquez-Mata}, J.~A. and {Wang}, L. and + {Wilkins}, S.~M. and {Williams}, R.}, + title = "{Galaxy And Mass Assembly (GAMA): Panchromatic Data Release (far-UV-far-IR) and the low-z energy budget}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1508.02076}, + keywords = {astronomical data bases: miscellaneous, galaxies: evolution, galaxies: general, galaxies: photometry, cosmology: observations}, + year = 2016, + month = feb, + volume = 455, + pages = {3911-3942}, + doi = {10.1093/mnras/stv2505}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.455.3911D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@article{duffy2012a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2012MNRAS.426.3385D}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1208.5592}, + Author = {{Duffy}, A.~R. and {Meyer}, M.~J. and {Staveley-Smith}, L. and {Bernyk}, M. and {Croton}, D.~J. and {Koribalski}, B.~S. and {Gerstmann}, D. and {Westerlund}, S.}, + Date-Added = {2017-04-25 15:30:27 +0000}, + Date-Modified = {2017-04-25 15:30:27 +0000}, + Doi = {10.1111/j.1365-2966.2012.21987.x}, + Eprint = {1208.5592}, + Journal = {\mnras}, + Keywords = {galaxies: evolution, galaxies: luminosity function, mass function, radio lines: galaxies}, + Month = nov, + Pages = {3385-3402}, + Primaryclass = {astro-ph.CO}, + Title = {{Predictions for ASKAP neutral hydrogen surveys}}, + Volume = 426, + Year = 2012 +} %FFFFFFFFFFF +@article{fernandez2013a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2013arXiv1303.2659F}, + Archiveprefix = {arXiv}, + Author = {{Fern{\'a}ndez}, X. and {van Gorkom}, J.~H. and {Hess}, K.~M. and {Pisano}, D.~J. and {Kreckel}, K. and {Momjian}, E. and {Popping}, A. and {Oosterloo}, T. and {Chomiuk}, L. and {Verheijen}, M.~A.~W. and {Henning}, P.~A. and {Schiminovich}, D. and {Bershady}, M.~A. and {Wilcots}, E.~M. and {Scoville}, N.}, + Date-Added = {2017-04-25 15:27:22 +0000}, + Date-Modified = {2017-04-25 15:27:22 +0000}, + Eprint = {1303.2659}, + Journal = {ArXiv e-prints}, + Keywords = {Astrophysics - Galaxy Astrophysics, Astrophysics - Cosmology and Extragalactic Astrophysics}, + Month = mar, + Primaryclass = {astro-ph.GA}, + Title = {{A Pilot for a VLA HI Deep Field}}, + Year = 2013 +} +@article{fernandez2016a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016ApJ...824L...1F}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1606.00013}, + Author = {{Fern{\'a}ndez}, X. and {Gim}, H.~B. and {van Gorkom}, J.~H. and {Yun}, M.~S. and {Momjian}, E. and {Popping}, A. and {Chomiuk}, L. and {Hess}, K.~M. and {Hunt}, L. and {Kreckel}, K. and {Lucero}, D. and {Maddox}, N. and {Oosterloo}, T. and {Pisano}, D.~J. and {Verheijen}, M.~A.~W. and {Hales}, C.~A. and {Chung}, A. and {Dodson}, R. and {Golap}, K. and {Gross}, J. and {Henning}, P. and {Hibbard}, J. and {Jaff{\'e}}, Y.~L. and {Donovan Meyer}, J. and {Meyer}, M. and {Sanchez-Barrantes}, M. and {Schiminovich}, D. and {Wicenec}, A. and {Wilcots}, E. and {Bershady}, M. and {Scoville}, N. and {Strader}, J. and {Tremou}, E. and {Salinas}, R. and {Ch{\'a}vez}, R.}, + Date-Added = {2017-04-25 15:27:24 +0000}, + Date-Modified = {2017-04-25 15:27:24 +0000}, + Doi = {10.3847/2041-8205/824/1/L1}, + Eid = {L1}, + Eprint = {1606.00013}, + Journal = {\apjl}, + Keywords = {galaxies: evolution, galaxies: starburst, radio lines: galaxies}, + Month = jun, + Pages = {L1}, + Title = {{Highest Redshift Image of Neutral Hydrogen in Emission: A CHILES Detection of a Starbursting Galaxy at z = 0.376}}, + Volume = 824, + Year = 2016 +} @ARTICLE{flaugher2005a, author = {{Flaugher}, B.}, title = "{The Dark Energy Survey}", @@ -90,7 +435,44 @@ @ARTICLE{flaugher2005a adsurl = {http://adsabs.harvard.edu/abs/2005IJMPA..20.3121F}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } -%GGGGGGGGGGG +%GGGGGGGGGGGGGG +@ARTICLE{galaz2015a, + author = {{Galaz}, G. and {Milovic}, C. and {Suc}, V. and {Busta}, L. and + {Lizana}, G. and {Infante}, L. and {Royo}, S.}, + title = "{Deep Optical Images of Malin 1 Reveal New Features}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1512.01095}, + keywords = {galaxies: general, galaxies: spiral, techniques: image processing}, + year = 2015, + month = dec, + volume = 815, + eid = {L29}, + pages = {L29}, + doi = {10.1088/2041-8205/815/2/L29}, + adsurl = {http://cdsads.u-strasbg.fr/abs/2015ApJ...815L..29G}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@article{glazebrook2013a, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1305.2469}, + Author = {{Glazebrook}, K.}, + Date-Added = {2017-04-25 15:25:24 +0000}, + Date-Modified = {2017-04-25 15:25:24 +0000}, + Doi = {10.1017/pasa.2013.34}, + Eid = {e056}, + Eprint = {1305.2469}, + Journal = {\pasa}, + Keywords = {galaxies: evolution, galaxies: formation, galaxies: high-redshift, galaxies: kinematics and dynamics, galaxies: stellar content, galaxies: structure}, + Month = nov, + Pages = {e056}, + Primaryclass = {astro-ph.CO}, + Title = {{The Dawes Review 1: Kinematic Studies of Star-Forming Galaxies Across Cosmic Time}}, + Volume = 30, + Year = 2013 +} + @ARTICLE{grogin2011a, author = {{Grogin}, N.~A. and {Kocevski}, D.~D. and {Faber}, S.~M. and {Ferguson}, H.~C. and {Koekemoer}, A.~M. and {Riess}, A.~G. and @@ -138,7 +520,171 @@ @ARTICLE{grogin2011a adsurl = {http://adsabs.harvard.edu/abs/2011ApJS..197...35G}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +%HHHHHHHHHHH +@ARTICLE{hocking2015a, + author = {{Hocking}, A. and {Geach}, J.~E. and {Davey}, N. and {Sun}, Y. + }, + title = "{Teaching a machine to see: unsupervised image segmentation and categorisation using growing neural gas and hierarchical clustering}", + journal = {arXiv:arXiv150701589}, +archivePrefix = "arXiv", + eprint = {1507.01589}, + primaryClass = "astro-ph.IM", + keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics}, + year = 2015, + month = jul, + adsurl = {http://adsabs.harvard.edu/abs/2015arXiv150701589H}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{hoekstra2015a, + author = {{Hoekstra}, H. and {Herbonnet}, R. and {Muzzin}, A. and {Babul}, A. and + {Mahdavi}, A. and {Viola}, M. and {Cacciato}, M.}, + title = "{The Canadian Cluster Comparison Project: detailed study of systematics and updated weak lensing masses}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1502.01883}, + keywords = {cosmology: observations, dark matter}, + year = 2015, + month = may, + volume = 449, + pages = {685-714}, + doi = {10.1093/mnras/stv275}, + adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.449..685H}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@inproceedings{holwerda2010a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2010iska.meetE..68H}, + Archiveprefix = {arXiv/1007.4101}, + Author = {{Holwerda}, B. and {Blyth}, S.}, + Booktitle = {ISKAF2010 Science Meeting}, + Date-Added = {2017-04-25 15:29:43 +0000}, + Date-Modified = {2017-04-25 15:29:43 +0000}, + Eprint = {1007.4101}, + Primaryclass = {astro-ph.CO}, + Title = {{Trumpeting the Vuvuzela: The deepest HI observations with MeerKAT}}, + Year = 2010 +} +@inproceedings{holwerda2011a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2011AAS...21743317H}, + Author = {{Holwerda}, B.~W. and {Blyth}, S. and {Baker}, A.~J. and {MeerKAT Deep HI Survey Team}}, + Booktitle = {Abstract \#217}, + Date-Added = {2017-04-25 15:30:04 +0000}, + Date-Modified = {2017-04-25 15:30:04 +0000}, + Month = jan, + Pages = {\#433.17}, + Series = {Bulletin of the AAS}, + Title = {{A 5000-hour Meerkat Large Survey Project To Observe Hi To Z=1}}, + Volume = 43, + Year = 2011 +} +%IIIIIIIIIII +@ARTICLE{ivezic2008a, + author = {{Ivezic}, Z. and {Tyson}, J.~A. and {Abel}, B. and {Acosta}, E. and + {Allsman}, R. and {AlSayyad}, Y. and {Anderson}, S.~F. and {Andrew}, J. and + {Angel}, R. and {Angeli}, G. and {Ansari}, R. and {Antilogus}, P. and + {Arndt}, K.~T. and {Astier}, P. and {Aubourg}, E. and {Axelrod}, T. and + {Bard}, D.~J. and {Barr}, J.~D. and {Barrau}, A. and {Bartlett}, J.~G. and + {Bauman}, B.~J. and {Beaumont}, S. and {Becker}, A.~C. and {Becla}, J. and + {Beldica}, C. and {Bellavia}, S. and {Blanc}, G. and {Blandford}, R.~D. and + {Bloom}, J.~S. and {Bogart}, J. and {Borne}, K. and {Bosch}, J.~F. and + {Boutigny}, D. and {Brandt}, W.~N. and {Brown}, M.~E. and {Bullock}, J.~S. and + {Burchat}, P. and {Burke}, D.~L. and {Cagnoli}, G. and {Calabrese}, D. and + {Chandrasekharan}, S. and {Chesley}, S. and {Cheu}, E.~C. and + {Chiang}, J. and {Claver}, C.~F. and {Connolly}, A.~J. and {Cook}, K.~H. and + {Cooray}, A. and {Covey}, K.~R. and {Cribbs}, C. and {Cui}, W. and + {Cutri}, R. and {Daubard}, G. and {Daues}, G. and {Delgado}, F. and + {Digel}, S. and {Doherty}, P. and {Dubois}, R. and {Dubois-Felsmann}, G.~P. and + {Durech}, J. and {Eracleous}, M. and {Ferguson}, H. and {Frank}, J. and + {Freemon}, M. and {Gangler}, E. and {Gawiser}, E. and {Geary}, J.~C. and + {Gee}, P. and {Geha}, M. and {Gibson}, R.~R. and {Gilmore}, D.~K. and + {Glanzman}, T. and {Goodenow}, I. and {Gressler}, W.~J. and + {Gris}, P. and {Guyonnet}, A. and {Hascall}, P.~A. and {Haupt}, J. and + {Hernandez}, F. and {Hogan}, C. and {Huang}, D. and {Huffer}, M.~E. and + {Innes}, W.~R. and {Jacoby}, S.~H. and {Jain}, B. and {Jee}, J. and + {Jernigan}, J.~G. and {Jevremovic}, D. and {Johns}, K. and {Jones}, R.~L. and + {Juramy-Gilles}, C. and {Juric}, M. and {Kahn}, S.~M. and {Kalirai}, J.~S. and + {Kallivayalil}, N. and {Kalmbach}, B. and {Kantor}, J.~P. and + {Kasliwal}, M.~M. and {Kessler}, R. and {Kirkby}, D. and {Knox}, L. and + {Kotov}, I. and {Krabbendam}, V.~L. and {Krughoff}, S. and {Kubanek}, P. and + {Kuczewski}, J. and {Kulkarni}, S. and {Lambert}, R. and {Le Guillou}, L. and + {Levine}, D. and {Liang}, M. and {Lim}, K. and {Lintott}, C. and + {Lupton}, R.~H. and {Mahabal}, A. and {Marshall}, P. and {Marshall}, S. and + {May}, M. and {McKercher}, R. and {Migliore}, M. and {Miller}, M. and + {Mills}, D.~J. and {Monet}, D.~G. and {Moniez}, M. and {Neill}, D.~R. and + {Nief}, J. and {Nomerotski}, A. and {Nordby}, M. and {O'Connor}, P. and + {Oliver}, J. and {Olivier}, S.~S. and {Olsen}, K. and {Ortiz}, S. and + {Owen}, R.~E. and {Pain}, R. and {Peterson}, J.~R. and {Petry}, C.~E. and + {Pierfederici}, F. and {Pietrowicz}, S. and {Pike}, R. and {Pinto}, P.~A. and + {Plante}, R. and {Plate}, S. and {Price}, P.~A. and {Prouza}, M. and + {Radeka}, V. and {Rajagopal}, J. and {Rasmussen}, A. and {Regnault}, N. and + {Ridgway}, S.~T. and {Ritz}, S. and {Rosing}, W. and {Roucelle}, C. and + {Rumore}, M.~R. and {Russo}, S. and {Saha}, A. and {Sassolas}, B. and + {Schalk}, T.~L. and {Schindler}, R.~H. and {Schneider}, D.~P. and + {Schumacher}, G. and {Sebag}, J. and {Sembroski}, G.~H. and + {Seppala}, L.~G. and {Shipsey}, I. and {Silvestri}, N. and {Smith}, J.~A. and + {Smith}, R.~C. and {Strauss}, M.~A. and {Stubbs}, C.~W. and + {Sweeney}, D. and {Szalay}, A. and {Takacs}, P. and {Thaler}, J.~J. and + {Van Berg}, R. and {Vanden Berk}, D. and {Vetter}, K. and {Virieux}, F. and + {Xin}, B. and {Walkowicz}, L. and {Walter}, C.~W. and {Wang}, D.~L. and + {Warner}, M. and {Willman}, B. and {Wittman}, D. and {Wolff}, S.~C. and + {Wood-Vasey}, W.~M. and {Yoachim}, P. and {Zhan}, H. and {for the LSST Collaboration} + }, + title = "{LSST: from Science Drivers to Reference Design and Anticipated Data Products}", + journal = {ArXiv e-prints}, +archivePrefix = "arXiv", + eprint = {0805.2366}, + keywords = {Astrophysics}, + year = 2008, + month = may, + adsurl = {http://adsabs.harvard.edu/abs/2008arXiv0805.2366I}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} %JJJJJJJJJJJ +@article{jarvis2012a, + Adsurl = {http://adsabs.harvard.edu/abs/2012AfrSk..16...44J}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1107.5165}, + Author = {{Jarvis}, M.~J.}, + Date-Added = {2017-04-25 15:27:37 +0000}, + Date-Modified = {2017-04-25 15:27:37 +0000}, + Eprint = {1107.5165}, + Journal = {African Skies}, + Keywords = {Astrophysics - Cosmology and Extragalactic Astrophysics}, + Month = mar, + Pages = {44}, + Primaryclass = {astro-ph.CO}, + Title = {{Multi-wavelength Extragalactic Surveys and the Role of MeerKAT and SALT}}, + Volume = 16, + Year = 2012 +} +@ARTICLE{johnston2007a, + author = {{Johnston}, S. and {Bailes}, M. and {Bartel}, N. and {Baugh}, C. and + {Bietenholz}, M. and {Blake}, C. and {Braun}, R. and {Brown}, J. and + {Chatterjee}, S. and {Darling}, J. and {Deller}, A. and {Dodson}, R. and + {Edwards}, P.~G. and {Ekers}, R. and {Ellingsen}, S. and {Feain}, I. and + {Gaensler}, B.~M. and {Haverkorn}, M. and {Hobbs}, G. and {Hopkins}, A. and + {Jackson}, C. and {James}, C. and {Joncas}, G. and {Kaspi}, V. and + {Kilborn}, V. and {Koribalski}, B. and {Kothes}, R. and {Landecker}, T.~L. and + {Lenc}, E. and {Lovell}, J. and {Macquart}, J.-P. and {Manchester}, R. and + {Matthews}, D. and {McClure-Griffiths}, N.~M. and {Norris}, R. and + {Pen}, U.-L. and {Phillips}, C. and {Power}, C. and {Protheroe}, R. and + {Sadler}, E. and {Schmidt}, B. and {Stairs}, I. and {Staveley-Smith}, L. and + {Stil}, J. and {Taylor}, R. and {Tingay}, S. and {Tzioumis}, A. and + {Walker}, M. and {Wall}, J. and {Wolleben}, M.}, + title = "{Science with the Australian Square Kilometre Array Pathfinder}", + journal = {\pasa}, +archivePrefix = "arXiv", + eprint = {0711.2103}, + keywords = {telescopes}, + year = 2007, + month = dec, + volume = 24, + pages = {174-188}, + doi = {10.1071/AS07033}, + adsurl = {http://adsabs.harvard.edu/abs/2007PASA...24..174J}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{johnston2008a, author = {{Johnston}, K.~V. and {Bullock}, J.~S. and {Sharma}, S. and {Font}, A. and {Robertson}, B.~E. and {Leitner}, S.~N.}, @@ -190,6 +736,101 @@ @ARTICLE{kartaltepe2007a adsurl = {http://adsabs.harvard.edu/abs/2007ApJS..172..320K}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{kaviraj2005a, + author = {{Kaviraj}, S. and {Devriendt}, J.~E.~G. and {Ferreras}, I. and + {Yi}, S.~K.}, + title = "{The elliptical galaxy colour-magnitude relation as a discriminant between the monolithic and merger paradigms}", + journal = {\mnras}, + eprint = {astro-ph/0401126}, + keywords = {galaxies: elliptical and lenticular, cD, galaxies: evolution, galaxies: formation, galaxies: fundamental parameters}, + year = 2005, + month = jun, + volume = 360, + pages = {60-68}, + doi = {10.1111/j.1365-2966.2005.08883.x}, + adsurl = {http://adsabs.harvard.edu/abs/2005MNRAS.360...60K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2009a, + author = {{Kaviraj}, S. and {Peirani}, S. and {Khochfar}, S. and {Silk}, J. and + {Kay}, S.}, + title = "{The role of minor mergers in the recent star formation history of early-type galaxies}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {0711.1493}, + keywords = {methods: N-body simulations , galaxies: elliptical and lenticular, cD , galaxies: evolution , galaxies: formation}, + year = 2009, + month = apr, + volume = 394, + pages = {1713-1720}, + doi = {10.1111/j.1365-2966.2009.14403.x}, + adsurl = {http://adsabs.harvard.edu/abs/2009MNRAS.394.1713K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2014a, + author = {{Kaviraj}, S.}, + title = "{The significant contribution of minor mergers to the cosmic star formation budget}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1310.0007}, + keywords = {galaxies: elliptical and lenticular, cD, galaxies: evolution, galaxies: formation, galaxies: interactions, galaxies: starburst}, + year = 2014, + month = jan, + volume = 437, + pages = {L41-L45}, + doi = {10.1093/mnrasl/slt136}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.437L..41K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2014b, + author = {{Kaviraj}, S.}, + title = "{The importance of minor-merger-driven star formation and black hole growth in disc galaxies}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1402.1166}, + keywords = {galaxies: evolution, galaxies: formation, galaxies: interactions, galaxies: spiral}, + year = 2014, + month = jun, + volume = 440, + pages = {2944-2952}, + doi = {10.1093/mnras/stu338}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.440.2944K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2015a, + author = {{Kaviraj}, S. and {Devriendt}, J. and {Dubois}, Y. and {Slyz}, A. and + {Welker}, C. and {Pichon}, C. and {Peirani}, S. and {Le Borgne}, D. + }, + title = "{Galaxy merger histories and the role of merging in driving star formation at z $\gt$ 1}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1411.2595}, + keywords = {galaxies: evolution, galaxies: formation, galaxies: high-redshift, galaxies: interactions}, + year = 2015, + month = sep, + volume = 452, + pages = {2845-2850}, + doi = {10.1093/mnras/stv1500}, + adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.452.2845K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2017a, + author = {{Kaviraj}, S. and {Laigle}, C. and {Kimm}, T. and {Devriendt}, J.~E.~G. and + {Dubois}, Y. and {Pichon}, C. and {Slyz}, A. and {Chisari}, E. and + {Peirani}, S.}, + title = "{The Horizon-AGN simulation: evolution of galaxy properties over cosmic time}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1605.09379}, + keywords = {methods: numerical, galaxies: evolution, galaxies: formation, galaxies: high-redshift, cosmology: theory, large-scale structure of Universe}, + year = 2017, + month = jun, + volume = 467, + pages = {4739-4752}, + doi = {10.1093/mnras/stx126}, + adsurl = {http://adsabs.harvard.edu/abs/2017MNRAS.467.4739K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{koekemoer2011a, author = {{Koekemoer}, A.~M. and {Faber}, S.~M. and {Ferguson}, H.~C. and {Grogin}, N.~A. and {Kocevski}, D.~D. and {Koo}, D.~C. and {Lai}, K. and @@ -263,6 +904,28 @@ @ARTICLE{heckman2005a adsnote = {Provided by the SAO/NASA Astrophysics Data System} } %LLLLLLLLLLL +@ARTICLE{leauthaud2012a, + author = {{Leauthaud}, A. and {Tinker}, J. and {Bundy}, K. and {Behroozi}, P.~S. and + {Massey}, R. and {Rhodes}, J. and {George}, M.~R. and {Kneib}, J.-P. and + {Benson}, A. and {Wechsler}, R.~H. and {Busha}, M.~T. and {Capak}, P. and + {Cort{\^e}s}, M. and {Ilbert}, O. and {Koekemoer}, A.~M. and + {Le F{\`e}vre}, O. and {Lilly}, S. and {McCracken}, H.~J. and + {Salvato}, M. and {Schrabback}, T. and {Scoville}, N. and {Smith}, T. and + {Taylor}, J.~E.}, + title = "{New Constraints on the Evolution of the Stellar-to-dark Matter Connection: A Combined Analysis of Galaxy-Galaxy Lensing, Clustering, and Stellar Mass Functions from z = 0.2 to z =1}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1104.0928}, + keywords = {dark matter, galaxies: evolution, galaxies: formation, galaxies: luminosity function, mass function, galaxies: stellar content, gravitational lensing: weak}, + year = 2012, + month = jan, + volume = 744, + eid = {159}, + pages = {159}, + doi = {10.1088/0004-637X/744/2/159}, + adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...744..159L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{lin2008a, author = {{Lin}, L. and {Patton}, D.~R. and {Koo}, D.~C. and {Casteels}, K. and {Conselice}, C.~J. and {Faber}, S.~M. and {Lotz}, J. and {Willmer}, C.~N.~A. and @@ -281,6 +944,57 @@ @ARTICLE{lin2008a adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...681..232L}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{liske2015a, + author = {{Liske}, J. and {Baldry}, I.~K. and {Driver}, S.~P. and {Tuffs}, R.~J. and + {Alpaslan}, M. and {Andrae}, E. and {Brough}, S. and {Cluver}, M.~E. and + {Grootes}, M.~W. and {Gunawardhana}, M.~L.~P. and {Kelvin}, L.~S. and + {Loveday}, J. and {Robotham}, A.~S.~G. and {Taylor}, E.~N. and + {Bamford}, S.~P. and {Bland-Hawthorn}, J. and {Brown}, M.~J.~I. and + {Drinkwater}, M.~J. and {Hopkins}, A.~M. and {Meyer}, M.~J. and + {Norberg}, P. and {Peacock}, J.~A. and {Agius}, N.~K. and {Andrews}, S.~K. and + {Bauer}, A.~E. and {Ching}, J.~H.~Y. and {Colless}, M. and {Conselice}, C.~J. and + {Croom}, S.~M. and {Davies}, L.~J.~M. and {De Propris}, R. and + {Dunne}, L. and {Eardley}, E.~M. and {Ellis}, S. and {Foster}, C. and + {Frenk}, C.~S. and {H{\"a}u{\ss}ler}, B. and {Holwerda}, B.~W. and + {Howlett}, C. and {Ibarra}, H. and {Jarvis}, M.~J. and {Jones}, D.~H. and + {Kafle}, P.~R. and {Lacey}, C.~G. and {Lange}, R. and {Lara-L{\'o}pez}, M.~A. and + {L{\'o}pez-S{\'a}nchez}, {\'A}.~R. and {Maddox}, S. and {Madore}, B.~F. and + {McNaught-Roberts}, T. and {Moffett}, A.~J. and {Nichol}, R.~C. and + {Owers}, M.~S. and {Palamara}, D. and {Penny}, S.~J. and {Phillipps}, S. and + {Pimbblet}, K.~A. and {Popescu}, C.~C. and {Prescott}, M. and + {Proctor}, R. and {Sadler}, E.~M. and {Sansom}, A.~E. and {Seibert}, M. and + {Sharp}, R. and {Sutherland}, W. and {V{\'a}zquez-Mata}, J.~A. and + {van Kampen}, E. and {Wilkins}, S.~M. and {Williams}, R. and + {Wright}, A.~H.}, + title = "{Galaxy And Mass Assembly (GAMA): end of survey report and data release 2}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1506.08222}, + keywords = {surveys, galaxies: distances and redshifts, galaxies: fundamental parameters, galaxies: general, galaxies: photometry, galaxies: statistics}, + year = 2015, + month = sep, + volume = 452, + pages = {2087-2126}, + doi = {10.1093/mnras/stv1436}, + adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.452.2087L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{lofthouse2017a, + author = {{Lofthouse}, E.~K. and {Kaviraj}, S. and {Conselice}, C.~J. and + {Mortlock}, A. and {Hartley}, W.}, + title = "{Major mergers are not significant drivers of star formation or morphological transformation around the epoch of peak cosmic star formation}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1608.03892}, + keywords = {galaxies: elliptical and lenticular, CD, galaxies: evolution, galaxies: formation, galaxies: high-redshift, galaxies: interactions}, + year = 2017, + month = mar, + volume = 465, + pages = {2895-2900}, + doi = {10.1093/mnras/stw2895}, + adsurl = {http://adsabs.harvard.edu/abs/2017MNRAS.465.2895L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{lotz2004a, author = {{Lotz}, J.~M. and {Primack}, J. and {Madau}, P.}, title = "{A New Nonparametric Approach to Galaxy Morphological Classification}", @@ -330,6 +1044,24 @@ @ARTICLE{madau2014a adsurl = {http://adsabs.harvard.edu/abs/2014ARA%26A..52..415M}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@article{maddox2016a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.460.3419M}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1605.04962}, + Author = {{Maddox}, N. and {Jarvis}, M.~J. and {Oosterloo}, T.~A.}, + Date-Added = {2017-04-25 15:31:20 +0000}, + Date-Modified = {2017-04-25 15:31:20 +0000}, + Doi = {10.1093/mnras/stw1164}, + Eprint = {1605.04962}, + Journal = {\mnras}, + Keywords = {surveys, galaxies: evolution, galaxies: general, radio continuum: galaxies, radio lines: galaxies}, + Month = aug, + Pages = {3419-3431}, + Title = {{Optimizing commensality of radio continuum and spectral line observations in the era of the SKA}}, + Volume = 460, + Year = 2016 +} @ARTICLE{martinez-delgado2008a, author = {{Mart{\'{\i}}nez-Delgado}, D. and {Pe{\~n}arrubia}, J. and {Gabany}, R.~J. and {Trujillo}, I. and {Majewski}, S.~R. and {Pohlen}, M.}, @@ -346,6 +1078,91 @@ @ARTICLE{martinez-delgado2008a adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...689..184M}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{mauduit2012a, + author = {{Mauduit}, J.-C. and {Lacy}, M. and {Farrah}, D. and {Surace}, J.~A. and + {Jarvis}, M. and {Oliver}, S. and {Maraston}, C. and {Vaccari}, M. and + {Marchetti}, L. and {Zeimann}, G. and {Gonz{\'a}les-Solares}, E.~A. and + {Pforr}, J. and {Petric}, A.~O. and {Henriques}, B. and {Thomas}, P.~A. and + {Afonso}, J. and {Rettura}, A. and {Wilson}, G. and {Falder}, J.~T. and + {Geach}, J.~E. and {Huynh}, M. and {Norris}, R.~P. and {Seymour}, N. and + {Richards}, G.~T. and {Stanford}, S.~A. and {Alexander}, D.~M. and + {Becker}, R.~H. and {Best}, P.~N. and {Bizzocchi}, L. and {Bonfield}, D. and + {Castro}, N. and {Cava}, A. and {Chapman}, S. and {Christopher}, N. and + {Clements}, D.~L. and {Covone}, G. and {Dubois}, N. and {Dunlop}, J.~S. and + {Dyke}, E. and {Edge}, A. and {Ferguson}, H.~C. and {Foucaud}, S. and + {Franceschini}, A. and {Gal}, R.~R. and {Grant}, J.~K. and {Grossi}, M. and + {Hatziminaoglou}, E. and {Hickey}, S. and {Hodge}, J.~A. and + {Huang}, J.-S. and {Ivison}, R.~J. and {Kim}, M. and {LeFevre}, O. and + {Lehnert}, M. and {Lonsdale}, C.~J. and {Lubin}, L.~M. and {McLure}, R.~J. and + {Messias}, H. and {Mart{\'{\i}}nez-Sansigre}, A. and {Mortier}, A.~M.~J. and + {Nielsen}, D.~M. and {Ouchi}, M. and {Parish}, G. and {Perez-Fournon}, I. and + {Pierre}, M. and {Rawlings}, S. and {Readhead}, A. and {Ridgway}, S.~E. and + {Rigopoulou}, D. and {Romer}, A.~K. and {Rosebloom}, I.~G. and + {Rottgering}, H.~J.~A. and {Rowan-Robinson}, M. and {Sajina}, A. and + {Simpson}, C.~J. and {Smail}, I. and {Squires}, G.~K. and {Stevens}, J.~A. and + {Taylor}, R. and {Trichas}, M. and {Urrutia}, T. and {van Kampen}, E. and + {Verma}, A. and {Xu}, C.~K.}, + title = "{The Spitzer Extragalactic Representative Volume Survey (SERVS): Survey Definition and Goals}", + journal = {\pasp}, +archivePrefix = "arXiv", + eprint = {1206.4060}, + year = 2012, + month = jul, + volume = 124, + pages = {714}, + doi = {10.1086/666945}, + adsurl = {http://adsabs.harvard.edu/abs/2012PASP..124..714M}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{mcgaugh2000a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2000ApJ...533L..99M}, + Author = {{McGaugh}, S.~S. and {Schombert}, J.~M. and {Bothun}, G.~D. and {de Blok}, W.~J.~G.}, + Date-Added = {2017-04-25 15:26:41 +0000}, + Date-Modified = {2017-04-25 15:26:41 +0000}, + Doi = {10.1086/312628}, + Eprint = {arXiv:astro-ph/0003001}, + Journal = {\apjl}, + Keywords = {COSMOLOGY: DARK MATTER, GALAXIES: DWARF, GALAXIES: FORMATION, GALAXIES: FUNDAMENTAL PARAMETERS, GALAXIES: KINEMATICS AND DYNAMICS, GALAXIES: SPIRAL}, + Month = apr, + Pages = {L99-L102}, + Title = {{The Baryonic Tully-Fisher Relation}}, + Volume = 533, + Year = 2000 +} +@article{meyer2015a, + Adscomment = {to be published in: 'Advancing Astrophysics with the Square Kilometre Array', Proceedings of Science, PoS(AASKA14)131}, + Adsurl = {http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1501.01082}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1501.01082v1}, + Author = {{Meyer}, Martin and {Robotham}, Aaron and {Obreschkow}, Danail and {Driver}, Simon and {Staveley-Smith}, Lister and {Zwaan}, Martin}, + Date-Added = {2017-04-25 15:30:42 +0000}, + Date-Modified = {2017-04-25 15:30:42 +0000}, + Eprint = {1501.01082v1}, + Jornal = {ArXiv e-prints}, + Month = {Jan}, + Primaryclass = {astro-ph.GA}, + Title = {Connecting the Baryons: Multiwavelength Data for SKA HI Surveys}, + Year = {2015} +} +@article{meyer2016a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.455.3136M}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1510.07785}, + Author = {{Meyer}, S.~A. and {Meyer}, M. and {Obreschkow}, D. and {Staveley-Smith}, L.}, + Date-Added = {2017-04-25 15:25:50 +0000}, + Date-Modified = {2017-04-25 15:25:50 +0000}, + Doi = {10.1093/mnras/stv2458}, + Eprint = {1510.07785}, + Journal = {\mnras}, + Keywords = {galaxies: evolution, galaxies: fundamental parameters, galaxies: kinematics and dynamics, galaxies: spiral, dark matter, radio lines: galaxies}, + Month = jan, + Pages = {3136-3147}, + Title = {{Extended Tully-Fisher relations using H I stacking}}, + Volume = 455, + Year = 2016 +} @INPROCEEDINGS{miyazaki2012a, author = {{Miyazaki}, S. and {Komiyama}, Y. and {Nakaya}, H. and {Kamata}, Y. and {Doi}, Y. and {Hamana}, T. and {Karoji}, H. and {Furusawa}, H. and @@ -375,6 +1192,54 @@ @INPROCEEDINGS{miyazaki2012a adsnote = {Provided by the SAO/NASA Astrophysics Data System} } %NNNNNNNNNNN +@ARTICLE{newman2008a, + author = {{Newman}, J.~A.}, + title = "{Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross-Correlations}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {0805.1409}, + keywords = {galaxies: distances and redshifts, large-scale structure of universe, methods: miscellaneous, surveys}, + year = 2008, + month = sep, + volume = 684, + eid = {88-101}, + pages = {88-101}, + doi = {10.1086/589982}, + adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...684...88N}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{newman2015a, + author = {{Newman}, J.~A. and {Abate}, A. and {Abdalla}, F.~B. and {Allam}, S. and + {Allen}, S.~W. and {Ansari}, R. and {Bailey}, S. and {Barkhouse}, W.~A. and + {Beers}, T.~C. and {Blanton}, M.~R. and {Brodwin}, M. and {Brownstein}, J.~R. and + {Brunner}, R.~J. and {Carrasco Kind}, M. and {Cervantes-Cota}, J.~L. and + {Cheu}, E. and {Chisari}, N.~E. and {Colless}, M. and {Comparat}, J. and + {Coupon}, J. and {Cunha}, C.~E. and {de la Macorra}, A. and + {Dell'Antonio}, I.~P. and {Frye}, B.~L. and {Gawiser}, E.~J. and + {Gehrels}, N. and {Grady}, K. and {Hagen}, A. and {Hall}, P.~B. and + {Hearin}, A.~P. and {Hildebrandt}, H. and {Hirata}, C.~M. and + {Ho}, S. and {Honscheid}, K. and {Huterer}, D. and {Ivezi{\'c}}, {\v Z}. and + {Kneib}, J.-P. and {Kruk}, J.~W. and {Lahav}, O. and {Mandelbaum}, R. and + {Marshall}, J.~L. and {Matthews}, D.~J. and {M{\'e}nard}, B. and + {Miquel}, R. and {Moniez}, M. and {Moos}, H.~W. and {Moustakas}, J. and + {Myers}, A.~D. and {Papovich}, C. and {Peacock}, J.~A. and {Park}, C. and + {Rahman}, M. and {Rhodes}, J. and {Ricol}, J.-S. and {Sadeh}, I. and + {Slozar}, A. and {Schmidt}, S.~J. and {Stern}, D.~K. and {Anthony Tyson}, J. and + {von der Linden}, A. and {Wechsler}, R.~H. and {Wood-Vasey}, W.~M. and + {Zentner}, A.~R.}, + title = "{Spectroscopic needs for imaging dark energy experiments}", + journal = {Astroparticle Physics}, +archivePrefix = "arXiv", + eprint = {1309.5384}, + keywords = {Cosmology, Dark energy, Surveys}, + year = 2015, + month = mar, + volume = 63, + pages = {81-100}, + doi = {10.1016/j.astropartphys.2014.06.007}, + adsurl = {http://adsabs.harvard.edu/abs/2015APh....63...81N}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{noeske2007a, author = {{Noeske}, K.~G. and {Weiner}, B.~J. and {Faber}, S.~M. and {Papovich}, C. and {Koo}, D.~C. and {Somerville}, R.~S. and {Bundy}, K. and {Conselice}, C.~J. and @@ -396,7 +1261,105 @@ @ARTICLE{noeske2007a adsurl = {http://adsabs.harvard.edu/abs/2007ApJ...660L..43N}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +%OOOOOOOOOOO +@article{oh2015a, + Adscomment = {100 pages, 85 figures, Accepted for publication on AJ}, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2015arXiv150201281O}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arXiv.org/abs/1502.01281}, + Author = {{Oh}, S.-H. and {Hunter}, D.~A. and {Brinks}, E. and {Elmegreen}, B.~G. and {Schruba}, A. and {Walter}, F. and {Rupen}, M.~P. and {Young}, L.~M. and {Simpson}, C.~E. and {Johnson}, M. and {Herrmann}, K.~A. and {Ficut-Vicas}, D. and {Cigan}, P. and {Heesen}, V. and {Ashley}, T. and {Zhang}, H.-X.}, + Date-Added = {2017-04-25 15:26:51 +0000}, + Date-Modified = {2017-04-25 15:26:51 +0000}, + Eprint = {1502.01281}, + Journal = {ArXiv e-prints}, + Keywords = {Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics}, + Month = feb, + Title = {{High-resolution mass models of dwarf galaxies from LITTLE THINGS}}, + Year = 2015 +} +@ARTICLE{okabe2013a, + author = {{Okabe}, N. and {Smith}, G.~P. and {Umetsu}, K. and {Takada}, M. and + {Futamase}, T.}, + title = "{LoCuSS: The Mass Density Profile of Massive Galaxy Clusters at z = 0.2}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1302.2728}, + keywords = {cosmology: observations, galaxies: clusters: general, gravitational lensing: weak }, + year = 2013, + month = jun, + volume = 769, + eid = {L35}, + pages = {L35}, + doi = {10.1088/2041-8205/769/2/L35}, + adsurl = {http://adsabs.harvard.edu/abs/2013ApJ...769L..35O}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{okabe2016a, + author = {{Okabe}, N. and {Smith}, G.~P.}, + title = "{LoCuSS: weak-lensing mass calibration of galaxy clusters}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1507.04493}, + keywords = {gravitational lensing: weak}, + year = 2016, + month = oct, + volume = 461, + pages = {3794-3821}, + doi = {10.1093/mnras/stw1539}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.461.3794O}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +%PPPPPPPPPPP +@ARTICLE{pasquali2010a, + author = {{Pasquali}, A. and {Gallazzi}, A. and {Fontanot}, F. and {van den Bosch}, F.~C. and + {De Lucia}, G. and {Mo}, H.~J. and {Yang}, X.}, + title = "{Ages and metallicities of central and satellite galaxies: implications for galaxy formation and evolution}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {0912.1853}, + keywords = {galaxies: clusters: general, galaxies: evolution, galaxies: general, galaxies: statistics, galaxies: stellar content, dark matter}, + year = 2010, + month = sep, + volume = 407, + pages = {937-954}, + doi = {10.1111/j.1365-2966.2010.17074.x}, + adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.407..937P}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{ponomareva2016a, + Adscomment = {50 pages, 9 figures, 32 atlas figures. Accepted for publication in MNRAS}, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016arXiv160900378P}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1609.00378}, + Author = {{Ponomareva}, A.~A. and {Verheijen}, M.~A.~W. and {Bosma}, A.}, + Date-Added = {2017-04-25 15:24:09 +0000}, + Date-Modified = {2017-04-25 15:24:09 +0000}, + Eprint = {1609.00378}, + Journal = {ArXiv e-prints}, + Keywords = {Astrophysics - Astrophysics of Galaxies}, + Month = sep, + Title = {{Detailed HI kinematics of Tully-Fisher calibrator galaxies}}, + Year = 2016, +} %RRRRRRRRRRR +@ARTICLE{robertson2007a, + author = {{Robertson}, B. and {Li}, Y. and {Cox}, T.~J. and {Hernquist}, L. and + {Hopkins}, P.~F.}, + title = "{Photometric Properties of the Most Massive High-Redshift Galaxies}", + journal = {\apj}, + eprint = {astro-ph/0703456}, + keywords = {Galaxies: Evolution, Galaxies: Formation}, + year = 2007, + month = sep, + volume = 667, + pages = {60-78}, + doi = {10.1086/520057}, + adsurl = {http://adsabs.harvard.edu/abs/2007ApJ...667...60R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{robotham2014a, author = {{Robotham}, A.~S.~G. and {Driver}, S.~P. and {Davies}, L.~J.~M. and {Hopkins}, A.~M. and {Baldry}, I.~K. and {Agius}, N.~K. and @@ -421,6 +1384,142 @@ @ARTICLE{robotham2014a adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.444.3986R}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{rykoff2014a, + author = {{Rykoff}, E.~S. and {Rozo}, E. and {Busha}, M.~T. and {Cunha}, C.~E. and + {Finoguenov}, A. and {Evrard}, A. and {Hao}, J. and {Koester}, B.~P. and + {Leauthaud}, A. and {Nord}, B. and {Pierre}, M. and {Reddick}, R. and + {Sadibekova}, T. and {Sheldon}, E.~S. and {Wechsler}, R.~H.}, + title = "{redMaPPer. I. Algorithm and SDSS DR8 Catalog}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1303.3562}, + keywords = {galaxies: clusters: general}, + year = 2014, + month = apr, + volume = 785, + eid = {104}, + pages = {104}, + doi = {10.1088/0004-637X/785/2/104}, + adsurl = {http://adsabs.harvard.edu/abs/2014ApJ...785..104R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%SSSSSSSSSSS +@ARTICLE{salim2016a, + author = {{Salim}, S. and {Lee}, J.~C. and {Janowiecki}, S. and {da Cunha}, E. and + {Dickinson}, M. and {Boquien}, M. and {Burgarella}, D. and {Salzer}, J.~J. and + {Charlot}, S.}, + title = "{GALEX-SDSS-WISE Legacy Catalog (GSWLC): Star Formation Rates, Stellar Masses, and Dust Attenuations of 700,000 Low-redshift Galaxies}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {1610.00712}, + keywords = {galaxies: fundamental parameters, galaxies: star formation}, + year = 2016, + month = nov, + volume = 227, + eid = {2}, + pages = {2}, + doi = {10.3847/0067-0049/227/1/2}, + adsurl = {http://adsabs.harvard.edu/abs/2016ApJS..227....2S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + + +@BOOK{sersic1968a, + author = {{Sersic}, J.~L.}, + title = "{Atlas de galaxias australes}", + keywords = {GALAXIES, GROUPS OF GALAXIES, ATLASES}, +booktitle = {Cordoba, Argentina: Observatorio Astronomico, 1968}, + year = 1968, + adsurl = {http://adsabs.harvard.edu/abs/1968adga.book.....S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{stott2012a, + author = {{Stott}, J.~P. and {Hickox}, R.~C. and {Edge}, A.~C. and {Collins}, C.~A. and + {Hilton}, M. and {Harrison}, C.~D. and {Romer}, A.~K. and {Rooney}, P.~J. and + {Kay}, S.~T. and {Miller}, C.~J. and {Sahl{\'e}n}, M. and {Lloyd-Davies}, E.~J. and + {Mehrtens}, N. and {Hoyle}, B. and {Liddle}, A.~R. and {Viana}, P.~T.~P. and + {McCarthy}, I.~G. and {Schaye}, J. and {Booth}, C.~M.}, + title = "{The XMM Cluster Survey: the interplay between the brightest cluster galaxy and the intracluster medium via AGN feedback}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1202.3787}, + primaryClass = "astro-ph.CO", + keywords = {galaxies: active, galaxies: clusters: intracluster medium, galaxies: elliptical and lenticular, cD}, + year = 2012, + month = may, + volume = 422, + pages = {2213-2229}, + doi = {10.1111/j.1365-2966.2012.20764.x}, + adsurl = {http://adsabs.harvard.edu/abs/2012MNRAS.422.2213S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%TTTTTTTTTTTTTTTTT +@article{tiley2016a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.tmp..713T}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1604.06103}, + Author = {{Tiley}, A.~L. and {Stott}, J.~P. and {Swinbank}, A.~M. and {Bureau}, M. and {Harrison}, C.~M. and {Bower}, R. and {Johnson}, H.~L. and {Bunker}, A.~J. and {Jarvis}, M.~J. and {Magdis}, G. and {Sharples}, R. and {Smail}, I. and {Sobral}, D. and {Best}, P.}, + Date-Added = {2017-04-25 15:25:09 +0000}, + Date-Modified = {2017-04-25 15:25:09 +0000}, + Doi = {10.1093/mnras/stw936}, + Eprint = {1604.06103}, + Journal = {\mnras}, + Keywords = {galaxies: evolution, galaxies: general, galaxies: kinematics and dynamics}, + Month = apr, + Title = {{The KMOS Redshift One Spectroscopic Survey (KROSS): The Tully-Fisher Relation at z {\tilde} 1}}, + Year = 2016 +} +@article{tiley2016b, + Adscomment = {Accepted for publication in MNRAS. 27 pages, 10 figures; doi:10.1093/mnras/stw1545}, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016arXiv160701393T}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1607.01393}, + Author = {{Tiley}, A.~L. and {Bureau}, M. and {Saintonge}, A. and {Topal}, S. and {Davis}, T.~A. and {Torii}, K.}, + Date-Added = {2017-04-25 15:26:22 +0000}, + Date-Modified = {2017-04-25 15:26:22 +0000}, + Doi = {10.1086/338962}, + Eprint = {1607.01393}, + Journal = {ArXiv e-prints}, + Keywords = {Astrophysics - Astrophysics of Galaxies}, + Month = jul, + Pages = {L69-L72}, + Title = {{The Tully-Fisher Relation of COLD GASS Galaxies}}, + Volume = {564}, + Year = 2016 +} +@article{trachternach2008a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2008AJ....136.2720T}, + Archiveprefix = {arXiv}, + Author = {{Trachternach}, C. and {de Blok}, W.~J.~G. and {Walter}, F. and {Brinks}, E. and {Kennicutt}, R.~C.}, + Date-Added = {2017-04-25 15:26:32 +0000}, + Date-Modified = {2017-04-25 15:26:32 +0000}, + Doi = {10.1088/0004-6256/136/6/2720}, + Eprint = {0810.2116}, + Journal = {\aj}, + Keywords = {dark matter, galaxies: dwarf, galaxies: fundamental parameters, galaxies: ISM, galaxies: kinematics and dynamics, galaxies: spiral}, + Month = dec, + Pages = {2720-2760}, + Title = {{Dynamical Centers and Noncircular Motions in Things Galaxies: Implications for Dark Matter Halos}}, + Volume = 136, + Year = 2008 +} +@article{tully1977a, + Adsnote = {Provided by the Smithsonian/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/1977A%26A....54..661T}, + Author = {{Tully}, R.~B. and {Fisher}, J.~R.}, + Date-Added = {2017-04-25 15:24:36 +0000}, + Date-Modified = {2017-04-25 15:24:36 +0000}, + Journal = {\aap}, + Month = feb, + Pages = {661-673}, + Title = {{A new method of determining distances to galaxies}}, + Volume = 54, + Year = 1977 +} %VVVVVVVVVVV @ARTICLE{van_dokkum2014a, author = {{van Dokkum}, P.~G. and {Abraham}, R. and {Merritt}, A.}, @@ -438,6 +1537,91 @@ @ARTICLE{van_dokkum2014a adsurl = {http://adsabs.harvard.edu/abs/2014ApJ...782L..24V}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } + +@article{verheijen2001a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2001ApJ...563..694V}, + Author = {{Verheijen}, M.~A.~W.}, + Date-Added = {2017-04-25 15:24:48 +0000}, + Date-Modified = {2017-04-25 15:24:48 +0000}, + Doi = {10.1086/323887}, + Eprint = {arXiv:astro-ph/0108225}, + Journal = {\apj}, + Keywords = {Cosmology: Dark Matter, Galaxies: Clusters: Individual: Name: Ursa Major, Galaxies: Fundamental Parameters, Galaxies: Kinematics and Dynamics, Galaxies: Spiral, Galaxies: Structure}, + Month = dec, + Pages = {694-715}, + Title = {{The Ursa Major Cluster of Galaxies. V. H I Rotation Curve Shapes and the Tully-Fisher Relations}}, + Volume = 563, + Year = 2001 +} +@article{verheijen2010a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2010arXiv1009.0279V}, + Archiveprefix = {arXiv}, + Author = {{Verheijen}, M. and {Deshev}, B. and {van Gorkom}, J. and {Poggianti}, B. and {Chung}, A. and {Cybulski}, R. and {Dwarakanath}, K.~S. and {Montero-Castano}, M. and {Morrison}, G. and {Schiminovich}, D. and {Szomoru}, A. and {Yun}, M.}, + Date-Added = {2017-04-25 15:27:10 +0000}, + Date-Modified = {2017-04-25 15:27:10 +0000}, + Eprint = {1009.0279}, + Journal = {ArXiv e-prints}, + Keywords = {Astrophysics - Cosmology and Extragalactic Astrophysics}, + Month = sep, + Primaryclass = {astro-ph.CO}, + Title = {{Westerbork Ultra-Deep Survey of HI at z=0.2}}, + Year = 2010 +} +%WWWWWWWWWWW +@ARTICLE{wang2016a, + author = {{Wang}, H. and {Mo}, H.~J. and {Yang}, X. and {Zhang}, Y. and + {Shi}, J. and {Jing}, Y.~P. and {Liu}, C. and {Li}, S. and {Kang}, X. and + {Gao}, Y.}, + title = "{ELUCID - Exploring the Local Universe with ReConstructed Initial Density Field III: Constrained Simulation in the SDSS Volume}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1608.01763}, + keywords = {dark matter, galaxies: halos, large-scale structure of universe, methods: statistical }, + year = 2016, + month = nov, + volume = 831, + eid = {164}, + pages = {164}, + doi = {10.3847/0004-637X/831/2/164}, + adsurl = {http://adsabs.harvard.edu/abs/2016ApJ...831..164W}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{weiner2006a, + Adsnote = {Provided by the Smithsonian/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2006ApJ...653.1049W&db_key=AST}, + Author = {{Weiner}, B.~J. and {Willmer}, C.~N.~A. and {Faber}, S.~M. and {Harker}, J. and {Kassin}, S.~A. and {Phillips}, A.~C. and {Melbourne}, J. and {Metevier}, A.~J. and {Vogt}, N.~P. and {Koo}, D.~C.}, + Date-Added = {2017-04-25 15:24:59 +0000}, + Date-Modified = {2017-04-25 15:24:59 +0000}, + Doi = {10.1086/508922}, + Eprint = {astro-ph/0609091}, + Journal = {\apj}, + Month = dec, + Pages = {1049-1069}, + Title = {{A Survey of Galaxy Kinematics to z\~{}1 in the TKRS/GOODS-N Field. II. Evolution in the Tully-Fisher Relation}}, + Volume = 653, + Year = 2006 +} +@ARTICLE{willott2013a, + author = {{Willott}, C.~J. and {McLure}, R.~J. and {Hibon}, P. and {Bielby}, R. and + {McCracken}, H.~J. and {Kneib}, J.-P. and {Ilbert}, O. and {Bonfield}, D.~G. and + {Bruce}, V.~A. and {Jarvis}, M.~J.}, + title = "{An Exponential Decline at the Bright End of the z = 6 Galaxy Luminosity Function}", + journal = {\aj}, +archivePrefix = "arXiv", + eprint = {1202.5330}, + keywords = {cosmology: observations, galaxies: evolution, galaxies: high-redshift}, + year = 2013, + month = jan, + volume = 145, + eid = {4}, + pages = {4}, + doi = {10.1088/0004-6256/145/1/4}, + adsurl = {http://adsabs.harvard.edu/abs/2013AJ....145....4W}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + %YYYYYYYYYYY @ARTICLE{york2000a, author = {{York}, D.~G. and {Adelman}, J. and {Anderson}, Jr., J.~E. and @@ -492,3 +1676,13 @@ @ARTICLE{york2000a adsnote = {Provided by the SAO/NASA Astrophysics Data System} } + + + + + + + + + + diff --git a/science_background/galaxies/galaxies.tex b/science_background/galaxies/galaxies.tex index 5c200a6..3e2975c 100644 --- a/science_background/galaxies/galaxies.tex +++ b/science_background/galaxies/galaxies.tex @@ -1,12 +1,8 @@ - -% LSST Extragalactic Roadmap +% LSST Galaxies Science Roadmap % Chapter: science_background % Section: galaxies -% First draft by - -\section{Galaxy Evolution Studies with LSST} -\label{sec:sci:gal:bkgnd} +{\justify Galaxies represent fundamental astronomical objects outside our own Milky Way. The large luminosities of galaxies enable their @@ -59,7 +55,7 @@ \section{Galaxy Evolution Studies with LSST} For studies of galaxies, LSST provide both an unequaled catalogue of billions of extragalactic sources and high-quality multiband imaging of individual objects. This section of -the {\it Extragalactic Roadmap} presents scientific +the {\it Galaxies Science Roadmap} presents scientific background for studies of these galaxies with LSST to provide a context for considering how the astronomical community can best leverage the catalogue and imaging datasets and for @@ -73,7 +69,7 @@ \section{Galaxy Evolution Studies with LSST} Energy Survey \citep{flaugher2005a}. Relative to these prior efforts, extragalactic science breakthroughs generated by LSST will likely benefit from its increased area, source -counts, and statistical samples, the constraining power of the +counts and statistical samples, the constraining power of the six-band imaging, and the survey depth and image quality. The following discussion of LSST efforts focusing on the astrophysics of galaxies will highlight how these features of the survey enable new science @@ -81,7 +77,7 @@ \section{Galaxy Evolution Studies with LSST} -\subsection{Star Formation and Stellar Populations in Galaxies} +\section{Star Formation and Stellar Populations in Galaxies} \label{sec:sci:gal:bkgnd:stars} Light emitted by stellar populations will @@ -136,7 +132,7 @@ \subsection{Star Formation and Stellar Populations in Galaxies} For stellar populations older than $\sim100$ million years, optical observations provide sensitivity to the spectral breaks near a -wavelength of $\lambda\approx4000\AA$ in the +wavelength of $\lambda\approx4000\mbox{\normalfont\AA}$ in the rest-frame related to absorption in the atmospheres of mature stars. Such observations help constrain @@ -148,7 +144,7 @@ \subsection{Star Formation and Stellar Populations in Galaxies} that traces the succession of galaxies from recently-merged spheroids to the most massive systems at the -centers of galaxy clusters. For blue, +centers of galaxy clusters \citep[e.g.][]{kaviraj2005a}. For blue, star-forming galaxies, optical light can help quantify the relative contribution of @@ -165,7 +161,7 @@ \subsection{Star Formation and Stellar Populations in Galaxies} Determining the physical or possibly statistical origin of the relation remains an active -line of inquiry, guided by recently improved +line of inquiry \citep[e.g.][]{lofthouse2017a}, guided by recently improved data from Hubble Space Telescope over the $\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared Deep Extragalactic Survey @@ -179,12 +175,15 @@ \subsection{Star Formation and Stellar Populations in Galaxies} that can help discriminate between phenomenological explanations of the sequence. -\subsection{Galaxies as Cosmic Structures} +\section{Galaxies as Cosmic Structures} \label{sec:sci:gal:bkgnd:structures} The structural properties of galaxies arise from an intricate combination of important astrophysical -processes. The gaseous disks of galaxies require +processes. Driven by dark matter structure growth, the dynamical +interplay between baryonic and dark matter components form +the basis for the development of galaxy properties. +The gaseous disks of galaxies require substantial energy dissipation while depositing angular momentum into a rotating structure. These gaseous disks form stars with a @@ -205,14 +204,15 @@ \subsection{Galaxies as Cosmic Structures} variety as a function of galaxy mass and cosmic environment, LSST will revolutionize studies of evolving galaxy morphologies by providing enormous -samples with deep imaging of exquisite quality. +samples with deep imaging of exquisite quality. These data also enable +studies of galaxy mass profiles via weak lensing of the background +galaxy population. The huge sample of galaxies provided by LSST will provide a definitive view of how the sizes and structural parameters of disk and spheroidal systems -vary with color, stellar mass, and luminosity. -Morphological studies will employ at least two -complementary techniques for quantifying the +vary with color, total mass, stellar mass, and luminosity. +Morphological studies will employ several complementary techniques for quantifying the structural properties of galaxies. Bayesian methods can yield multi-component parameterized models for all the galaxies @@ -224,13 +224,12 @@ \subsection{Galaxies as Cosmic Structures} of the light distribution including the Gini and M20 metrics that quantify the surface brightness uniformity and spatial moment of -dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. -Collectively, these morphological measures provided +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume of the LSST dataset, which will also change on short timescales in terms of depth, new machine-learning algorithms \citep[e.g.][]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided by analyzing the LSST imaging data will enable a consummate determination of the relation between structural properties and other features of galaxies over a range of galaxy mass and luminosity -previously unattainable. +previously unattainable. While the size of the LSST sample supplies the statistical power for definitive morphological studies, @@ -258,7 +257,7 @@ \subsection{Galaxies as Cosmic Structures} under rare conditions only well-probed by the sheer size of the LSST survey. -Similarly, the characterizing the extremes of the +Similarly, characterizing the extremes of the massive spheroid population can critically inform theoretical models for their formation. For instance, the most massive galaxies at the centers of galaxy clusters @@ -286,8 +285,23 @@ \subsection{Galaxies as Cosmic Structures} wide variation in environments probed by a survey of half the sky, the image quality of LSST will permit studies of galaxy structures in the very low surface -brightness regime. Observational -measures of the outer most regions of thin disks can constrain +brightness regime. This will allow for the characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +such as tidal features produced by mergers and interactions and density inhomogeneities, originate +from the hierarchical formation process and their +morphological properties provides critical clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observational studies using small, deep surveys like the SDSS Stripe 82 \citep[e.g.][]{kaviraj2014a,kaviraj2014b} and recent work using small telescopes \citep{martinez-delgado2008a,atkinson2013,abraham2014a,van_dokkum2014a} +have +demonstrated the critical importance of probing the low surface-brightness Universe in order to test the hierarchical galaxy formation paradigm. Since low-mass galaxies far outnumber their massive counterparts, the assembly history of massive galaxies is dominated by mergers of unequal mass ratios (`minor' mergers). However, such mergers typicaly produce tidal features that are fainter than the surface brightness limits of current surveys like the SDSS. Hence, the vast majority of merging remains, from an empirical point of view, unquantified. In other words, deep wide surveys like LSST, with its unrivalled entendue, are crucial for empirically testing the hierarchical paradigm and understanding the role of galaxy merging in driving star formation, black hole growth and morphological transformation over cosmic time \citep{kaviraj2014b}. + +Furthermore, the examination of stellar halos around galaxies will +result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +the nature of dark matter and models of the galaxy formation process at the extreme +low-mass end of the mass function. + +Finally, observational measures of the outermost regions of thin disks can constrain how such disks ``end'', how dynamical effects might truncate disks, and whether some disks smoothly transition into stellar halos. LSST will provide such measures and help quantify the @@ -301,31 +315,23 @@ \subsection{Galaxies as Cosmic Structures} surface brightness, which relates to the extremes of star formation in low surface density environments. -The ability of LSST to probe low surface brightnesses -also allows for characterization of stellar halos that -surround nearby galaxies. Structures in stellar halos, -from streams to density inhomogeneities, originate -from the hierarchical formation process and their -morphology provides clues to the formation history -on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. -Observations with small telescopes \citep{martinez-delgado2008a,abraham2014a} -have already -demonstrated that stellar halo structures display interesting -variety -\citep[e.g.,][]{van_dokkum2014a}. -LSST, with its unrivaled entendue, can help build a statistical -sample of stellar halos and cross-reference their morphologies -with the observed properties of their central galaxies. Such -studies may determine whether the formation histories reflected -in the structures of halos also influence galaxy colors or -morphological type. The -examination of stellar halos around external galaxies may -also result in the identification of small mass satellites -whose sizes, luminosities, and abundances can constrain -models of the galaxy formation process on the extreme -low-mass end of the mass function. -\subsection{Probing the Extremes of Galaxy Formation} + +The LSST survey uniquely enables precision statistical studies of +galaxy mass +distribution via weak gravitational lensing of the 40 background +galaxies per square arcminute. From the radial dependence of +the galaxy-mass correlation function, galaxy morphological properties +can be compared with the mass distribution, as a function +of redshift of the lens galaxy population (Choi et al. 2012, +Leauthaud et al. 2012). Even dwarf galaxies +can be studied in this way: the LSST survey will enable mass +mapping of samples of hundreds of thousands of dwarf galaxies. +With a sample of hundreds of millions of foreground galaxies, +for the first time trends in galaxy stellar evolution and type +can be correlated with halo mass and mass environment out beyond several Mpc. + +\section{Probing the Extremes of Galaxy Formation} \label{sec:sci:gal:bkgnd:rare} The deep, multiband imaging LSST provides over an enormous @@ -377,7 +383,7 @@ \subsection{Probing the Extremes of Galaxy Formation} of close galaxy pairs or morphological indicators of mergers provide varying estimates for the redshift dependence of the galaxy merger rate -\citep[e.g.,][]{conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,robotham2014a}. +\citep[e.g.,][]{darg2010a,conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,kaviraj2009a,robotham2014a,kaviraj2015a}. The identification of merging galaxy pairs as a function of separation, merger mass ratio, and environment in the LSST data will enable @@ -385,20 +391,30 @@ \subsection{Probing the Extremes of Galaxy Formation} the observed properties of galaxies as a function of cosmic time. -\subsection{Photometric Redshifts} +\vspace{-0.05in} + +\section{Photometric Redshifts} \label{sec:sci:gal:bkgnd:photoz} -As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-z's). While spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra, photometric redshifts, instead, estimate the rough distance to an object based on broad-band photometric colors. This can be thought of as akin to a very low-resolution spectrum sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.~the 4000\AA\ and Lyman breaks), with each broad-band filter being a single pixel in the spectrum. By relying on imaging data alone, we are able to measure photo-z's for billions of galaxies in the LSST survey, at the cost of added uncertainty in the redshift estimates, and potential redshift degeneracies. - As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-z's is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it the incorrect luminosity via the distance modulus, and can bias estimates of the luminosity function; errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to an error in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. - In order to understand the biases and uncertainties inherent to photo-z's for a particular survey, we need to train the photo-z algorithms using galaxies with known redshifts. For a full characterization, a fully representative sub-sample of the underlying galaxy population is necessary; however, in practice, this is very difficult to achieve, due to limitations in both spectroscopic instrumentation and telescope time. We can attempt to identify and remove any biases due to incomplete training data using several redshift calibration techniques, the most prominent one relying on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts. A detailed plan describing the spectroscopic needs, for training and calibration, is laid out in \citet[]{Newman2015}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be functional in the near future. As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-z training, but also to those studying galaxy formation and evolution. In addition, any insights gained on galaxy formation and evolution during the course of the LSST survey can be used to improve photo-z algorithms. For example, improved spectral energy distribution evolution models would improve photo-z performance at high redshift. Or, observable quantities such as size and surface brightness may be incorporated as Bayesian priors on the photo-z's once their distributions are well understood. This mutual benefit between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both subjects as the survey progresses. +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-$z$'s). Spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra. In contrast, photometric redshifts estimate the rough distance to an object based on its broad-band photometric colors (and, potentially, other properties measurable from imaging). The measurement of a photo-$z$ can be thought of as akin to determining redshifts from a very low-resolution but high signal-to-noise spectrum, with each broad-band filter contributing a single pixel to that spectrum. They are therefore sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.,~the 4000~\AA\ and Lyman breaks), but in general lack the definitiveness of a redshift measured from multiple well-centroided spectral features (e.g., a pair of emission or absorption lines of known separation). As a result, photometric redshifts will generally be more uncertain than spectroscopic redshift estimates and can be affected by degeneracies in the color-redshift relation. + +By relying on imaging data alone, we will be able to measure photo-$z$'s for billions of galaxies in the LSST survey. +As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it an incorrect luminosity (due to misestimation of both the distance modulus and $k$-corrections), and hence can bias estimates of the luminosity function. Errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to errors in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. + +In order to develop optimal estimates of photo-$z$'s for a particular survey, we need to train the photo-z algorithms using a set of galaxies with known redshifts. If spectroscopy is obtained for a fully representative sub-sample of the underlying galaxy population spanning the full domain of application, this spectroscopy can also be used to characterize the biases and uncertainties in the photometric redshift estimates, calibrating their use for science. -\subsection{Science Book} +However, in practice, obtaining such a fair sample will be very difficult to achieve due to limitations in spectroscopic instrumentation, telescope time, and the astrophysical properties of galaxies (e.g., objects with only extremely weak spectral features are exceedingly difficult to measure redshifts for). We can attempt to identify and remove any biases due to incomplete training data using a variety of redshift calibration techniques; the most prominent one relies on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts over wide fields, as will be provided by DESI and 4MOST \citep{newman2008a}. A detailed plan describing the spectroscopic needs for training and calibrating photometric redshifts for LSST is laid out in \citet[]{newman2015a}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be available in the near future. + +As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-$z$ training, but also to help us to study galaxy formation and evolution. The insights about the formation and evolution of galaxies we expect to gain from LSST can also be used to improve photo-$z$ algorithms, both by constraining the family of spectral energy distributions of galaxies as a function of redshift and by improving our knowledge of distributions of other observable quantities such as size and surface brightness. This mutual synergy between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both areas as the survey progresses. + +\vspace{-0.05in} +\section{Science Book} \label{sec:sci:gal:bkgnd:scibook} The LSST Science Book (\citealt{LSSTSciBook}) provided -detailed descriptions of foundationl science enabled +detailed descriptions of foundational science enabled by LSST. The LSST Galaxies Science Collaboration authored the Chapter 9 ``Galaxies'' of the Science Book, and the -a table of contents of that chapter follow below to +table of contents of that chapter follow below to provide an example list of topics in extragalactic science that LSST data will help revolutionize. The interested reader is referred to the LSST Science @@ -441,8 +457,6 @@ \subsection{Science Book} \item Special Populations of Galaxies \item Public Involvement \end{enumerate} +} - - - - +\let\cleardoublepage\clearpage diff --git a/science_background/science_background.save.tex b/science_background/science_background.save.tex new file mode 100644 index 0000000..742c1cc --- /dev/null +++ b/science_background/science_background.save.tex @@ -0,0 +1,7 @@ +% LSST Galaxies Science Roadmap +% Chapter: science_background + +\chapter[Galaxy Evolution Studies with LSST]{Galaxy Evolution Studies with LSST} +\label{ch:science_background} + +\input{science_background/galaxies/galaxies.tex} diff --git a/science_background/science_background.tex b/science_background/science_background.tex index bd4f0e0..31b6b9f 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -1,20 +1,463 @@ +% LSST Galaxies Science Roadmap +% Chapter: science_background -% LSST Extragalactic Roadmap -% Chapter: science_background -% First draft by - -\chapter[Science Background]{Science Background} +\chapter[Galaxy Evolution Studies with LSST]{Galaxy Evolution Studies with LSST} \label{ch:science_background} +{\justify + + +Galaxies represent fundamental astronomical objects +outside our own Milky Way. +The large luminosities of galaxies enable their +detection to extreme distances, providing abundant +and far-reaching probes into the depths of the universe. +At each epoch in cosmological history, the color +and brightness distributions of the galaxy population +reveal how stellar populations form with time and +as a function of galaxy mass. The progressive mix of +disk and spheroidal morphological components of +galaxies communicate the relative importance of +energy dissipation and collisionless processes +for their formation. +Correlations between internal galaxy properties and +cosmic environments indicate +the ways the universe nurtures galaxies as they form. +The evolution of the +detailed characteristics of galaxies over cosmic time +reflects how fundamental astrophysics +operates to generate the rich variety of +astronomical structures observed today. + +Study of the astrophysics of galaxy formation represents +a vital science of its own, but the ready +observability of galaxies critically enables a host of +astronomical experiments in other fields. +Galaxies act as the semaphores of the +universe, encoding information about +the development of large scale +structures and the mass-energy budget of the +universe in their spatial distribution. The mass distribution +and clustering of galaxies reflect essential +properties of dark matter, including potential +constraints on the velocity and mass of particle candidates. +Galaxies famously host supermassive black holes, +and observations of active galactic nuclei provide +a window into the high-energy astrophysics of black hole +accretion processes. The porous interface between the +astrophysics of black holes, galaxies, and +dark matter structures allows for astronomers to +achieve gains in each field using the same datasets. + +The Large Synoptic Survey Telescope (LSST) will provide a +digital image of the southern sky in six bands ($ugrizy$). +The area ($\sim18,000~\mathrm{deg}^2$) and depth +($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of +the survey will enable research of such breadth +that LSST may influence essentially all extragalactic +science programs that rely primarily on photometric data. +For studies of galaxies, LSST provide both an unequaled +catalogue of billions of extragalactic sources and high-quality +multiband imaging of individual objects. This section of +the {\it Galaxies Science Roadmap} presents scientific +background for studies of these galaxies with LSST to provide a +context for considering how the astronomical community can +best leverage the catalogue and imaging datasets and for +identifying any required preparatory science tasks. + +LSST will begin science operations during the next decade, +more than twenty years after the start of the Sloan +Digital Sky Survey \citep{york2000a} and subsequent precursor surveys +including PanSTARRS \citep{kaiser2010a}, the Subaru +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark +Energy Survey \citep{flaugher2005a}. Relative to these prior +efforts, extragalactic science breakthroughs +generated by LSST will likely benefit from its increased area, source +counts and statistical samples, the constraining power of the +six-band imaging, and the survey depth and image quality. The following +discussion of LSST efforts focusing on the astrophysics of galaxies +will highlight how these features of the survey enable new science +programs. + + + +\section{Star Formation and Stellar Populations in Galaxies} +\label{sec:sci:gal:bkgnd:stars} + +Light emitted by stellar populations will +provide all the direct measurements made by +LSST. This information will be filtered through +the six passbands utilized by the survey +($ugrizy$), providing constraints on the +rest-frame ultraviolet SEDs of galaxies to +redshift $z\sim6$ and a probe of rest-frame +optical spectral breaks to $z\sim1.5$. By +using stellar population synthesis modeling, +these measures of galaxy SEDS will enable +estimates of the redshifts, star formation rates, +stellar masses, dust content, and +population ages for potentially +billions of galaxies. In the context of previous +extragalactic surveys, LSST +will enable new advances in our understanding +of stellar populations in galaxies by contributing +previously unachievable statistical power and an +areal coverage that samples the rarest cosmic +environments. + +A variety of ground- and space-based observations +have constrained the +star formation history of the universe over the +redshift range that LSST will likely probe +\citep[for a recent review, see][]{madau2014a}. +The statistical power of LSST will improve our +knowledge of the evolving UV luminosity function, +luminosity density, and cosmic +star formation rate. The LSST observations can +constrain how the astrophysics of gas +cooling within dark matter halos, the efficiency +of molecular cloud formation and the star formation +within them, and +regulatory mechanisms like supernova and radiative +heating give rise to these statistical features +of the galaxy population. While measurement of +the evolving UV luminosity function can +help quantify the role of these +astrophysical processes, the ability of LSST +to probe vastly different cosmic environments +will also allow for the robust quantification of any +changes in the UV luminosity function with +environmental density, and an examination of +connections between environment and the fueling +of star formation. + +Optical observations teach us about +the established stellar content of galaxies. +For stellar populations older than $\sim100$ million +years, optical observations provide +sensitivity to the spectral breaks near a +wavelength of $\lambda\approx4000\mbox{\normalfont\AA}$ in the +rest-frame related to absorption in the +atmospheres of mature stars. +Such observations help constrain +the amount of stellar mass in galaxies. For +passive galaxies that lack vigorous star formation, +these optical observations reveal +the well-defined ``red sequence'' of +galaxies in the color-magnitude plane +that traces the succession of +galaxies from recently-merged spheroids +to the most massive systems at the +centers of galaxy clusters \citep[e.g.][]{kaviraj2005a}. For blue, +star-forming +galaxies, optical light can help +quantify the relative contribution of +evolved stars to total galaxy luminosity, +and indeed has +led to the identification of a well-defined +locus of galaxies in the parameter space of +star formation rate and stellar mass +\citep[e.g.,][]{noeske2007a}. This +relation, often called the ``star-forming +main sequence'' of galaxies, indicates that +galaxies of the same stellar mass typically +sustain a similar star-formation rate. +Determining the +physical or possibly statistical +origin of the relation remains an active +line of inquiry \citep[e.g.][]{lofthouse2017a}, guided by recently improved +data from Hubble Space Telescope over the +$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared +Deep Extragalactic Survey +\citep{grogin2011a,koekemoer2011a}. While +LSST will be comparably limited in redshift +selection, its $~30,000$ times larger area +will enable a much fuller sampling of the +star formation--stellar mass plane, allowing +for a characterization of the distribution +of galaxies that lie off the main sequence +that can help discriminate between phenomenological +explanations of the sequence. + +\section{Galaxies as Cosmic Structures} +\label{sec:sci:gal:bkgnd:structures} + +The structural properties of galaxies arise from +an intricate combination of important astrophysical +processes. Driven by dark matter structure growth, the dynamical +interplay between baryonic and dark matter components form +the basis for the development of galaxy properties. +The gaseous disks of galaxies require +substantial energy dissipation while depositing +angular momentum into a rotating structure. These +gaseous disks form stars with a +surface density that declines exponentially with +galactic radius, populating stellar orbits that +differentially rotate about the galactic center and +somehow organize into spiral features. +Many disk galaxies contain (pseduo-)bulges that form through +a combination of violent relaxation and orbital dynamics. +These disk galaxy features contrast with systems where +spheroidal stellar distributions dominate the galactic +structure. Massive ellipticals form through galaxy +mergers and accretions, and manage to forge a regular +sequence of surface density, size, and stellar velocity +dispersion from the chaos of strong gravitational +encounters. Since these astrophysical +processes may operate with great +variety as a function of galaxy mass and +cosmic environment, LSST will revolutionize studies +of evolving galaxy morphologies by providing enormous +samples with deep imaging of exquisite quality. These data also enable +studies of galaxy mass profiles via weak lensing of the background +galaxy population. + +The huge sample of galaxies provided by LSST will +provide a definitive view of how the sizes and +structural parameters of disk and spheroidal systems +vary with color, total mass, stellar mass, and luminosity. +Morphological studies will employ several complementary techniques for quantifying the +structural properties of galaxies. Bayesian +methods can yield multi-component +parameterized models for all the galaxies +in the LSST sample, including the quantified +contribution of bulge, disk, and +spheroid structures to the observed galaxy +surface brightness profiles. The parameterized +models will supplement non-parametric measures +of the light distribution including the +Gini and M20 metrics that quantify the surface +brightness uniformity and spatial moment of +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume of the LSST dataset, which will also change on short timescales in terms of depth, new machine-learning algorithms \citep[e.g.][]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided +by analyzing the LSST imaging data will enable +a consummate determination of the relation between +structural properties and other features of +galaxies over a range of galaxy mass and luminosity +previously unattainable. + +While the size of the LSST sample supplies the +statistical power for definitive morphological studies, +the sample size also enables the identification of rare +objects. This capability will benefit our efforts for +connecting the distribution of galaxy morphologies to their +evolutionary origin during the structure formation process, +including the formation of disk galaxies. +The emergence of ordered disk galaxies remains a hallmark +event in cosmic history, with so-called ``grand design'' +spirals like the Milky Way forming dynamically cold, thin +disks in the last $\sim10$ Gyr. Before thin disks emerged, +rotating systems featured ``clumpy'' mass distributions with +density enhancements +that may originate from large scale gravitational instability. +Whether the ground-based LSST can effectively probe +the exact timing and duration of the transition from +clumpy to well-ordered disks remains +unknown, but LSST can undoubtedly contribute studying the +variation in forming disk structures at the present day. +Unusual objects, such as the UV luminous local galaxies identified +by \citet{heckman2005a} that display physical features analogous to +Lyman break galaxies at higher redshifts, may provide a +means to study the formation of disks in the present day +under rare conditions only well-probed by the sheer size +of the LSST survey. + +Similarly, characterizing the extremes of the +massive spheroid population can critically inform +theoretical models for their formation. For instance, +the most massive galaxies at the centers of galaxy clusters +contain vast numbers of stars within enormous stellar +envelopes. The definitive LSST sample can capture enough +of the most massive, rare clusters to quantify the +spatial extent of these galaxies at +low surface brightnesses, where the bound stellar +structures blend with the intracluster light of +their hosts. Another research area the LSST data +can help address regards the central densities of local +ellipticals that have seemingly decreased compared with +field ellipticals at higher redshifts. The transformation +of these dense, early ellipticals to the spheroids in the +present day may involve galaxy mergers and environmental +effects, two astrophysical processes that LSST can characterize +through unparalleled statistics and environmental probes. +By measuring the +surface brightness profiles of billions of +ellipticals LSST can determine whether any such dense +early ellipticals survive to the present day, whatever +their rarity. + +Beyond the statistical advances enabled by LSST and the +wide variation in environments probed by a survey +of half the sky, the image quality of LSST will permit +studies of galaxy structures in the very low surface +brightness regime. This will allow for the characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +such as tidal features produced by mergers and interactions and density inhomogeneities, originate +from the hierarchical formation process and their +morphological properties provides critical clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observational studies using small, deep surveys like the SDSS Stripe 82 \citep[e.g.][]{kaviraj2014a,kaviraj2014b} and recent work using small telescopes \citep{martinez-delgado2008a,atkinson2013,abraham2014a,van_dokkum2014a} +have +demonstrated the critical importance of probing the low surface-brightness Universe in order to test the hierarchical galaxy formation paradigm. Since low-mass galaxies far outnumber their massive counterparts, the assembly history of massive galaxies is dominated by mergers of unequal mass ratios (`minor' mergers). However, such mergers typicaly produce tidal features that are fainter than the surface brightness limits of current surveys like the SDSS. Hence, the vast majority of merging remains, from an empirical point of view, unquantified. In other words, deep wide surveys like LSST, with its unrivalled entendue, are crucial for empirically testing the hierarchical paradigm and understanding the role of galaxy merging in driving star formation, black hole growth and morphological transformation over cosmic time \citep{kaviraj2014b}. + +Furthermore, the examination of stellar halos around galaxies will +result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +the nature of dark matter and models of the galaxy formation process at the extreme +low-mass end of the mass function. + +Finally, observational measures of the outermost regions of thin disks can constrain +how such disks ``end'', how dynamical effects might truncate +disks, and whether some disks smoothly transition into stellar +halos. LSST will provide such measures and help quantify the +relative importance the physical effects that influence the +low surface brightness regions in disks. Other galaxies +have low surface brightnesses throughout their stellar +structures, and the image quality and sensitivity +of LSST will enable the most complete census +of low surface brightness galaxies to date. LSST will provide +the best available constraints on the extremes of disk +surface brightness, which relates to the extremes of +star formation in low surface density environments. + + + +The LSST survey uniquely enables precision statistical studies of +galaxy mass +distribution via weak gravitational lensing of the 40 background +galaxies per square arcminute. From the radial dependence of +the galaxy-mass correlation function, galaxy morphological properties +can be compared with the mass distribution, as a function +of redshift of the lens galaxy population (Choi et al. 2012, +Leauthaud et al. 2012). Even dwarf galaxies +can be studied in this way: the LSST survey will enable mass +mapping of samples of hundreds of thousands of dwarf galaxies. +With a sample of hundreds of millions of foreground galaxies, +for the first time trends in galaxy stellar evolution and type +can be correlated with halo mass and mass environment out beyond several Mpc. + +\section{Probing the Extremes of Galaxy Formation} +\label{sec:sci:gal:bkgnd:rare} + +The deep, multiband imaging LSST provides over an enormous +area will enable the search for galaxies that form in the +rarest environments, under the most unusual conditions, +and at very early times. By probing the extremes of +galaxy formation, the LSST data will push our theoretical +understanding of the structure formation process. + +The rarest, most massive early galaxies may form in +conjunction with the supermassive black holes that +power distant quasars. LSST can use the same +types of color-color selections to identify extremely +luminosity galaxies out to redshift $z\sim6$, and +monitor whether the stellar mass build-up in these +galaxies tracks the accretion history of the most +massive supermassive black holes. If stellar mass +builds proportionally to black hole mass in quasars, +then very rare luminous star forming galaxies at +early times may immediately proceed the formation +of bright quasars. LSST has all the requisite +survey properties (area, mutliband imaging, and +depth) to investigate this long-standing problem. + +The creation of LSST Deep Drilling fields will +enable a measurement of the very bright end +of the high-redshift galaxy luminosity function. +Independent determinations of the distribution of +galaxy luminosities at $z\sim6$ show substantial +variations at the bright end. The origin of +the discrepancies between various groups remains +unclear, but the substantial cosmic variance expected +for the limited volumes probed and the intrinsic +rarity of the bright objects may conspire to +introduce large potential differences between +the abundance of massive galaxies in different +areas of the sky. Reducing this uncertainty requires +deep imaging over a wide area, and the LSST Deep Drilling +fields satisfy this need by achieving sensitivities +beyond the rest of the survey. + +Lastly, the spatial rarity of extreme objects discovered +in the wide LSST area may reflect an intrinsically +small volumetric density of objects or the short duration +of an event that gives rise to the observed properties of the +rare objects. Mergers represent a critical class +of short-lived epochs in the formation histories of +individual galaxies. Current determinations of the evolving numbers +of close galaxy pairs or morphological indicators of +mergers provide varying estimates for the +redshift dependence of the galaxy merger rate +\citep[e.g.,][]{darg2010a,conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,kaviraj2009a,robotham2014a,kaviraj2015a}. +The identification of merging +galaxy pairs as a function of separation, merger +mass ratio, and environment in the LSST data will enable +a full accounting of how galaxy mergers influence +the observed properties of galaxies as a function of +cosmic time. + +\vspace{-0.05in} + +\section{Photometric Redshifts} +\label{sec:sci:gal:bkgnd:photoz} +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-$z$'s). Spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra. In contrast, photometric redshifts estimate the rough distance to an object based on its broad-band photometric colors (and, potentially, other properties measurable from imaging). The measurement of a photo-$z$ can be thought of as akin to determining redshifts from a very low-resolution but high signal-to-noise spectrum, with each broad-band filter contributing a single pixel to that spectrum. They are therefore sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.,~the 4000~\AA\ and Lyman breaks), but in general lack the definitiveness of a redshift measured from multiple well-centroided spectral features (e.g., a pair of emission or absorption lines of known separation). As a result, photometric redshifts will generally be more uncertain than spectroscopic redshift estimates and can be affected by degeneracies in the color-redshift relation. + +By relying on imaging data alone, we will be able to measure photo-$z$'s for billions of galaxies in the LSST survey. +As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it an incorrect luminosity (due to misestimation of both the distance modulus and $k$-corrections), and hence can bias estimates of the luminosity function. Errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to errors in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. + +In order to develop optimal estimates of photo-$z$'s for a particular survey, we need to train the photo-z algorithms using a set of galaxies with known redshifts. If spectroscopy is obtained for a fully representative sub-sample of the underlying galaxy population spanning the full domain of application, this spectroscopy can also be used to characterize the biases and uncertainties in the photometric redshift estimates, calibrating their use for science. + +However, in practice, obtaining such a fair sample will be very difficult to achieve due to limitations in spectroscopic instrumentation, telescope time, and the astrophysical properties of galaxies (e.g., objects with only extremely weak spectral features are exceedingly difficult to measure redshifts for). We can attempt to identify and remove any biases due to incomplete training data using a variety of redshift calibration techniques; the most prominent one relies on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts over wide fields, as will be provided by DESI and 4MOST \citep{newman2008a}. A detailed plan describing the spectroscopic needs for training and calibrating photometric redshifts for LSST is laid out in \citet[]{newman2015a}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be available in the near future. -%TBD -%\input{science_background/chapterintro.tex} +As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-$z$ training, but also to help us to study galaxy formation and evolution. The insights about the formation and evolution of galaxies we expect to gain from LSST can also be used to improve photo-$z$ algorithms, both by constraining the family of spectral energy distributions of galaxies as a function of redshift and by improving our knowledge of distributions of other observable quantities such as size and surface brightness. This mutual synergy between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both areas as the survey progresses. +\vspace{-0.05in} +\section{Science Book} +\label{sec:sci:gal:bkgnd:scibook} -\input{science_background/galaxies/galaxies.tex} +The LSST Science Book (\citealt{LSSTSciBook}) provided +detailed descriptions of foundational science enabled +by LSST. The LSST Galaxies Science Collaboration authored +the Chapter 9 ``Galaxies'' of the Science Book, and the +table of contents of that chapter follow below to +provide an example list of topics in extragalactic +science that LSST data will help revolutionize. The +interested reader is referred to the LSST Science +Book for more details. -%\input{science_background/black_holes/black_holes.tex} -%\input{science_background/informatics/informatics.tex} -%\input{science_background/lss/lss.tex} -%\input{science_background/strong_lensing/strong_lensing.tex} -%\input{science_background/weak_lensing/weak_lensing.tex} +\begin{enumerate} +\item Measurements, Detection, Photometry, Morphology +\item Demographics of Galaxy Populations +\begin{itemize} +\item Passively evolving galaxies +\item High-redshift star forming galaxies +\item Dwarf galaxies +\item Mergers and interactions +\end{itemize} +\item Distribution Functions and Scaling Relations +\begin{itemize} +\item Luminosity and size evolution +\item Relations between observables +\item Quantifying the Biases and Uncertainties +\end{itemize} +\item Galaxies in their Dark-Matter Context +\begin{itemize} +\item Measuring Galaxy Environments with LSST +\item The Galaxy-Halo Connection +\item Clusters and Cluster Galaxy Evolution +\item Probing Galaxy Evolution with Clustering Measurements +\item Measuring Angular Correlations with LSST, Cross-correlations +\end{itemize} +\item Galaxies at Extremely Low Surface Brightness +\begin{itemize} +\item Spiral Galaxies with LSB Disks +\item Dwarf Galaxies +\item Tidal Tails and Streams +\item Intracluster Light +\end{itemize} +\item Wide Area, Multiband Searches for High-Redshift Galaxies +\item Deep Drilling Fields +\item Galaxy Mergers and Merger Rates +\item Special Populations of Galaxies +\item Public Involvement +\end{enumerate} +} \ No newline at end of file diff --git a/structure.tex b/structure.tex index d0bba70..8bd3c63 100644 --- a/structure.tex +++ b/structure.tex @@ -1,6 +1,6 @@ \usepackage{amsmath} \usepackage{amssymb} -\usepackage[top=3cm,bottom=3cm,left=3cm,right=3cm,headsep=10pt]{geometry} % Page margins +\usepackage[top=3cm,bottom=3cm,left=0.8in,right=0.8in,headsep=10pt]{geometry} % Page margins \usepackage{graphicx} % Required for including pictures diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index 7705045..b9eebe9 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -1,26 +1,50 @@ -\section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} +\section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} {\justify -AGN are phenomena that enable us to understand the growth of BHs, understand aspects of galaxy evolution, probe the high redshift universe and study other physical activity, including accretion physics, jets, magnetic fields, etc. There are distinct aspects of the study of AGN that can best be explored by considering AGN as an evolutionary stage of galaxies rather than a distinct type of source. The tasks listed here explore aspects of AGN study that are particularly important AGN as a stage in galaxy evolution. + +Active Galactic Nuclei (AGN) phenomena enable us to understand the growth of supermassive black holes (BHs), understand aspects of galaxy evolution, probe the high redshift universe, and study other physical activity including accretion physics, jets, and magnetic fields. +While AGN represent a distinct topic within the LSST Science Collaborations, the LSST +dataset will reveal some aspects of AGN science via their role as an +evolutionary stage of galaxies in addition to their ability to probe accretion physics around BHs. +The tasks listed here present preparatory science efforts connected with AGN study as a special +phase in galaxy evolution. \begin{tasklist}{AGN} -\subsection{AGN feedback in clusters} -\tasktitle{AGN feedback in clusters} +\subsection{AGN Selection from LSST Data} +\tasktitle{AGN Selection from LSST Data} \begin{task} -\label{task:agn:feedback_in_clusters} +\label{task:agn:selection} \motivation{ -Brightest Cluster/Group Galaxies (hereafter BCGs) are the most massive galaxies in the local Universe residing at/near the centres of galaxy clusters/groups. They will therefore contain the largest supermassive black holes. These black holes can influence their host BCG, the cluster gas and other cluster members via the mechanical energy produced by their 100s kpc scale jets (AGN feedback). -\\ -For low redshift galaxy clusters it is possible to perform detailed studies of the star, gas and AGN jets to analyse the details of AGN feedback. LSST will provide a large sample of moderate to high redshift clusters in which we can measure AGN feedback statistically. By combining X-ray, radio and optical observations we can assess the average influence of the BCG's AGN on the hot Intra-cluster medium (ICM) for different sub-populations [e.g. Stott et al. 2012]. -} +LSST multiband photometry may select Active Galactic Nuclei using a variety of different methods. At optical and near infrared wavelengths, the distinctive colors of AGN +at particular redshifts enables their photometric selection. +The LSST data will therefore augment methods that rely on X-ray or radio activity, or the +identification of emission lines in spectroscopic data. +LSST will also open up, in a more practical way, the identification of AGN based on their variability. +These LSST photometric, multiwavelength, and variability-selected samples may probe +unique aspects of AGN phenomena. +A better understanding of the AGN role in galaxy evolution requires +that we understand how and why these selection methods include or exclude particular sources +or phases of AGN-galaxy co-evolution. +} +~\\ \activities{ -By assembling a multi-wavelength dataset (optical, X-ray, Radio) we can obtain the BCG mass, cluster mass and ICM temperature, and the mechanical power injected into the ICM. We can use this to study the interplay between the BCG, its black hole and the cluster gas, to assess the balance of energies involved and for direct comparison with theoretical models of AGN feedback. This has been done with a few hundred clusters at z<0.3 using SDSS but we may well be able to reach z=1 and therefore look for an evolution in their interplay and therefore AGN feedback. There are also implications for cosmology too as this will help with the selection of clusters for which the X-ray properties better represent the mass of the cluster rather than the complex interplay of baryonic physics. } - +The use of LSST as a single way to identify AGN and characterize their diversity of AGN +requires the development of selection criteria that can leverage the color, morphology, +and variability information available from LSST imaging alone. +A number of AGN surveys with input from multiple wavelength observation and spectra already +exist, and precursor work must utilize these surveys to determine +whether AGN that prove difficult to identify via optical color selection will reveal +themselves through the additional parameters of morphology, variability, and/or the +near-infrared data that LSST will provide. +} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Investigate the number of BCGs and the mass range of their clusters with redshift that LSST is likely to be able to observe. -\item Assess radio and X-ray data available for AGN Feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS etc). -\item Assess the theoretical predictions expected for the above (e.g. cosmological simulations such as EAGLE or more detailed single cluster studies). +\item Creation of a cross-matched catalog of known AGN selected and verified using different methods. +\item Development of morphological parameters beyond star/galaxy separation and an understanding of the efficacy of LSST Level 2 data products for morphological selection of AGN. +\item Development of color selection criteria that accounts for morphology. +\item Understanding of AGN variability sensitivity given the nominal LSST cadence. +\item Development of algorithms for color selection account for AGN variability. \end{enumerate} } \end{task} @@ -28,45 +52,72 @@ \subsection{AGN feedback in clusters} %\begin{tasklist}{T} -\subsection{AGN Selection from LSST Data} -\tasktitle{AGN Selection from LSST Data} +\subsection{AGN Host Galaxy Properties from LSST Data} +\tasktitle{AGN Host Galaxy Properties from LSST Data} \begin{task} -\label{task:agn:selection} +\label{task:agn:host_galaxies} \motivation{ -Active Galactic Nuclei are selected using a variety of different methods. At optical and infrared wavelengths, photometric selection of AGN candidates is driven by their distinctive colors at particular redshifts. X-ray and radio observations can also be efficient selectors of candidates for additional follow-up. With spectral data, AGN can be selected using the ratios of their emission lines. LSST will also open up, in a more practical way, the identification of AGN based on their variability. -Each of these samples probes aspects of the AGN phenomena and a better understanding of the AGN role in galaxy evolution requires that we understand how and why each of these selection methods includes or excludes particular sources. Furthermore, currently each of these methods for identifying AGN candidates requires spectral follow-up to cull these samples to positively identify the most reliably clean AGN sample. +Morphological characterizations from parameterized models, such as multiple-component +\cite{sersic1968a} profiles, or non-parametric measures like CAS and Gini-M20 \cite{abraham1994a,conselice2000a,lotz2004a} can help identify mergining galaxies in the LSST data. +The ability of these techniques to characterize efficiently and accurately the +morphology of AGN host galaxies identified via their variability remains unproven. } +~\\ \activities{ -For us to use LSST as a single way to identify the diversity of AGN, we must develop selection criteria that take advantage of the source parameters available with just LSST imaging, that is, color, morphology and variability. Already there are a number of AGN surveys with input from multiple wavelength observation and spectra. Precursor work needs to be done using these surveys to determine if AGN not easily identified using optical color selection can be selected using the additional parameters of morphology, variability and/or the additional filter that LSST provides. -} +Simulated or model AGN host galaxies can characterize whether the +LSST Level 2 data will enable the measurement of morphological features associated with +AGN, as a function of host galaxy properties, AGN luminosity, and variability. +For each model galaxy, varying the central AGN luminosity will reveal the impact of +central source brightness on the recovery of morphological properties. +Existing data sets, such as Pan-STARRS, may help inform LSST about the range of +variability frequency and amplitude, and how these AGN properties may affect the +recovery of morphological properties in AGN host galaxies. +} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Cross-matched catalog of known AGN selected and verified using different methods -\item Development of morphology parameters beyond just star/galaxy separation and an understanding of the morphology parameters to be provided by LSST level 2 products. -\item Development of color selection criteria that takes into account the morphology of the source -\item Understanding of how AGN variability looks given the nominal LSST cadence -\item Development of algorithms for color selection that take into account the variability of an AGN source +\item Characterization of the accuracy and precision afforded by the LSST dataset for the +recovery of basic morphology properties as a function of AGN brightness and wavelength. +\item Understaing of the effects of AGN brightness and variability on host-galaxy classification diagrams. \end{enumerate} } \end{task} %\end{tasklist} - -%\begin{tasklist}{T} -\subsection{AGN Host Galaxy Properties from LSST Data} -\tasktitle{AGN Host Galaxy Properties from LSST Data} +\subsection{AGN Feedback in Clusters} +\tasktitle{AGN Feedback in Clusters} \begin{task} -\label{task:agn:host_galaxies} +\label{task:agn:feedback_in_clusters} \motivation{ -We are requesting that basic morphological parameters (e.g., CAS, G-M20, etc.) be measured in the pipeline and made available as products to help in the identification of merging galaxies in LSST data. The issue here is how well this can be done when the host galaxies contain AGN that are likely identified via their variability. In other words, how well can we determine the host morphology of galaxies with variable AGN? This would be interesting for models of AGN fueling during mergers. +Brightest Cluster/Group Galaxies (hereafter BCGs) represent the most massive galaxies in the local +universe, residing at/near the centers of galaxy clusters/groups. +BCGs contain the largest known supermassive BHs that can influence the host galaxy properties, +cluster gas, and other cluster members via the mechanical energy produced by their $>100$kpc +scale jets (``AGN feedback''). +\\ +The relative proximity of low-redshift galaxy clusters enable detailed studies of +stars, gas, and AGN jets that may reveal the ramifications of AGN feedback. +LSST will provide a large sample of moderate- to high-redshift clusters +in which we can measure AGN feedback statistically. By combining X-ray, radio, and optical observations we can assess the average influence of BCG AGN on the hot intracluster medium (ICM) for different sub-populations \citep[e.g.,][]{stott2012a}. } +~\\ \activities{ -Simulations of the accuracy by which the pipeline (deblender) can measure the defined morphology parameters in host galaxies as a function of AGN brightness and wavelength. We could then ``vary'' the central source by expected levels in certain filters to see the effect on the morphological params. To constrain this it would be helpful to add in central sources with reasonable SEDs across the LSST bands, and a limited set of frequencies/amplitudes (based on real data - perhaps Pan-STARRS?). -} +By assembling a multi-wavelength dataset (optical, X-ray, and radio) we can obtain the BCG mass, cluster mass, ICM temperature, and the mechanical power injected into the ICM. +We can use this to study the interplay between the BCG, its black hole, and the cluster gas, +providing an assessment of the balance of energies involved and a direct comparison with theoretical models of AGN feedback. +SDSS has enabled this multi-wavelength analysis for a few hundred clusters at $z<0.3$, +but LSST cluster datasets to reach $z>1$. +Such studies hold implications for cosmological studies by helping to distinguish between +X-ray gas properties strongly influenced by AGN in addition to the +cluster mass. +} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Plots of the accuracy of the measured basic morphology parameters as a function of AGN brightness and wavelength. -\item Effect of AGN brightness on classification diagrams. +\item Investigation of the number of BCGs and the mass range of their clusters with redshift that LSST will likely observe. +\item Assessment of radio and X-ray data available for AGN Feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS, etc.). +\item Assessment of theoretical predictions expected for the multi-wavelength properties of +AGN host galaxies in clusters or groups (e.g., cosmological simulations such as EAGLE or more detailed single cluster studies). \end{enumerate} } \end{task} @@ -78,10 +129,15 @@ \subsection{AGN Variability Selection in LSST Data} \begin{task} \label{task:agn:variability} \motivation{ -Most AGN exhibit broad-band aperiodic, stochastic variability across the entire EM spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, making it a powerful probe of accretion physics. The main LSST WFD survey will obtain $\sim10^8$ AGN light curves (i.e. flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. The deep drilling fields will give us AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will critically depend on the interval between observations in individual filter bands. It is of crucial importance to determine guidelines for an optimal survey strategy (from an AGN variability perspective) and determine what biases and uncertainties are introduced into AGN variability science as a result of the chosen survey strategy.} +Most AGN exhibit broad-band aperiodic, stochastic variability across the entire electromagnetic +spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, providing a powerful probe of accretion physics. +The main LSST Wide-Fast-Deep (WFD) survey will obtain $\sim10^8$ AGN light curves (i.e., flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. +The Deep Drilling Fields will provide AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will crucially depend on the interval between observations in individual filter bands. These concerns motivate a determinination of guidelines for an optimal survey strategy (from an AGN variability perspective) and a discovery +of possible biases and uncertainties introduced into AGN variability science as a result of the chosen survey strategy.} +~\\ \activities{ -Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate \& study simulations using parameters selected from these models with the observationally determined constraints to determine goodness of simulations for carrying out various types of AGN variability science - PSD models, QPO searches, binary AGN models, etc. -} +Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate and study simulations using parameters selected from these models using observational constraints, and determine the appropriateness of simulations for carrying out various types of AGN variability science including power spectrum models, quasi-periodic oscillation searches, and binary AGN models.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Observational constraints on AGN variability models. @@ -97,15 +153,23 @@ \subsection{AGN Photometric Redshifts from LSST Data} \begin{task} \label{task:agn:photoz} \motivation{ -Given the large number of AGN that will be observed with LSST, many of these will not be followed up with spectral observations. However, understanding the large scale structure of the universe, requires a 3-D understanding of the distribution of these galaxies in the universe. Photometric redshifts can provide relatively accurate redshifts for large numbers of galaxies. However, it is harder to obtain accurate photometric redshifts for galaxies that contain AGN compared to those that do not. We must understand how to get accurate photometric redshifts of galaxies with AGN. +Given the large number of AGN that LSST will discover, +many AGN will not receive follow-up with spectroscopic observations. +Photometric redshifts can provide relatively accurate redshifts for large numbers of galaxies, +but accurate photometric redshifts for AGN host galaxies remain challenging. } +~\\ \activities{ -An initial activity for this need to include comprehensive review of the state of the art in obtaining photo-z’s for AGN host galaxy populations and how those compare to non-AGN galaxies. A comparison of model and/or observed AGN host SEDs with a matched set of non-host galaxies at a variety of redshifts will be used to determine color selection criteria for identifying AGN hosts. Explore whether variability can be used to break degeneracies. +Initial efforts include a comprehensive review of the state of the art in AGN host galaxy photo-$z$ +determinations and an analysis of AGN vs. non-AGN galaxy photo-$z$ performance. +A comparison of model and/or observed AGN host SEDs with a matched set of +non-host galaxies at a variety of redshifts will help engineer color selection criteria for identifying AGN hosts, and whether variability can break photo-$z$ degeneracies. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Plots that show AGN host color selection criteria and where that color selection might become ambiguous (be degenerate) for non-host galaxies with different parameters. -\item Plots that show if other parameters might break degeneracies. +\item Development of AGN host color selection criteria, and an identification of objects for which color selection might prove ambiguous or degenerate. +\item Exploration of multiwavelength, morphological, or variability information that might break photo-$z$ degeneracies. \end{enumerate} } \end{task} @@ -117,18 +181,27 @@ \subsection{AGN Merger Signature from LSST Data} \begin{task} \label{task:agn:mergers} \motivation{ -Understanding the role AGN play in galaxy evolution requires identifying the phenomenon at all stages and in all types of galaxies. AGN host galaxies are often found to be disturbed suggesting that the galaxy merger process is an important trigger of AGN activity. While the ‘trainwrecks’ may be easier to find, galaxies in other merger stages can be difficult to identify and those experiencing ‘pre-merger’ harassment may be particularly hard to recognize. Preliminary work needs to be done to understand how to identify mergers from the LSST data products and whether galaxy deblending and segmentation methods and procedures are adequate or mask galaxy mergers. +Understanding the role AGN play in galaxy evolution requires identifying AGN phenomena at all stages and in all types of galaxies. +AGN host galaxies often show disturbed morphology, suggesting that the galaxy merger process may trigger AGN activity. +While the ``trainwrecks'' may prove easy to identify in the high-quality LSST data, the +identification of galaxies in other merger stages, such as ``pre-merger'' harassment, may be particularly hard to recognize. +Preliminary work needs to be done to understand how to identify mergers from the LSST data products and whether galaxy deblending and segmentation methods and procedures are adequate. } +~\\ \activities{ -Create or Identify simulated and real images that contain known galaxy mergers, these images should contain mergers with and without AGN. -Run LSST detection and identification software on these images. -Identify metrics that describe/quantify the accurate detection of galaxy mergers (with and without AGN). +Create simulated or identify real images that contain known galaxy mergers, including +systems with and without visible AGN. +Run the LSST software stack on these images, and +engineer metrics that describe/quantify +the accurate detection of galaxy mergers with and without AGN. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Give feedback to LSST software teams about metrics and detection of galaxy mergers -\item Give feedback on structure or galaxy type that do and do not work well with current versions of LSST software +\item Improve the ability of the LSST Level 2 data to enable the detection of galaxy mergers with AGN. +\item Identify merging galaxy properties or categories that will prove challenging to measure using the LSST datasets. \end{enumerate} } \end{task} \end{tasklist} +} \ No newline at end of file diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex new file mode 100644 index 0000000..80efe14 --- /dev/null +++ b/task_lists/aux/aux.tex @@ -0,0 +1,144 @@ +\section{Auxiliary Data}\label{sec:tasks:aux} +{\justify +While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing and upcoming external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, x-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation, and during, LSST operations it is therefore prudent to ensure appropriate access, use-ability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. + + + +\begin{tasklist}{AUX} +\subsection{A database of extra-galactic optical/NIR spectroscopy within the LSST footprint} +\tasktitle{AUX} +\begin{task} +\label{task:aux:spectroscopy} +\motivation{ +Although great strides have been made in projects using photometric redshifts alone, some science is only possible with either spectroscopic redshifts and/or spectroscopic line measurements. In particular, spectroscopic redshifts are essential when distance accuracies of less than 1000 km/s are required; for example in identifying galaxy pairs and groups. Robust measurement of gas and stellar phase metalicities also require relatively high-S/N spectra (3 to 20 respectively) at a spectral resolution of better than a few Angstroms. Finally, photometric redshifts still require spectroscopic redshifts for both calibration and accuracy assessment. As such, it is essential that we ensure the LSST community has access to the available high precision redshifts, spectroscopically-derived properties and calibrated spectra for all available galaxies and quasars within the LSST footprint. This necessarily entails bringing together data from disparate surveys (such as 2dFGRS, SDSS, 6dF, MGC, GAMA, VIPERS, VVDS), the homogenization of data products and quality control, as well as the ongoing ingestion of upcoming spectroscopic campaigns such as TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. This will require significant pre-LSST effort. +} +~\\ +\activities{ +Several activities are necessary to compile this spectroscopic database: +\begin{enumerate} +\item Establishment of a database structure capable of accommodating and serving both spectra and derived data products including fast SQL database queries +\item Ingestion of existing key public datasets including, for example: 2dFGRS, SDSS, 2QZ, 2SLAQ, 6dF, MGC, GAMA, ESP, VVDS, VIPERS +\item A process for establishing quality control and homogenization of datasets including assignment of revised quality flags +\item A pathway for ingesting future datasets as they become available and potentially in advance via MOU arrangements, e.g., TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. +\end{enumerate} +Approximately 6 million spectroscopic redshifts are known, with the majority of these already in the public domain; along with associated flux and wavelength calibrated spectra. In addition, derived parameters also exist for many of these spectra including, but not limited too, redshifts, equivalent widths, velocity dispersions, line asymmetries etc. Many of these measurements have been made using bespoke software specific to each originating survey (e.g., SDSS v 2dFGRS), creating an inhomogeneous network of data, measurements and quality control flags within the LSST footprint. +\\ +In addition, in the next decade a number of new surveys will expand these measurements from millions to tens of millions of spectra through facilities and programs such as LAMOST, 4MOST, DESI as well as coarse spectroscopic information via GRISM data from Euclid and eventually WFIRST, leading to a wealth of spectroscopic data which will be invaluable to LSST. +\\ +The community has two specific problems, i) collating this data and ii) ensuring quality control and standardization. Due to differing observing and analysis techniques not all spectroscopic measurements will be equal, and will depend on the resolution, signal-to-noise and precise software applied. +\\ +Within reason some effort should be made to both collate and standardize the data with some provision of a uniform quality control process. At the bare minimum this should result in a database which contains the flux and wavelength calibrated spectra, links or copies of original derived products, and crucially, measurements using a uniform set of software analysis tools (e.g., to produce consistent redshift and equivalent width measurements) with some coherent cross-survey quality control flags. +\\ +While this task sounds intimidating, this is exactly what has been achieved within the 200 square degrees of the Galaxy And Mass Assembly survey \citep{driver2011a,driver2016a,liske2015a} and an expansion of this process to the full LSST footprint is not unreasonable or impossible. However, this process needs to commence imminently if the database is to be in place for both LSST and the next generation of spectroscopic surveys. +\\ +As the majority of LSST's footprint covers the Southern Hemisphere, where many (but not all) large spectroscopic surveys have been instigated from Australia, this task represents a potential contribution from the Australian LSST contingent. +} +~\\ +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item A useable and searchable database of spectra with associated derived products +\item Derived products using standardized analysis codes to measure redshifts, equivalent widths etc +\item A strategy for ingesting additional datasets as they become available +\end{enumerate} +} +\end{task} + + + +\subsection{A Universal database of panchromatic imaging within the LSST footprint} +\tasktitle{AUX} +\begin{task} +\label{task:lsb:panchromatic} +\motivation{ +LSST will only cover a small portion of the electro-magnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life-cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available x-ray, UV, IR, and radio data. +\\ +While archives of these data exist independently, there is a dire need to establish a Universe database which federates these data in a coherent manner. One of the major concerns of such a database is the accurate multi-wavelength source identification and de-convolution in disparate data with wildly differing resolutions. For example, two closely separated sources in the LSST data may appear as a single source in lower resolution data. As such, significant errors will be made when simply table matching these photometric catalogues. +\\ +The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFITs; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to x-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse x-ray halos, discrete x-ray sources and extended radio lobes). +} +~\\ +\activities{ +Several activities are required: +\begin{enumerate} +\item Database to host imaging data from diverse sources, including astrometric alignment +\item Software to define aperture in a specified (LSST) band +\item Software to measure flux across panchromatic data taking into account original aperture definition, facility resolution, signal-to-noise limitations, and any physical priors +\item Tool to serve imaging and photometric data either for individual or sets of objects +\end{enumerate} +As galaxies emit radiation across the entire electromagnetic spectrum it is important to be able to trace this breadth of emission deriving from different astrophysical processes. This is particularly important in the LSST optical wavebands where anywhere from 0-90 per cent of the radiation might be attenuated by dust and re-radiated in the far-IR. +\\ +The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman- and the 4000Ang-breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. +\\ +Finally, x-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star-formation. Unification across the wavelength range requires federation of these very disparate datasets. This will become an increasingly common problem as we move into the ear of Big Data, and hence is worth centralizing prior to LSST operations. +\\ +Note a similar task has recently been achieved by the Galaxy And Mass Assembly team for a 200 square degree region \citep[see][and http://www/gama-survey.org/]{driver2016a} and can be extended to the full LSST footprint using similar techniques. +} +~\\ +\deliverables{Deliverables over the next few years from the activities described above include: +\begin{enumerate} +\item A database capable of serving image cutouts at any location over the LSST footprint and any wavelength (see http://cutout.icrar.org/psi.php for a similar database over the GAMA regions). This database will include +\begin{itemize} +\item x-ray maps from eROSITA +\item UV from GALEX +\item Optical from SkyMapper, DES, and Euclid +\item near-IR from VISTA and Euclid +\item mid-IR from WISE +\item far-IR from IRAS, Herschel, Spica +\item Radio continuum and HI from ASKAP(EMU,WALLABY,DINGO), MeerKAT (LADUMA, MIGHTEE, MeerKLASS) and eventually the SKA +\end{itemize} +\item Derived panchromatic photometry (on the fly or pre-processed) +\end{enumerate} +} +\end{task} + +\subsection{Tully-Fisher with LSST and SKA Pathfinders} +\tasktitle{AUX} +\begin{task} +\label{task:HI} +\motivation{ +% +How do galaxies evolve kinematically? The relation between stellar luminosity and rotation for disk galaxies is well known in the local Universe \citep[i.e., the Tully-Fisher or T-F relation, see][]{tully1977a,verheijen2001a} and +suspected to evolve as gas and stars form a disk within the dark matter gravitational potential. H\,{\sc{i}} extends throughout the stellar disk and well beyond, its kinematics tracing the galaxy's dark matter potential. +How the T-F relation evolved with cosmic time and redshift is being debated; whether the normalization or the slope or both evolve \cite[][]{weiner2006a,tiley2016a}? +A few major drawback for these studies into the evolution of the T-F are +(a) the kinematic information comes from H$\alpha$ optical data (sometimes redshifted into the infra-red, +which does not trace the full rotation curve, +(b) adaptive optics for these observations filters out the lower surface brightness features such as the rotating +disk \citep[see for a review ][]{glazebrook2013a}, and +(c) these measurements are made for intrinsically bright samples of galaxies. +However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}.\\ +% +The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b}, +detailed kinematics \citep{trachternach2008a}, extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. +The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}.\\ +% +For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), +an accurate photometry measurement, and a disk inclination. The last two critical measurements will be provided by LSST imaging (see XX and YY).\\ +There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST confirmed deep drilling fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments. \\ +Two other surveys represent the progressively wider/shallower H\,{\sc{i}} survey tiers with the ASKAP telescope \citep{johnston2007a}: DINGO, a survey of the GAMA fields \citep[][Meyer+ {\em in prep}]{driver2009a,duffy2012a,meyer2015a} and WALLABY, the Southern Sky H\,{\sc{i}} survey \citep[][Koribalski+ {\em in prep}]{duffy2012a}. + A benefit of the MeerKAT and ASKAP radio surveys is that they are conducted commensally: radio continuum and 21 cm emission line (H\,{\sc{i}}) are observed at the same time. The combination +The survey strategy from wide and shallow to single deep field (WALLABY-DINGO-MIGHTEE-LADUMA) is designed to beat down cosmic variance effectively \citep[see e.g.,][]{maddox2016a}. +} +~\\ +\activities{ +Several activities are necessary to compile kinematic evolution using a combination of H\,{\sc{i}} kinematics and LSST imaging: +\begin{enumerate} +\item Accurate photometry of extended objects in all LSST deep drilling fields. +\item accurate morphology of all galaxies with HI detections (to infer inclination). +\item Spectroscopic redshifts of all galaxies {\em not} detected in H\,{\sc{i}} for stacking purposes. +\end{enumerate} +} +~\\ +\deliverables{Deliverables over the next several years from the activities described above include the following: +\begin{enumerate} +\item Robust and accurate inclination estimates from morphological fits/models. +\item Accurate galaxy photometry from deep drilling stacks. +\item stacking code for H\,{\sc{i}} spectra. +\end{enumerate} +} +\end{task} + + + +\end{tasklist} +} diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 620ba9d..23a8198 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -1,6 +1,5 @@ - \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} - +{\justify The cosmological process of galaxy formation inextricably links the together, environment and large scale structure with the detailed properties of galaxy populations. The extent of this connection @@ -20,17 +19,17 @@ \subsection{Cluster/LSS Sample Emulator} clusters will be detected in given ranges of redshift, richness, mass, and other physical parameters. } +~\\ \activities{ LSST has advanced simulations of its 10-year Wide Fast Deep survey available from the Operations Simulator. The output databases can be analyzed to determine the depth LSST is expected to reach in its final -detection image at each sky location, and Awan et al.~2016 -(http://adsabs.harvard.edu/abs/2016ApJ...829…50A) turns these depths +detection image at each sky location, and \citet{awan2016a} turns these depths into predicted numbers of galaxies as a function of redshift and brightness. \\ To predict galaxy sample sizes as a function of physical parameters, -the ``raw'' predicted galaxy numbers from Awan et al.~(2016) will be +the ``raw'' predicted galaxy numbers from \citet{awan2016a} will be interfaced with semi-analytical models painted on large N-body simulations by Risa Wechsler and collaborators. This will extend the predictions to include observed properties of color, size, morphology @@ -43,9 +42,10 @@ \subsection{Cluster/LSS Sample Emulator} The properties will be based on simple scaling laws, with the user allowed freedom to choose the parameters of the scaling laws, including how they evolve. This will then be interfaced with the -``raw'' predicted galaxy numbers from Awan et al.~(2016), to determine +``raw'' predicted galaxy numbers from \citet{awan2016a}, to determine which of the groups and clusters should be detectable in the LSST data.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Create a public LSST Extragalactic Sample Emulator with a @@ -78,6 +78,7 @@ \subsection{Identifying and Characterizing Clusters} for cluster identification as well as incorporate complementary data from projects such as \emph{Euclid}, \emph{eROSITA}, etc. } +~\\ \activities{ Using existing imaging datasets and simulations, algorithms need to be developed and optimised to identify clusters at intermediate @@ -89,13 +90,13 @@ \subsection{Identifying and Characterizing Clusters} large volumes, so as to capture significant numbers ($\gg10,000$) of simulated galaxy clusters at high $z$. Potential algorithms to be tested include adaptations of RedMaPPer -(Rykoff et al.~2014) as well as methods that search for galaxy -overdensities over a range of scales (e.g.~Chiang et al.~2014; Wang et -al.~2016). +\citep{rykoff2014a} as well as methods that search for galaxy +overdensities over a range of scales \citep[e.g.,][]{chiang2014a,wang2016a}. In parallel, a comprehensive search for multiwavelength data (specifically IR and X-ray imaging) is needed to aid in the search for high-$z$ clusters and in the confirmation and characterization of systems at all redshifts.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item The primary product of this analysis will be improved cluster @@ -119,8 +120,8 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} properties. For example, satellite galaxies in the local Universe exhibit lower star formation rates, more bulge-dominated morphologies, as well as older and more metal-rich stellar populations when compared -to isolated (or ``field'') systems of equivalent stellar mass (Baldry -et al.~2006; Cooper et al.~2010; Pasquali et al.~2010). +to isolated (or ``field'') systems of equivalent stellar mass +\citep{baldry2006a,cooper2010a,pasquali2010a}. Unlike spectroscopic surveys, LSST will lack the precise line-of-sight velocity measurements to robustly identify satellite galaxies in lower-mass groups, where the expected photo-$z$ precision will greatly @@ -134,6 +135,7 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} to host halo mass, etc.), so as to enable analyses of environment's role in galaxy evolution with LSST. } +~\\ \activities{ Using mock galaxy catalogs created via semi-analytic techniques, we will compare different tracers of local @@ -145,6 +147,7 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} suited to LSST. For each measure, we will examine the impact of increasing survey depth and photo-$z$ precision over the course of the survey.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item With an improved understanding of the @@ -173,6 +176,7 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} the underlying dark matter is also essential for optimally utilizing the large-scale distribution of galaxies as a cosmological probe. } +~\\ \activities{ Preparatory work will be along two main tracks. The first one will be support work to define and characterize @@ -199,6 +203,7 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} This endeavor overlaps with DESC-LSS working group efforts, and requires cooperation of the DESC-PhotoZ working group and the Galaxies Theory and Mock Catalogs working group.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Ensuring LSST galaxy pipelines include all the necessary @@ -232,6 +237,7 @@ \subsection{Disentangling Complicated Lines of Sight} identification of star-forming galaxies in clusters and their infall regions to probe the physics of quenching of star formation. } +~\\ \activities{ The LSST will deliver the most information rich dataset ever in relation to the masses and internal structures of clusters and their @@ -258,6 +264,7 @@ \subsection{Disentangling Complicated Lines of Sight} of cluster and groups, environmental measures, cluster detection, complementary data, and also work in the DESC Clusters WG via $p(z)$ of background galaxies.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item A new cluster-specific photometric redshift algorithm that can be @@ -288,13 +295,13 @@ \subsection{Forward Modeling LSST Clusters and Groups} magnitude less stringent here than in DESC. Arguably, $\sim10\%$ control of systematic biases in weak-lensing measurements of low redshift clusters ($\gtrsim2\times10^{14}M_\odot$) has already been -achieved (Okabe et al. 2013; Applegate et al. 2014; Hoekstra et -al. 2015; Okabe \& Smith 2016). Therefore in this Science +achieved \citep{okabe2013a,applegate2014a,hoekstra2015a,okabe2016a}. +Therefore in this Science Collaboration we have the challenge of maintaining that level of control down to smaller masses and out to higher redshifts. \\ A growing number of studies are adopting an approach of forward -modelling the cluster population simultaneously with the cosmological +modeling the cluster population simultaneously with the cosmological model to obtain constraints on scaling relations and cosmological parameters. Here, the idea is to borrow this same approach, but adopt a fixed cosmological model, broaden the mass range of systems @@ -306,6 +313,7 @@ \subsection{Forward Modeling LSST Clusters and Groups} to constrain the physics of galaxies and hot gas in groups and clusters, tied directly to the halo mass function via weak-lensing. } +~\\ \activities{ Key activities include: % @@ -317,6 +325,7 @@ \subsection{Forward Modeling LSST Clusters and Groups} \item Combine this development work other work packages within Galaxies and DESC \end{itemize} } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Bayesian inference code to simultaneously model cluster shear @@ -330,3 +339,4 @@ \subsection{Forward Modeling LSST Clusters and Groups} \end{tasklist} +} \ No newline at end of file diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index c7f0545..11c4a28 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -1,6 +1,11 @@ \section{Deep Drilling Fields}\label{sec:tasks:ddf} -The LSST Drilling-Fields (DDF) are areas that have a higher cadence and deeper observations than the Deep-Wide survey. Many of the details of the observing strategy have yet to be finalized. Four Deep-Drilling fields have been selected. Whether to include any others will be part of a complex trade involving other special projects that depart from the Deep-Wide survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy are all still under study, and the Project needs input from the science collaborations to inform these decisions. The tasks outlined in this section are intended to help optimize the LSST observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy-evolution science. +{\justify +The LSST Deep Drilling Fields (DDF) will have a higher cadence and deeper observations than the Wide-Fast-Deep (WFD) survey. +Many of the details of the observing strategy have yet to be finalized, but four Deep-Drilling fields have been selected. +Whether to include any others will be part of a complex trade involving other special projects that depart from the WFD survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy all remain under study at the current time. +The tasks outlined in this section will help optimize the LSST DDF +observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy evolution science. \begin{tasklist}{DDF} @@ -9,42 +14,61 @@ \subsection{Coordinating Ancillary Observations} \begin{task} \label{task:ddf:ancillary_obs} \motivation{ -It is crucial that the LSST deep-drilling fields be supported by observations from other facilities. While the LSST data by themselves will be unique in having deep and accurate photometry, good image quality, and time-series sampling, the amount of information in six bands of relatively broad optical imaging is quite limited. Estimates of photometric redshifts and stellar-population parameters (e.g. mass and star-formation rate) are greatly improved with long-wavelength data. Combining these quantities with information on dust and gas from far-IR, mm and radio observations allows one to build and test models that track the flow of gas in and out of galaxies. Deep and dense spectroscopy is essential both providing precise redshifts, calibrating photometric redshifts, and measuring physical properties of galaxies. Properly supported by this additional data, the LSST DDFs will become the most valuable areas of the sky for galaxy-evolution science. The central regions of the four fields already selected are already in this category; the main challenge is filling out the much larger area subtended by the LSST field of view. +Galaxy evolution science performed using LSST DDF data crucially requires supporting observations from other facilities. +While the LSST data uniquely provides deep and accurate photometry, good image quality, and time-series sampling, the amount of information in six bands of relatively broad optical imaging +remains quite limited. Estimates of photometric redshifts and stellar-population parameters (e.g., mass and star-formation rate) greatly improve with the addition of longer-wavelength data. +Combining these quantities with information on dust and gas from far-IR, millimeter, and radio observations allows one to build and test models that track the flow of gas in and out of galaxies. +Deep and dense spectroscopy provides precise redshifts, calibrates photometric redshifts, and measures important physical properties of galaxies. +Properly supported by this additional data, the LSST DDFs will become the most valuable areas of the sky for galaxy evolution science. +The central regions of the four fields already selected already enjoy multiwavelength coverage; +the main challenge is filling out the much larger area subtended by the LSST field of view. } +~\\ \activities{ -The major challenge in supporting the Deep Drilling Fields is the huge investment of telescope time. There is a need for coordination across facilities and collaborations to make the most efficient use of this time. Coordination is certainly happening somewhat haphazardly, but there has not to date been a dedicated effort to get all the potential stakeholders involved in developing a coherent plan. The LSST science collaborations can and should be taking the lead here. The SERVS program to observe the already-designated DDFs with Spitzer is a good example of where this has happened (Manduit et al. 2012), but there is much more to be done. Activities include: +The major challenge in supporting the LSST DDFs is the huge investment of telescope time. +Providing supporting multiwavelength data sets requires +coordination across facilities and collaborations to make the most efficient use of telescope time. Current coordination occurs somewhat haphazardly, but there has not to date been a dedicated effort to organize potential stakeholders involved in developing a coherent plan. The LSST Science Collaborations can and should take the lead here. +The SERVS program to observe the already-designated DDFs with Spitzer provides a good example of where coordination can prove fruitful \citep{mauduit2012a}, but substantial +further work remains. Activities include: \begin{itemize} -\item Workshops to discuss LSST DDF coordination -\item Proposals for major surveys or even new instrumentation to provide supporting data -\item Executing those supporting programs -\item Working to integrate the data from those programs with the LSST data -\item Working to enable DDF support through policies and strategic planning at major observatories +\item Workshops to discuss LSST DDF coordination. +\item Proposals for major surveys or even new instrumentation to provide supporting data. +\item Execution of supporting programs. +\item Work to integrate the data from supporting programs with the LSST data. +\item Work to enable DDF support through policies and strategic planning at major observatories. \end{itemize} } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Workshops on LSST DDF supporting observations -\item Annually updated roadmap of supporting observations (conceived, planned or executed) -\item Public Release of data from supporting observations -\item Level 3 software to enable use of LSST data with supporting data +\item Workshops on LSST DDF supporting observations. +\item Annually updated roadmap of supporting observations (conceived, planned, or executed). +\item Public Release of data from supporting observations. +\item Level 3 software to enable use of LSST data with supporting data. \end{enumerate} } \end{task} -\subsection{Observing Strategy “Cadence”} -\tasktitle{Observing Strategy “Cadence”} +\subsection{Observing Strategy Cadence} +\tasktitle{Observing Strategy Cadence} \begin{task} \label{task:ddf:cadence} \motivation{ -The LSST DDF observing strategy will need to serve diverse needs. For galaxy-evolution science, the time series aspect of the observation is less important than the depth, image quality, and mix of filters. Optimizing the observing strategy (including timing) is influenced by non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data. For example, for many science goals, completing the observations of one DDF to the final 10-year depth in the first year could be very beneficial. But there is work to be done to justify that, select the field, and find synergies with other science areas (e.g. DESC, AGN, transients). +The LSST DDF observing strategy will need to serve diverse needs. For galaxy evolution science, the time series aspect of the observation may prove less important than the depth, image quality, and mix of filters. +Non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data will influence the observing strategy optimization. +For example, for many science goals completing the observations of one DDF to the final 10-year depth in the first year could prove very beneficial. +But justifying this investment will require work, including the selection of a suitable DDF +and the identification of synergies with other LSST science areas (e.g., DESC, AGN, transients). } +~\\ \activities{ -The LSST observing strategy is optimized using the Operations Simulator (OpsSim). The Project works with the community to develop both strawman observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpsSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} +The LSST observing strategy is optimized using the Operations Simulator (OpSim). The Project works with the community to develop both baseline observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Figures of Merit via MAF for use by OpSim -\item Proposed observing strategies for DDFs with rationale -\item Proposing and/or helping to assess selection of additional DDFs +\item Figures of Merit via MAF for use by OpSim. +\item Proposed observing strategies for DDFs with rationale. +\item Proposing and/or helping to assess selection of additional DDFs. \end{enumerate} } \end{task} @@ -54,23 +78,35 @@ \subsection{Data Processing} \begin{task} \label{task:ddf:data_processing} \motivation{ -Getting the most out of the DDFs may require data processing beyond that required for the Deep-Wide Survey. There are a variety of issues that ought to be considered in trying to optimize the science output. These include different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features , deblending overlapping objects, or estimating photometric redshifts. The fields are small enough that it is conceivable to process or reprocess them making use of data from supporting observations. It will clearly be advantageous to have one “official” LSST-released catalog, but defining such a catalog to support a very broad range of science is challenging. This does not preclude having additional special-purpose catalogs, but it is clearly beneficial to the advancement of extragalactic research to have a high-quality official catalog that has “buy in” from the LSST Science Collaborations. This requires time and effort both in the Project and in the Collaborations. +Getting the most out of the DDFs may require data processing beyond that required for the WFD Survey. A variety of issues will need consideration in trying to optimize the science output, +including different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features, deblending overlapping objects, or estimating photometric redshifts. Reprocessing the DDF data while utilizing +supporting observations may prove feasible. +While there exists a clear advantage to issue one ``official'' LSST-released catalog at Level 2, +defining such a catalog to support a very broad range of science remains challenging. +Generating high-quality Level 3 catalogs to advance extragalactic research that include external +data will require time and effort from the LSST Science Collaborations. } +~\\ \activities{ -A major activity here is to identify the most important DDF-specific science drivers and identify any processing requirements that are distinct from the Deep-Wide survey. This ought to be coordinated with the Project and the other Science Collaborations to provide a coherent set of specifications and priorities. +Identify the most important DDF-specific science drivers and any processing requirements distinct from the WFD survey. Coordinate with the Project and Science Collaborations to provide a coherent set of specifications and priorities for data processing. \\ -Another major activity is to develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection) This may stress the inputs to the image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low-surface brightness features. Use of the supporting data sets in level 2 or level 3 processing requires careful thought. For example, source identification and photometry can be improved using pixel-level information for either Euclid or WFIRST. However, this will not be available for all the DDFs and is not in the baseline plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The collaborations need to work with the various projects to identify a clear path forward.} +Develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection). This activity may stress the inputs to the image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low-surface brightness features. Use of the supporting data sets in Level 2 or 3 processing requires careful thought. For example, +pixel-level information from either Euclid or WFIRST +may improve source identification and photometry. +However, these ancillary data sets will not be available for all the DDFs and does not currently +reflect the baseline observing plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The Science Collaborations need to work with the various projects to identify a clear path forward.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Science drivers and input to the development of level 2 processing of the DDFs. -\item Specifications for galaxy-evolution oriented level-3 DDF processing -\item Specifications for data-processing using supporting data from other facilities -\item Simulations tailored to the DDFs -\item Level 3 processing code +\item Science drivers and input to the development of Level 2 processing of the DDFs. +\item Specifications for galaxy-evolution oriented Level 3 DDF processing. +\item Specifications for data-processing using supporting data from other facilities. +\item Simulations tailored to the DDFs. +\item Level 3 data processing code, or augmentations to the LSST Level 2 pipeline. \end{enumerate} } \end{task} \end{tasklist} - \ No newline at end of file +} diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index de49c68..96a8964 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -1,45 +1,31 @@ % LSST Extragalactic Roadmap % Chapter: task_lists % Section: galaxies -% First draft by \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} - -The LSST design, and to a certain extent the design of the data-management -system, is optimized to carry out the core science mission. For measurements -of dark-energy, that generally means treating galaxies as ``tracer particles'' -- -using statistical measures of ellipticity and position provide statistical +{\justify +The LSST Project optimized the observatory and data management design +to execute successfully and efficiently the core LSST science mission. +For measurements +of dark energy, that optimization generally means treating galaxies as ``tracer particles'' -- + using statistical measures of ellipticity and position to provide statistical constraints on large-scale structure and cosmic geometry. While many of the -DESC tasks are directly relevant to studying galaxy evolution, they are +DESC tasks relate directly to studying galaxy evolution, they remain incomplete. In particular, studies of galaxy evolution require more attention to -optimizing multi-wavelength supporting data, different kinds of spectroscopy, different -kinds of simulations and theoretical support, and greater attention to detection +optimizing multi-wavelength supporting data, obtaining different kinds of spectroscopy, +performing different +kinds of simulations and other theoretical support, and a greater attention to +the detection and characterization of low-surface brightness features or unusual morphologies. -The task list presented here highlights the preparation work needed in the next 3-4 -years. Of primary importance are tasks that might influence the detailed survey -design or the algorithms used in the DM to construct catalogs. These are the most -urgent. Also included are activities that can be reasonably independent of the -LSST survey design and DM optimization, but which will ensure good support for +The task list presented here highlights the preparatory research needed in the next $\sim3-4$ +years. +Tasks of primary importance and particular urgency include those that might influence the detailed survey +design or the algorithms used in the LSST Software Stack to construct catalogs. +Other critical tasks remain reasonably independent of the +LSST survey design and data pipeline optimization, but will help ensure good support for LSST galaxy studies. -%\begin{tasklist}{G} -%\subsection{Example Task List} -%\tasktitle{Example Task List} -%\begin{task} -%\label{task:label_for_this_task} -%\motivation{Put Science Motivation Here} -%\activities{Described Activities Here} -%\deliverables{ -% Deliverables over the next several years from the activities described above include the following: -% \begin{enumerate} -% \item a deliverable -% \item another deliverable -% \end{enumerate} -%} -%\end{task} -%\end{tasklist} - \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} \begin{tasklist}{G-TAS} @@ -49,143 +35,159 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga \begin{task} \label{task:gal:lsb} \motivation{ -A huge benefit of LSST relative to prior large-area surveys will be its ability to detect -low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and -other features associated with past and ongoing mergers, it includes intra-cluster and -intra-group light, and it includes relatively nearby, extended low-surface-brightness galaxies. -Prior to LSST, typical studies of the low-surface-brightness universe have focused -on relatively small samples, often selected by criteria that are difficult to quantify -or reproduce in theoretical models. Measurements of the LSB features themselves themselves -are challenging, often requiring hand-tuning and interactive scientific judgment. This is -important for accurately quantifying what we observe, but such interactive tuning -of the measurements (a) is not something that can be applied on the LSST scale and (b) -is difficult to apply to theoretical models. For LSST it is crucial that we automate -the detection and characterization of LSB features, at least to the point where samples -for further study can be selected via database queries, and where the completeness of -samples returned from such queries can be quantified. +Important scientific benefits of the LSST dataset +relative to prior large-area surveys include its ability to detect +low-surface-brightness (LSB) features associated with galaxies. +This ability includes the identification of tidal streams and +other features associated with past and ongoing mergers, intra-cluster and +intra-group light, and relatively nearby, extended low-surface-brightness galaxies. +Prior to LSST, typical studies of the low-surface-brightness universe focused +on relatively small samples, often selected by criteria that prove difficult to quantify +or reproduce in theoretical models. Measurements of the LSB features themselves +can challenge pipelines and subsequent analysis, +and often require both hand-tuning and interactive scientific judgment. This manual +attention serves to help quantify accurately what we observe, but such +interacting tuning of the measurements does not scale to the LSST dataset and +can prove difficult to apply to theoretical models. +For LSST, we must automate the detection and characterization of LSB features, +at least to the point where we can select samples +for further study via database queries and quantify the completeness or +other statistical properties of +those retrieved samples. } - +~\\ \activities{ -Several activities are of crucial importance: (1) simulating realistic LSB features, (2) -using the simulations to optimize detection and measurement, (3) ensuring that LSST -level-2 processing strategies and observing strategies are at least cognizant -of needs of LSB science and (4) developing a strategy for finding and measuring LSB features through -some combination of level 2 measurements, database queries, and level 3 processing.\\ -It is important to insert realistic low-surface-brightness -features into LSST simulated images and try to extract and measure them, exploring -different techniques or algorithms for doing the detection and measurement. Because the LSB objects -are sparse on the sky, making realistic LSST sky images is probably not the most efficient -way to accomplish this; more targeted simulations with a higher density of -LSB objects are needed. The simulated observations need to be realistic in their -treatment of scattered light, particularly scattering from bright stars which -may or may not be in the actual field of view of the telescope. -Scattering from bright stars is likely to be the primary source of contamination -when searching for extended LSB features. Ideally, the LSST scattered-light model, -tuned by repeated observations, will be sufficiently good that these contaminants -can be removed or at least flagged at level 2. Defining the metrics for ``sufficiently good,'' -based on analysis of simulations, is an important activity that needs early work to +Several crucial activities include: (1) simulating realistic LSB features, (2) +using the simulations to optimize detection and measurement, (3) informing LSST +Level 2 processing and observing strategies about the needs of LSB science, +and (4) developing a strategy for finding and measuring LSB features through +some combination of Level 2 measurements, database queries, and Level 3 processing.\\ +The instertion of realistic LSB features into LSST simulated images will provide +``data challenges'' to test methods for their extraction and measurement, allowing +for the exploration of different techniques or algorithms for performing LSB +feature detection and characterization. +Because the LSB objects sparsely populate the sky, +making realistic LSST sky images will probably prove inefficient. +More targeted simulations with a higher density of LSB object will better +enable the efficient exploration of LSB feature detection and analysis. +Simulated observations must realistically treat scattered light, particularly +scattering from bright stars that may or may not fall in the actual field of +view of the telescope. Scattering from bright stars will likely contribute the +primary source of contamination when searching for extended LSB features. +Ideally, the LSST scattered-light model, +tuned by repeated observations, will perform sufficiently well and enable the removal +or flagging of these contaminants at Level 2. +Defining the associated performance metrics for +based on analysis of simulation represents an important activity that needs early work to help inform LSST development. Including Galactic cirrus in the simulations is important for very large-scale LSB features. Including a cirrus model as part of the LSST background -estimation is worth considering, but it is unclear yet whether the science benefit -can justify the extra effort. \\ +estimation is worth considering, but the science benefit gained from the +additional effort remains unclear.\\ Because the LSST source extraction is primarily -optimized for finding faint, barely-resolved galaxies, it is going to be challenging to -optimize simultaneously for finding large LSB structures and cataloging them as -one entity in the database. For very large structures, analysis of the LSST ``sky background'' -map, might be the most productive approach. We need to work with the LSST project -to make sure the background map is stored in a useful form, and that background +optimized for finding faint, barely-resolved galaxies, +simultaneously finding large LSB structures and cataloging them as +one entity in the LSST database may pose challenges. +For very large structures, analysis of the LSST ``sky background'' +map might constitute the most productive approach. +We need to work with the LSST Project +to make sure the Software Stack stores the background map in a useful form, and that background measurements from repeated observations can be combined to separate the fluctuating -foreground and scattered light from the astrophysically interesting signal from extended -LSB structures. Then, we need strategies for measuring these background maps, characterizing -structures, and developing value-added catalogs to supplement the level 2 database.\\ -For smaller structures, it is likely that the database will contain pieces -of the structure, either as portions of a hierachical -family of deblended objects, or cataloged as separate objects. Therefore, we need to +foreground and scattered light from the astrophysically interesting signal owing to extended +LSB structures. +Then, we need strategies for measuring these background maps, characterizing +structures, and developing value-added catalogs to supplement the Level 2 database.\\ +For smaller structures, the database likely will contain pieces +of the structure, either as portions of a hierarchical +family of deblended objects or as separate catalog entries. Therefore, we need to develop strategies for querying the database to find such structures and either extract the appropriate data for customized processing, or develop ways to put back together the separate entries in the database. A possible value-added catalog, for example, from -the galaxies collaboration might be an extra set of fields for the database to indicate -which separate objects are probably part of the same physical entity. This would -be sparsely populated in the first year or two of LSST, but by the end of the survey -could be a useful resource for a wide variety of investigations. +the Galaxies Science Collaboration might include an extra set of fields for the database to indicate +which separate objects likely probably originate from the same physical entity. These additional fields would +remain sparsely populated in the first year or two of LSST, but by the end of the survey +the relational connections between deblended objects may prove a +useful resource for a wide variety of investigations. } - +~\\ \deliverables{ Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item realistic inputs of LSB galaxies or LSB features for the LSST image simulations; -\item custom simulations; -\item algorithms for finding and measuring LSB features; -\item input to the Project on scattered-light mitigation and modeling strategies; -\item input to the project on photometric and morphological parameters to measure/store at level 2; -\item query strategies and sample queries for finding LSB structures; and -\item a baseline concept for a value-added database of LSB structures +\item Creations of realistic inputs of LSB galaxies or LSB features for the LSST image simulations. +\item Development of algorithms for finding and measuring LSB features. +\item Input to the Project on scattered-light mitigation and modeling strategies. +\item Input to the Project on photometric and morphological parameters to measure/store at Level 2. +\item Identification of query strategies and sample queries for finding LSB structures. +\item Engineering of a baseline concept for a value-added database of LSB structures. \end{enumerate} } \end{task} -\subsection{Techniques for identifying and deblending overlapping galaxies} -\tasktitle{Techniques for identifying and deblending overlapping galaxies} +\subsection{Techniques for Identifying and Deblending Overlapping Galaxies} +\tasktitle{Techniques for Identifying and Deblending Overlapping Galaxies} \begin{task} \label{task:gal:deblending} \motivation{ -The Level 2 data products are the most relevant starting point +The Level 2 data products provide the most relevant starting point for galaxy-evolution science. In the LSST nomenclature, {\tt Objects} represent astrophysical entities (stars, galaxies, quasars, etc.), while {\tt Sources} represent their single-epoch observations. -The master list of Objects in Level 2 will be generated by associating +The Software Stack will generate the master list of Objects in Level 2 +by associating and deblending the list of single-epoch source detections and the -lists of sources detected on coadds. The exact strategies for doing -this are still under active development by the LSST project, and -engagement with the science community is essential. While each -data release will have unique object IDs, it will be a huge impediment -for LSST science if the first few generations of catalogs turn out -severely the limit the science that can be done via database queries. \\ -For galaxies science, the issue of deblending is of critical importance. +lists of sources detected on co-adds. The exact strategies for +performing this task still remain under active development by the LSST Project, and +engagement with the science community will prove essential. While each +data release will provide unique object IDs, if the first few +generations of catalogs limit the science performed through data base +queries the consequences may impede early LSST science.\\ +For galaxies science, the issue of deblending holds critical importance. For example, searches for high-redshift galaxies via color selection or photometric redshifts involve model or template spectra that make -the prior assumption that the object in question is a single object at -one redshift, not a blend of two objects at two different redshifts. -Therefore to get a reliable estimate of the evolution of classes of galaxies -over redshift, we need to (a) have reasonably clean catalogs to start with -and (b) be able to model the effects of blending on the sample selection -and derivation of redshift and other parameters. This is critical -not just for galaxy-evolution science, but for lensing and large-scale -structure studies. This is just one example. Another is the evolution +the prior assumption that each analyzed object does not consist of a +blend of two objects at two different redshifts. +Therefore, to get a reliable estimate of the evolution of classes of galaxies +over redshift we need to (a) create reasonably clean catalogs to start with +and (b) model the effects of blending on the sample selection +and derivation of redshift and other parameters. These issues critically +affect not just galaxy evolution science, but also lensing and large-scale +structure studies. Another example involves the evolution of galaxy morphologies, where the effects of blending and confusion -may well be the dominant source of uncertainty. \\ -The plan for the level-2 catalogs is that sources are hierarchically -deblended and that this hierarchy is maintained in the catalog. -Scientifically important decisions are still to be made about whether +may well dominate measurement uncertainties. \\ +For the Level 2 catalogs, the planned approach involves using the +Software Stack to deblend sources hierarchically and then +maintain this hierarchy in the catalog. +Scientifically important decisions still remain about whether and how to use color information in the deblending, and how to divide -the flux between overlapping components. Even if the Project is doing -the development work, engagement with the community is important for -developing tests and figures of merit to optimize the science return. +the flux between overlapping components. Even if the Project performs +the development work, engagement with the community can generate important +tests and figures of merit to optimize the science return. } +~\\ \activities{ Preparations for LSST in this area involve working both with simulations -and real data. The current LSST image simulations already have realistic source densities, +and real data. The current LSST image simulations already utilize realistic source densities, redshift distributions, sizes, and color distributions. However, the -input galaxies do not have realistic morphologies. At least some simulations +input galaxies do not display realistic morphologies. At least some simulations with realistic morphologies are needed, especially for the Deep Drilling Fields. -Inputs should come both from hydrodynamical simulations (where ``truth'' is known), +Inputs should come from hydrodynamical simulations, {\it Hubble} images, and images from precursor surveys such as CFHTLS, DES and HyperSuprimeCam. -The science collaborations should help provide and vet inputs. \\ -More challenging is to come up with techniques and algorithms to improve the +The Science Collaborations should help provide and vet inputs. \\ +More challenging activities involve developing techniques and algorithms to improve the deblending. When two galaxies at different redshifts overlap, using observations from all the LSST filters and perhaps even EUCLID and WFIRST might -help to disentangle them. Some attempts have been made over the past few years -to incorporate color information into the deblending algorithm, but this needs -much more attention, not only for developing and testing algorithms, but for +help to disentangle them. Some attempts over the past few years have +incorporated color gradient information into the deblending algorithm, but this approach needs +much more attention for developing and testing algorithms, and deciding on figures-of-merit for their performance. } +~\\ \deliverables{ Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item providing realistic galaxy image inputs to the ImSim team; -\item developing tests and figures of merit to quantify the effects on several science objectives; -\item assessing the current baseline plan for level-2 deblending and for parameter estimation for blended objects; and -\item developing prototype implementations of deblending algorithms that take advantage of the LSST color information. +\item Production of realistic galaxy image inputs to the ImSim team. +\item Development of tests and figures of merit to quantify the effects on several science objectives; +\item Assessment of the current baseline plan for Level 2 deblending and for parameter estimation for blended objects. +\item Development of prototype implementations of deblending algorithms that take advantage of the LSST color information. \end{enumerate} } \end{task} @@ -198,48 +200,106 @@ \subsection{Optimizing Galaxy Morphology Measurements} \begin{task} \label{task:gal:morphology} \motivation{ -Measurements of galaxy morphologies are an important tool for constraining models -of galaxy evolution. While fairly simple measures of galaxy ellipticity and position -angles may be sufficient for the Dark Energy science goals, other kinds of -measurements are needed for galaxy-evolution science. The ``multifit'' approach of -fitting simple parametric models to galaxy profiles has been the baseline plan. -This will be useful but insufficient. For well-resolved galaxies it is desirable -to have separate measures of bulge and disk, and spiral-arm structure, measures of -concentration, asymmetry, and clumpiness. These ought to be measured as part of -the level 2 processing, to enable database queries to extract subclasses of galaxies. -Both parametric and non-parametric measures are desirable. -While there will no doubt be optimization in level 3 processing, it is important -to have enough information in the level 2 output products to pick reasonable subsets -of galaxies. +Morphology encodes key signatures of the formation histories of galaxies, and measurements of galaxy morphology are an important tool for constraining models of galaxy evolution. While simple measures of galaxy ellipticity and position +angles may be sufficient for the Dark Energy science goals, more sophisticated measurements of morphology are needed for galaxy-evolution science. While the ``multifit'' approach of fitting simple parametric models to galaxy profiles is useful to zeroth order, this is insufficient for the detailed morphological information that will be required for much of the galaxy science that is planned using LSST. +\\ +For well-resolved galaxies the baseline requirement is to have separate measures of bulge and disk, and spiral-arm structure, measures of concentration, asymmetry, and clumpiness. These ought to be measured as part of the level 2 processing, to enable database queries to extract subclasses of galaxies. Both parametric and non-parametric measures are desirable. While there will no doubt be optimization in level 3 processing, it is important to have enough information in the level 2 output products to pick reasonable subsets of galaxies. +\\ +More importantly, while the traditional parametrisations of morphology described above will be useful, it is essential that new, more powerful methods of measuring galaxy morphology are developed and implemented, in order to leverage the exquisite volume and depth of LSST data. In this regard fast, unsupervised machine-learning techniques \citep[e.g.][]{hocking2015a}, which are able to efficiently separate LSST galaxy populations into different morphological classes, are particularly relevant and powerful (supervised techniques may not be as well-suited to LSST, since the sheer volume of data expected, coupled with the speed with which datasets will change in depth, makes producing training sets, via e.g. visual inspection, prohibitively time consuming. } -\activities{The preparation work, therefore, focuses on defining measures to enable -these queries. Two aspects of LSST data make this a significant research project: -the fact that LSST provides multi-band data with a high degree of uniformity, and the -fact that the individual observations will have varying point-spread functions. -The former offers the opportunity to use much more information than has been -generally possible. The latter means that it will take some effort to optimize and -calibrate the traditional non-parametric measure of morphology (e.g. the CAS, GINI and M20 parameters), -develop new LSST-optimized parameters, and optimize their computation to avoid -taxing the level-2 pipeline.\\ -Given the very large data set and the uncertainty in how to use specific morphological -parameters to choose galaxies in certain physical classes (e.g. different merger -stages or stages of disk growth), it is important to have extensive -training both from hydrodynamical simulations -with dust (where physical truth is known, even if the models are imperfect) and -from observations where kinematics or other information provide a good -understanding of the physical nature of the object. These training sets ought to -be classified by humans (still the gold-standard for image classification) and via -machine-learning techniques applied to the morphological measurements. A series -of ``classification challenges'' prior to the LSST survey could help to refine the techniques. +~\\ +\activities{The preparation work will focus on defining morphological parameters and developing unsupervised machine-learning algorithms to enable users to easily query galaxy morphologies from the LSST database. Two aspects of LSST data make this a significant research project: the fact that LSST provides multi-band data with a high degree of uniformity, and the fact that the individual observations will have varying point-spread functions. The former offers the opportunity to use much more information than has been generally possible. The latter means that it will take some effort to optimize and calibrate the traditional non-parametric measures of morphology (e.g. the CAS, GINI and M20 parameters), develop new LSST-optimized parameters, and tune machine-learning algorithms to operate on this type of data. +\\ +Given the very large data set expected from LSST, which will change on short timescales in terms of depth, morphological parameters (e.g. CAS) will likely need to be calibrated on realistic data from hydro-dynamical simulations in cosmological volumes, possibly augmented by training sets classified by humans. Similarly, unsupervised machine-learning algorithms will have to be developed and implemented using a mixture of realistic simulations and precursor datasets, such as the Hyper Suprime Cam Survey. A series of ``classification challenges'' prior to the LSST survey could help to refine these techniques. } +~\\ \deliverables{ Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item providing realistic galaxy image inputs for classification tests to the ImSim team; -\item human classification of the images; -\item machine-learning algorithms to be tested and developed into suitable SQL queries; -\item developing a menu of candidate morphological measurements for level 2 and level 3 processing; and -\item developing tests and figures of merit to quantify the effects on several science objectives. +\item Providing realistic galaxy image inputs from hydro-dynamical simulations and precursor datasets for classification tests +\item Human classification of image subsets for calibration of morphologial parameters +\item Unsupervised machine-learning algorithms that will provide fast morphological classification of LSST datasets, developed using and implemented on precursor datasets such as the Hyper Suprime Cam Survey +\end{enumerate} +} +\end{task} + + +\subsection{Galaxy structural parameters} +\tasktitle{Galaxy structural parameters} + +\begin{task} +\label{task:gal:struc_param} +\motivation{ +The image quality provided by the camera (0.2"/pixel), the wide field coverage (9.6deg2) over 18.000 deg2 in optical and NIR (ugrizy bands), promise to provide unique data to cast light on the evolution of the internal structure of galaxies and galaxy clusters and their dark matter haloes, up to redshift well beyond unity. The full depth of the Deep-Wide-Fast (r $\sim$27.5 coadded) will allow us to identify dwarf galaxies at z~0.5, and up to $M_*+2$ galaxies in clusters and field at z~1.5, and reach enough SNR to study the structural parameters (size, Sérsic index, ellipticity etc.) of $M_*$ galaxies at z~1.2 (for seeing<0.5"). The evolution of the structural parameters, especially the size, Sersic index and B/D over billion of galaxies will allow to correlate them with mass, colours and other intrinsic properties at different epochs and clarify the mechanisms that drive the galaxy assembly and transformation. Other science directly connected is the strong lensing (in model subtracted images) and galaxy dark matter content and the dark-to-luminous mass connection in galaxies. +} +~\\ +\activities{ Most of the preparatory work will consist on testing parametric methods for seeing convolved 2D fitting of the galaxy light distribution both on precursor surveys (e.g. Subaru or KiDS) and on simulated LSST images. The aim is to provide the collaboration viable tools for automatic image masking, catalogue extraction, source classification and 2D galaxy fitting. A specific aspect of this task is to optimise tool performances in order to guarantee big data analysis in reasonable time (e.g. 100 millions of LSST galaxies in all bands on a single week). The surface brightness profile of galaxies in different bands will finally generate a catalog of all relevant structural parameters via Level 3 products. +} +~\\ +\deliverables{From the activities described above we expect to provide the following deliverables: +\begin{enumerate} +\item benchmarks for different existing and newly developed tools for galaxy surface photometry; +\item automatic masks (star haloes and spikes, reflections etc.) and related procedures; +\item catalog of structural parameters in different bands; +\item machine learning algorithm for the identification of faint substructures in model subtracted images (e.g. streams, merging, rings, strong lensing arcs, etc.) +\end{enumerate} +} +\end{task} + +\bigskip +\subsection{Optimizing galaxy mass profile measurement} +\tasktitle{Optimizing galaxy mass profile measurement} +% foreground lens galaxy sample selection +% completeness +% shear simulations +% galaxy-mass correlation function +% sample cuts: type, environment, color, redshift +% correlations of mass profile with optical properties +\begin{task} +\label{task:gal:mass} +\motivation{Galaxies form and evolve dynamically via the gravitational influence +of the underlying dark matter structure. This non-baryonic dark mass is intimately +involved in the evolution of the baryonic component which ultimately generates the +stellar component visible in the optical. LSST can uniquely probe both of these +tracers for hundreds of millions of galaxies over a range of look-back time. +This provides an opportunity to probe the detailed relation between mass and light structure +evolution for the first time. This has been attempted before in a limited way using LSST +precursor surveys. Using 300,000 lens galaxies in the Deep Lens Survey, \citep{choi2012a} +studied the mass profile of galaxies in three luminosity bins out to several Mpc. Using +a similar number of lens galaxies in the COSMOS ACS data,\citep{leauthaud2012a} derived +constraints on the evolution of the stellar-to-dark matter connection in the context of halo models. +LSST will provide a billion lens galaxies and more accurate photometric redshifts . +} +~\\ +\activities{ +The question to be addressed is: how far down the galaxy mass function can +we expect to detect the mass profile in selected large samples of galaxies. One must start +with a model of the mass distribution in galaxies. This will +involve use of existing n-body galaxy formation simulations and resulting analytic models; +foreground lens galaxy sample selection; the weak lens shear simulations of LSST observing over +a large area (1000 sq.deg) containing a large sample of lens galaxies; stacked simulations of +the galaxy-mass correlation function out to significant radii for mass environment tests (3-10 Mpc); +sample cuts on morphological surface brightness type vs redshift; and assessment of SNR for +dwarf galaxy samples and sample completeness. The LSST main survey will +have hundreds of thousands of dwarf galaxies in a range of redshift from 0.2 - 0.6 which act as lenses. +The shear SNR is high: A simulation of just 20 LSST visits to a single $z=0.5$ galaxy +with total $10^{11} M_\odot$ virial mass yields a shear SNR of 10 out to several Mpc projected radius. +Stacking a million dwarf galaxies should thus yield high precision mass profiles, even when cut on +parameters such as mass environment, surface brightness type, stellar mass, redshift, etc. +} +~\\ +\deliverables{Deliverables over the next several years from the activities +described above include the following: +\begin{enumerate} +\item using a set of n-body full hydro models of galaxies at stages in development, +select a set of template galaxies for use as lenses in ray-trace simulations; +\item galaxy - mass shear simulations over at least 1000 sq.deg, using the +latest LSST OpSim run and full end-to-end weak lens ray trace, including PSF +and detector effects -- for a representative set of galaxies over a range of masses; +\item galaxy-mass correlation functions using these stacked LSST shear +simulations, for sets of populations of galaxies over a wide mass range; +\item assess SNR vs galaxy mass, and ability to correlate mass profile with +optical surface brightness and type, over a range of redshift. \end{enumerate} } \end{task} @@ -271,6 +331,7 @@ \subsection{Optimizing Galaxy Photometry} require not just photometry for the entire galaxy, but well-characterized photometry for sub-components, such as a central point-source or a central bulge. } +~\\ \activities{ The core photometry algorithms will end up being applied in level 2 processing, so it is important that photometry be vetted for a large number of potential @@ -287,13 +348,14 @@ \subsection{Optimizing Galaxy Photometry} Because photometry is so central to much of LSST science, there will need to be close collaboration between the LSST Project and the community. } +~\\ \deliverables{ Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item developing metrics for various science cases to help evaluate the level 2 photometry; \item providing realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies); \end{enumerate} -Deliverables over the longer term include develping optimal techniques for forced photometry +Deliverables over the longer term include developing optimal techniques for forced photometry using priors from the space missions. } \end{task} @@ -314,6 +376,7 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} the star-formation histories of sets of galaxies rather than individuals, and using ancillary data from other wavelengths. } +~\\ \activities{ Activities in this area include developing scalable techniques for hierarchical Bayesian inference on very large data sets. These can be @@ -325,6 +388,7 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} Another important activity is to identify the ancillary data sets and observing opportunities, especially for the deep fields. } +~\\ \deliverables{ Deliverables over the next several years from the activities described above include the following: \begin{enumerate} @@ -336,151 +400,32 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} \end{task} -\begin{comment} +%\begin{comment} -\subsection{Software Integration} -\tasktitle{Software Integration} +%\subsection{Software Integration} +%\tasktitle{Software Integration} % Level 2 and Level 3 software -\begin{task} -\label{task:gal:integration} -\motivation{ -The LSST Project is responsible for level 2 data processing, and the community -is expected to any processing beyond that as level 3. Furthermore, some algorithms developed -as part of the level 3 effort are expected to migrate to level 2. There needs -to be strong coordination between the Project and the community for this concept -to work. This includes training in developing level 3 software and community engagement in -defining the requirements and interfaces. -} -\activities{ -The most urgent activity is to develop some early prototypes of level 3 software -so that the interfaces can be worked out on realistic use cases. -} -\deliverables{} -\end{task} - -\end{tasklist} - -\subsection{Precursor Observations or Synergy with Other Facilities} \label{sec:tasks:gal:precursor} - -\begin{tasklist}{G-PO} -\tasktitle{Redshift surveys in the Deep Drilling fields} -\begin{task} -\label{task:gal:redshift_surveys_dd_fields} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Ancillary Data in Deep Drilling fields} -\begin{task} -\label{task:gal:ancillary_data_dd_fields} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Photometric redshift training and calibration} -% Emphasize differences in requirements relative to DE -\begin{task} -\label{task:gal:photz_calibration} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Joint use of spectroscopic and photometric redshifts} -\begin{task} -\label{task:gal:spec_plus_phot_redshifts} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\end{tasklist} - -\subsection{LSST-targeted theory or simulations} \label{sec:tasks:gal:simulations} - -\begin{tasklist}{G-TS} -\tasktitle{Image simulations of galaxies with complex morphologies} -% Mergers -% Tidal features -% Stellar halos -% Vary the galaxy-evolution model -\begin{task} -\label{task:gal:image_simulations} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Rare objects} -% extreme over/underdensities -% massive early galaxies -% extremely supermassive black holdes -\begin{task} -\label{task:gal:rare_objects} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Cosmic Variance estimators} -% Develop simple tools...encourage their use -\begin{task} -\label{task:gal:cv_estimators} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Nearby dwarfs: surface brightness fluctuations} -\begin{task} -\label{task:gal:dwarf_sb_fluctuations} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Testing group and void finders} -\begin{task} -\label{task:gal:group_finders} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\end{tasklist} - -\subsection{Databases and Data Services} \label{sec:tasks:gal:databases} - -\begin{tasklist}{G-DDS} -\tasktitle{Data structures to characterize survey biases and completeness} -\begin{task} -\label{task:gal:data_structures} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Queries to find unusual class of objects} -% mergers -% tidal streams -% nearby dwarf candidates -% morphologically disturbed close pairs -\begin{task} -\label{task:gal:queries} -\motivation{} -\activities{} -\deliverables{} -\end{task} - -\tasktitle{Compact representations of likelihood functions} -\begin{task} -\label{task:gal:likelihoods} -\motivation{} -\activities{} -\end{task} +%\begin{task} +%\label{task:gal:integration} +%\motivation{ +%The LSST Project is responsible for level 2 data processing, and the community +%is expected to any processing beyond that as level 3. Furthermore, some algorithms developed +%as part of the level 3 effort are expected to migrate to level 2. There needs +%to be strong coordination between the Project and the community for this concept +%to work. This includes training in developing level 3 software and community engagement in +%defining the requirements and interfaces. +%} +%~\\ +%\activities{ +%The most urgent activity is to develop some early prototypes of level 3 software +%so that the interfaces can be worked out on realistic use cases. +%} +%~\\ +%\deliverables{ADD SOMETHING} +%\end{task} -\end{comment} +%\end{tasklist} +%\end{comment} \end{tasklist} +} diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index 214509a..07e50a7 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -1,12 +1,13 @@ \section{High-Redshift Galaxies}\label{sec:tasks:high_z} +{\justify Observations of distant galaxies provide critical information into the efficiency of the galaxy formation process, the end of the reionization era, the early enrichment of the intergalactic medium, and the initial conditions for the formation of modern galaxies at later times. Through its wide area and sensitivity -in $zy$ LSST will probe galaxies out to $z\sim7$, and will probe -yet further in conjuction with future wide-area infrared surveys. +in $zy$, LSST will probe galaxies out to $z\sim7$ and +yet further in conjunction with future wide-area infrared surveys. The following science tasks address outstanding preparatory work for maximizing high-redshift science with LSST. @@ -18,18 +19,37 @@ \subsection{Optimizing Galaxy Photometry for High-Redshift Sources} \label{task:high_z:photometry} \motivation{ The identification and study of high-redshift galaxies with LSST hinges on reliable, accurate and optimal measurements of the galaxy flux in all LSST passbands. -Galaxies at redshifts above 7 will only be detected in the LSST y-band and will be non-detections or ``drop-outs'' in the other LSST filters. Galaxies at redshifts above 8 will not be detected at all in the LSST filters but combining LSST with infrared surveys such as Euclid and WFIRST would enable this population to be identified. It is particularly important to have robust flux measurements and robust flux limits for the undetected high-redshift galaxies in the blue LSST filters so this information can be utilized in the high-redshift galaxy selection. Since Euclid and WFIRST are space-based missions with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogenous flux measurements for sources across the different surveys. +Galaxies at redshifts above $z\sim7$ will only be detected in the LSST $y$-band and will be non-detections or ``drop-outs'' in the other LSST filters. +Galaxies at redshifts $z>8$ will not be detected at all in the LSST filters, +but combining LSST with infrared surveys such as Euclid and WFIRST would enable the identification +of this population. +Robust flux measurements or limits for the undetected high-redshift galaxies in the blue LSST filters will prove particularly important, as this information enables efficient +high-redshift galaxy selection. +The highest redshift searches will LSST will necessarily require combining with space-based +infrared surveys like Euclid and WFIRST. +Since Euclid and WFIRST will provide data with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogeneous flux measurements for sources across the different surveys. \\ -It is not clear if the current Level 2 data products package will meet all the requirements for high-redshift science with LSST and this therefore needs to be investigated before the start of the survey. +It remains unclear whether the current LSST Level 2 data will meet all the requirements for identifying and characterizing high-redshift galaxy populations, +motivating an investigation before the start of LSST operations. } +~\\ \activities{ -Firstly, we need to get a clearer picture of what constitutes the LSST Level 2 data products so we can assess whether these will be adequate for the high-redshift science. Issues that we need to understand are: 1) Will photometric catalogues be produced using the reddest LSST (e.g. y-band) images as the detection image? This is critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. 2) When computing model galaxy fluxes, will negative fluxes be stored? Negative fluxes for undetected galaxies together with their corresponding errorbars, provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. +First, the potential need for Level 3 data products beyond the baseline LSST Level 2 catalog +requires clarification. Photometric catalogues produced using the reddest LSST (e.g. $z$- or $y$-band) images as the detection image will prove critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. Similarly, negative fluxes for undetected galaxies together with their corresponding errorbars provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. Coordinating with the LSST Project to ensure +the application of forced photometry in Level 2 in a manner appropriate for high-redshift galaxy +selection may be sufficient, or Level 3 data products may be required. \\ -The second major activity will be determining the best approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection. We will need to determine the optimal measure of an optical-IR colour for sources from these two datasets. There is the additional complication that sources that are resolved in the Euclid/WFIRST data could be blended in LSST and will therefore need to be accurately de-blended, perhaps using the high-resolution IR data as a prior, before a reliable flux and colour measurement can be made. Tests can be run using existing datasets e.g. from the Dark Energy Survey (DES) and HST.} +Second, the determination of a suitable approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection will be required. +We will need to determine the optimal measure of an optical-IR color for sources from these two datasets. Sources resolved in Euclid or WFIRST data could be blended in LSST, and may therefore +require deblending using the higher resolution IR data as a prior before reliable flux and +color measurements can be made. The engineering of this combined analysis likely will require +Level 3 efforts, and tests using existing datasets (e.g., Dark Energy Survey and Hubble +Space Telescope data) may already commence.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Determine what constitutes LSST Level 2 data products and document what additional data products will be required for high-redshift science. -\item Develop tools to produce optimal combined photometry from ground and space-based surveys and test these on existing datasets. +\item Clarification of LSST Level 2 data suitability for high-redshift science, and an identification of any Level 3 needs. +\item Development of Level 3 tools to produce optimal combined photometry from ground and space-based surveys, and the testing of these tools on existing datasets. \end{enumerate} } \end{task} @@ -39,21 +59,43 @@ \subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} \begin{task} \label{task:high_z:interlopers} \motivation{ - Before the start of LSST operations, it is important that we are able to test our selection methods for high-redshift galaxies on high-fidelity simulations. Given the wide-field coverage of LSST, it will be uniquely positioned to uncover large samples of the most luminous and massive high-redshift galaxies at the Epoch of Reionisation and beyond. The most significant obstacle to selecting clean samples of such sources from the photometric data, is the presence of significant populations of interlopers e.g. cool stars in our own Milky Way and low-redshift, dusty and/or red galaxies, both of which can mimic the colours of high-redshift sources. Using the LSST simulations, we want to be able to devise the most effective way of separating these different populations, and utilising both photometric and morphological information for the sources. Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA infrared surveys, we expect at least some of the most luminous z > 6 galaxies to be spatially resolved in the LSST images. +Before the start of LSST operations, the testing of selection methods for high-redshift +galaxies on high-fidelity simulations will provide essential validation of the utility of +LSST data for studying distant galaxy populations. +Given its wide-field coverage, LSST will uniquely uncover large samples of the most luminous and potentially massive high-redshift galaxies at the Epoch of Reionization \citep{robertson2007a}. +The most significant obstacle to selecting clean samples of such sources from the photometric data +is the presence of significant populations of interlopers, such as +cool brown dwarfs in our own Milky Way and low-redshift, dusty and/or red galaxies. +These objects can mimic the colors of high-redshift sources and therefore +prove difficult to distinguish. +This is particularly a problem for the highest redshift objects detected by LSST, which, unless data at redder wavelengths is available (such as near-infrared imaging from VISTA/Euclid/WFIRST, and/or mid-infrared imaging from Spitzer/WISE) will be only detected in one or two red-optical filters. +Using the LSST simulations, we want to devise the most effective way of separating these different populations by utilizing both photometric and morphological information for the sources. +Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA, +we expect LSST images to spatially resolve at least some of the most luminous $z > 6$ galaxies \citep{willott2013a, bowler2017a}. +For fainter high-redshift galaxies however, a morphological distinction between faint ultra-cool brown dwarfs may not be possible, and further information such as near-infrared colours or proper motions will be required for identification. } +~\\ \activities{ -Liaise with the LSST simulations working group to ensure that high-redshift galaxies have been incorporated into the simulations with a representative set of physical properties (e.g. star formation histories, UV-slopes, emission line equivalent widths, dust extinction, metallicity). It is also important that the high-redshift galaxies have the correct number density and size distribution in the simulations. The latter will allow us to investigate how effectively we can use morphology to separate these galaxies from interlopers. -\\ -In addition to the high-redshift galaxies, it is equally important from a high-redshift science perspective, that interlopers have been incorporated into the simulations with the correct number densities and colours. Interlopers of particular relevance to the high-redshift searches will be cool stars in our own Milky Way (e.g. L and T-dwarf stars) as well as populations of very red, massive and/or dusty galaxies at lower redshifts of $z\sim2$. -\\ -Finally, we may want to consider whether to include colour information in the infrared filters (e.g. those from Euclid/WFIRST) in the simulations as this information will undoubtedly help with the high-redshift selection. +Liaise with the LSST Project simulations working group to ensure that high-redshift galaxies have been incorporated into the simulations with a representative set of physical properties (e.g., star formation histories, UV-slopes, emission line equivalent widths, dust extinction, and +metallicity). Ensure that high-redshift galaxies have the correct number density and size distribution in the simulations, allowing for investigations to characterize +how effectively morphology can separate high-redshift galaxies from low-redshift interlopers. +The high-redshift quasar population should also be included, as these have comparable number densities to the brightest galaxies at these redshifts and are typically indistinguishable with broad-band photometry only. +Incorporate interloper populations into the simulations with the correct number densities and colors, including cool Milky Way stars +(e.g., M, L and T-brown dwarfs) as well as populations of very red, massive, +and/or dusty galaxies at lower redshifts of $z\sim2$. +Determine the degree to which LSST selection of high-redshift galaxies effectively requires +color information from infrared filters provided by external surveys +(i.e., Euclid or WFIRST). } + ~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Incorporate high-z galaxies into LSST simulations with a realistic and representative set of properties. -\item Incorporate brown dwarfs into LSST simulations -\item Extend simulations to other datasets beyond LSST (e.g. Euclid/WFIRST filters). +\item Incorporate high-z galaxies (and quasars) into LSST simulations with a realistic and representative set of properties. +\item Incorporate cool Milky Way brown dwarfs into LSST simulations. +\item Provide a prediction of the likely number density of brown dwarfs over the different DDFs. +\item Extend simulations to other datasets beyond LSST (e.g., Euclid and WFIRST filters). \end{enumerate} } \end{task} \end{tasklist} +} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index b75b9c6..8b434be 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -1,136 +1,100 @@ \section{Low-Surface Brightness Science}\label{sec:tasks:lsb} - -The exquisite data quality of LSST will enable a new regime in -low-surface brightness (LSB) science over large areas of the sky. The capability -to conduct unparalleled LSB science with LSST will uncover new -evidence for and measures of the cosmic merger rate, reveal the -signature of hierarchical structure formation in extragalactic stellar -halos, and probe the LSB outskirts around other galaxies. The following -science tasks provide an enumeration of preparatory research tasks for -leveraging fully the LSST dataset for LSB science. +{\justify +The exquisite data quality of LSST will open up a brand new regime in +low-surface brightness (LSB) science, over unprecedentedly large areas of the sky. LSST's unique deep-wide capabilities will enable us to uncover new evidence for and measures of the cosmic merger rate (via tidal features that result from galaxy interactions), reveal the signatures of hierarchical structure formation in extragalactic stellar halos, and probe the LSB outskirts around local galaxies. The following science tasks provide an enumeration of the critical preparatory research tasks required for fully leveraging the LSST dataset for LSB science. \begin{tasklist}{LSB} -\subsection{Techniques for Finding Low-Surface Brightness Tidal Features} -\tasktitle{Techniques for Finding Low-Surface Brightness Tidal Features} +\subsection{Low-Surface Brightness Tidal Features} +\tasktitle{Low-Surface Brightness Tidal Features} \begin{task} \label{task:lsb:tidal_features} \motivation{ -A key advantage of LSST over previous large-area surveys (e.g. the SDSS) is its ability to detect low-surface-brightness (LSB) features associated with galaxies. This includes tidal streams and other features associated with past and ongoing interactions, intra-cluster and intra-group light, and nearby, extended low- surface-brightness galaxies. +A key advantage of LSST over previous large-area surveys (e.g. the SDSS) is its ability to detect low-surface-brightness (LSB) tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be 2 mags deeper than the SDSS almost immediately after start of operations, and 5 mags deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionise LSB tidal feature science, enabling us, for the first time, to empirically reconstruct the assembly histories of galaxies over at least two-thirds of cosmic time, provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth and morphological transformation over a significant fraction of cosmic time. \\ -Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected by criteria that are difficult to quantify (e.g. visual inspection that can somewhat subjective) or reproduce in theoretical models. Automated (algorithmic) measurements of the LSB features themselves can be challenging and many past studies have relied on visual inspection for the identification and characterization of features (which may not easily applied on the LSST scale). For LSST it is highly desirable that we automate the detection and characterization of LSB features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. +Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected using criteria that are difficult to quantify (e.g. visual inspection, that can be somewhat subjective) or reproduce in theoretical models. Furthermore, previously used techniques for the identification and characterization of features, such as visual inspection, cannot be easily applied to the unprecedented volume of data expected from the next generation of telescopes like LSST. Given the depth and volume of data expected from LSST, it is critical that we automate the detection, measurement and characterization of LSB tidal features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. } +~\\ \activities{ -Several activities are of crucial importance: +Several activities are of critical importance and need to be completed before LSST commissioning and the survey proper: \begin{enumerate} -\item Simulating realistic LSST images and LSB features (using, e.g., high-resolution hydro simulations) -\item Identifying precursor datasets that can be used as proxies for developing LSB tools for use on LSST data -\item Using the simulations to develop algorithms for detection and measurement of LSB features +\item Simulating realistic LSST images and LSB features (using e.g. new high-resolution hydrodynamical simulations in cosmological volumes, such as Horizon-AGN, EAGLE, Illustris and others). +\item Identifying precursor datasets (e.g. the Hyper Suprime Cam Survey or the Dark Energy Camera Legacy Survey (DECaLS)) that can be used as testbeds for developing LSB tools for use on LSST data. +\item Using such simulations to develop algorithms for auto-detection, measurement and characterisation of LSB features (e.g. using the properties of LSB tidal features to back-engineer the properties of the mergers which created them). \item Applying these algorithms to the precursor datasets to test their suitability -\item Ensuring that LSST level-2 processing strategies and observing strategies are aligned with the needs of LSB science -\item Developing a strategy for finding and measuring LSB features through a combination of level 2 measurements, database queries, and level 3 processing +\item Ensuring that LSST level-2 processing strategies and observing strategies are aligned with the needs of LSB tidal-feature science. \end{enumerate} -It is important to produce realistic LSST images from e.g. the current generation of hydro-dynamical cosmological simulations (which faithfully incorporate both the evolution of large-scale structure and the interplay between baryons and dark matter during interactions). Scattering from bright stars (which may or may not be in the actual field of view of the telescope) is likely to be the primary source of contamination when searching for extended LSB features. Ideally, the LSST scattered-light model, tuned by repeated observations, will be sufficiently good that these contaminants can be removed or at least flagged at level 2. Defining the metrics for “sufficiently good,” based on analysis of simulated images, is an important activity that needs early work to help inform LSST development. -\\ -Including Galactic cirrus in the simulations will be important when developing strategies for detecting for large-scale LSB features. Including a cirrus model as part of the LSST background estimation is worth considering, but it is unclear yet whether the science benefit can justify the extra effort. -\\ -Because the LSST source extraction is primarily optimized for finding faint, barely-resolved galaxies, it will be challenging to optimize simultaneously for finding large LSB structures and cataloging them as one entity in the database. For very large structures, analysis of the LSST “sky background” map, might be the most productive approach. We need to work with the LSST project to make sure the background map is stored in a useful form, and that background measurements from repeated observations can be combined to separate the fluctuating foreground and scattered light from the astrophysically interesting signal from extended LSB structures. Then, we need strategies for measuring these background maps, characterizing structures, and developing value-added catalogs to supplement the level 2 database. -\\ -For smaller structures, it is likely that the database will contain pieces of the structure, either as portions of a hierarchical family of deblended objects, or catalogued as separate objects. Therefore, we need to develop strategies for querying the database to identify galaxies which are likely to have such structures. E.g. in galaxies that have LSB tidal features around them, the main body of the galaxy is likely to be disturbed and therefore asymmetric. Measures of asymmetry will therefore be useful for flagging such systems. We then need to have a strategy for either extracting the appropriate data for customized processing, or develop ways to put back together the separate entries in the database. A possible value-added catalog, for example, from the galaxies collaboration might be an extra flag in the database to indicate that a galaxy is likely to have LSB tidal features and an extra set of fields for the database to indicate which separate objects are probably part of the same physical entity. -\\ -This would be relatively sparsely populated in the initial stages of LSST. Estimates from the Stripe 82, indicate that 15\% of galaxies carry LSB tidal features (LSST will reach Stripe 82 in a single shot) but by the end of the survey will become a key resource for a wide variety of investigations. } -\deliverables{Deliverables over the next several years from the activities described above include the following: +~\\ +\deliverables{Deliverables over the next several years (especially in the run up to commissioning) from the activities described above include the following: \begin{enumerate} -\item Realistic mock LSST images from hydro cosmological simulations (including re-simulations of individual objects were necessary) with spatial resolutions of tens of parsecs. -\item Algorithms for finding galaxies with LSB features and for measuring the properties of these features. -\item Input to the Project on scattered-light mitigation and modeling strategies from the simulations. -\item Input to the Project on photometric and morphological parameters (e.g. asymmetry, residual flux fractions etc) to measure and store in the level 2 database. -\item Query strategies and sample queries for finding LSB structures. -\item A baseline concept for a value-added database of LSB structures. +\item Realistic mock LSST images from hydro cosmological simulations (including re-simulations of individual objects were necessary) with spatial resolutions of $\sim1$ kpc or better +\item Algorithms for finding galaxies with LSB tidal features, measuring the properties of these features and characterising them i.e. using the properties of LSB tidal features to reconstruct the properties of the mergers which created them (e.g. mass ratios, time elapsed since the merger, etc.). +\item A baseline concept for a value-added LSST database of LSB tidal features. \end{enumerate} } \end{task} \subsection{Low-Surface Brightness Galaxies} -\tasktitle{Low-Surface Brightness Galaxies} +\tasktitle{Diffuse and Low-Surface Brightness Galaxies} \begin{task} \label{task:lsb:galaxies} \motivation{ -Our objective is to investigate the most relevant and challenging aspects of the Low Surface Brightness (LSB) Universe. This has a direct baring on the range of galaxies initially formed, the properties that they have during and after their assembly, their connection to the cosmic web and ultimately to the nature of dark matter, which plays a large part in all of these processes. -\\ -By LSB we mean objects that have surface brightnesses much less than that of the background night sky and that which is typical of the Milky Way galaxy we live within. Many authors have previously shown how difficult it is to detect objects of LSB and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to the spiral galaxy that we live within. Thus the Universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? -\\ -The problem is that astronomical observations always include a signal from a background, a level we need to detect our sources above. For ground based observations the background arises locally from the atmosphere and our proximity to the Sun, scattered light from the solar system, diffuse star light from the Galaxy and a small contribution from other galaxies in the Universe. For an astronomical object to be detected it must stand out above the noise level in this background. If this noise was purely due to photon statistics then very simply all we would need to do is collect as many photons as possible and the signal would gradually appear out of the noise. However, we currently know that it is nowhere near this simple because of scattered light across the field of view (FOV), instrumental calibration uncertainties and real fluctuations in the cosmic background. For these reasons there has previously been little progress in making a definitive study of the extent and brightness limits of the LSB Universe. +The objective of this task is to investigate objects that have surface brightnesses much less than that of the background night sky and that which is typical of the Milky Way galaxy we live within. Many authors have previously shown how difficult it is to LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to the spiral galaxy that we live within. Thus, the Universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? \\ -Additionally, this LSB universe include a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model. The galaxy mass function at masses less than Mh ~ 1010 Msun systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via HI surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies are still quite easy to detect in LSST images. +Additionally, this LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via HI surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies are still quite easy to detect in LSST images. \\ -The challenge is to identify them as nearby dwarfs and estimate their distances and hence luminosities. The dwarfs in question are low-surface-brightness galaxies, so many of the source-detection issues are common to the more general problem of detecting LSB features. LSST data allow us to focus on different issues. For certain distances and luminosities, typical dwarf spheroidal galaxies will be distinct from the vast majority of background galaxies in the radius vs apparent magnitude plane. However, there will often be overlapping background galaxies, so it is important that the de-blending and cataloging steps try to remove the overlaps and allow one to query for galaxies in the right portion of the color-size-brightness manifold. Once candidates are identified, it should be possible to tease out approximate distances for many dwarf galaxies via surface-brightness fluctuations (SBF). Once again this requires careful treatment of the background galaxies, but this step is now Level 3 processing, so can be customized much more than the detection step. More ambitiously, it is conceivable that machine-learning techniques could be trained to identify semi-resolved nearby dwarf galaxies given a suitable training set from LSST-precursor observations. +At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting SB of the LSST combined with the large FOV make this instrument unique to probe the existence of large LSBs, similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. \\ -On the other extreme of LSB objects, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disc of stars and an impressive system of spiral arms only revealed in 2015. The central bulge of the galaxy is prominent, but the stellar disc and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB discs? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting SB of the LSST combined with the large FOV make this instrument unique to probe the existence of large LSBs, similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant discs like Malin 1 only make this problem worse. This is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. In addition we will be exploring the very outer regions of galaxies and so will be able to explore the connection between the decreasing surface density of baryons and the increasing significance of the dark matter component of galaxies. -\\ -One reason why this subject has made little progress over the last few years is because of the limited amount of deep large area data available. Most previous deep (CCD) surveys have been specifically designed to investigate the distant Universe and so, like the Hubble Deep Field, have concentrated on long exposures over small areas of sky. The extensive sky survey that LSST will carry out will become the state-of-the-art for years to come and offers a new and enormous LSB discovery potential. As a pointer to these exciting discoveries there have recently been relatively small-scale observations that indicate that a hidden LSB galaxy population does exit. An example is the population of LSB galaxies recently detected in the Coma and Fornax clusters, galaxies not only with astonishing LSB (>27 B mag arcsec-2), but also with some of them exhibiting effective radii similar to that of the Milky Way. This is despite both Coma and Fornax being two of the previously most studies regions of the nearby Universe. -\\ -To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5\mathrm{mag}~\mathrm{arcsec}^2$ and that from a space telescope typically an order of magnitude fainter $\approx25.0\mathrm{mag}~\mathrm{arcsec}^2$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0\mathrm{mag}~\mathrm{arcsec}^2$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28\mathrm{mag}~\mathrm{arcsec}^2$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32\mathrm{mag}~\mathrm{arcsec}^2$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into high surface brightness stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26\mathrm{mag}~\mathrm{arcsec}^2$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the Universe using LSST to at least a surface brightness level of $30\mathrm{mag}~\mathrm{arcsec}^2$. +To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5~\mathrm{mag}~\mathrm{arcsec}^{-2}$ and that from a space telescope typically an order of magnitude fainter $\approx25.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28~\mathrm{mag}~\mathrm{arcsec}^{-2}$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32~\mathrm{mag}~\mathrm{arcsec}^{-2}$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into luminous stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the Universe using LSST to at least a surface brightness level of $30~\mathrm{mag}~\mathrm{arcsec}^{-2}$. } -\activities{ +~\\ +\activities{The key activities for this task are as follows: \begin{enumerate} -\item Production of simulated data that can be passed through the LSST data reduction pipeline. -\item Analysis of simulated images to ensure that LSB features can be accurately preserved and measured. -\item The development of new object detection software specifically designed for the detection of LSB features, in particular: +\item Production of simulated data e.g. from new hydro-dynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. +\item Analysis of simulated images to ensure that LSB galaxies can be accurately detected +\item The development of new object detection software specifically designed for the detection of LSB galaxies, in particular: \begin{itemize} \item Objects with large size. \item Objects near or melted with large size, bright galaxies. -\item Objects with patterns similar to galaxy streams. \item Highly irregular and distorted objects. \end{itemize} -\item Identification of precursor data sets that can be used to test our methods. We can use data generated using numerical simulations to look at the types of galaxies produced that have sufficient angular momentum to become LSB discs. These discs can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. We will develop new methods of detecting LSB objects. These will include pixel clustering methods and the labeling of pixels with certain properties i.e. surface brightness level, SED shape, proximity to other similar pixels etc. We will trial our methods on other currently available data sets (KIDS, CFHT etc). -\item Simulate realistic LSST images of nearby dwarf galaxies. +\item Identification of precursor data sets that can be used to test our methods. We can use data generated using numerical simulations to look at the types of galaxies produced that have sufficient angular momentum to become LSB disks. These disks can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. We will develop new methods of detecting LSB objects. These will include pixel clustering methods and the labeling of pixels with certain properties i.e. surface brightness level, SED shape, proximity to other similar pixels etc. We will trial our methods on other currently available data sets (KIDS, CFHT etc). +\item Production of realistic simulated LSST images of nearby dwarf galaxies (from high resolution hydro-dynamical simulations like New Horizon which has resolutions of tens of parsecs) \item Identify nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools. \item Develop and test the database search queries for finding candidates of several shapes and sizes. -\item Develop and test a measurement of semi-resolved ``texture'' as a candidate level 2 measurement. \end{enumerate} -The use of ``texture'' as a means of identifying candidate nearby dwarf galaxies is something that needs near-term attention if it is to make it into level 2 processing early in the survey. This can be developed and tested on the semi- resolved-galaxy simulations, but it is also essential to test it on precursor data sets from DES, CFHTLS or HSC. -\\ -As a natural consequence of the effort that the members of this team are going to invest on the discovery and catalogue, we can foresee a long-term group effort for continuing the research once deliverables are available. A natural strategy, will be to perform several follow ups with large aperture telescopes available in Chile, with powerful instruments capable of obtaining optical, near-IR spectra, sub-mm, mm and IFU data for LSB objects. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Realistic mock LSST images. -\item An assessment of the influence of the PSF, scattered light and other instrument signals that may affect our ability to detect LSB features -\item An assessment of the effect of proposed pipeline on the detection and measurement of LSB features. -\item A baseline concept for the construction of a database of LSB features detected using LSST data. -\begin{itemize} -\item Realistic inputs of dwarf galaxies for the LSST image simulations. -\item Realistic postage-stamp simulations of semi-resolved dwarf galaxies. -\item Training set of nearby dwarfs from LSST precursor data. -\item Figures of Merit for detection and selection algorithms -\item Run LSST pipeline on both simulations and precursor data and assess performance. -\end{itemize} -\item Optimized algorithms measuring surface brightness fluctuation distances. -\item A new LSB object detection package, friendly adapted for the user. +\item Realistic mock LSST images of LSB galaxies from simulations. +\item Detection and selection algorithms for LSB galaxies from observational datasets. +\item A new Level 3 LSB galaxy detection package. \end{enumerate} } \end{task} -\subsection{Probing the Faint Outskirts of Galaxies with LSST} -\tasktitle{Probing the Faint Outskirts of Galaxies with LSST} +\subsection{Faint Outskirts of Galaxies} +\tasktitle{Faint Outskirts of Galaxies} \begin{task} \label{task:lsb:faint_outskirts} \motivation{ -The outskirts of nearby galaxies, loosely defined as the regions below $25-26\mathrm{mag}~\mathrm{arcsec}^2$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). +The outskirts of nearby galaxies, loosely defined as the regions below $25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). \\ The main science driver here is understanding the assembly, formation, and evolution of galaxies. This can be studied through imaging and subsequent parametrization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar haloes. From numerical modelling we know that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo, are tightly related to the accretion and merging history. This is illustrated by the imaging of the stars in the outskirts of M31 and other local group galaxies, which show detailed structure. \\ -Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to local group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams may be less affected by overall PSF, but more by foreground cirrus. +Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams will be less affected by overall PSF. } +~\\ \activities{ Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modelling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyse the outskirts. Dithering and rotation of individual imaging will need to be modelled before stacking multiple imaging. \\ Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Information on the stability and spatial constancy of the LSST PSF. @@ -141,36 +105,39 @@ \subsection{Probing the Faint Outskirts of Galaxies with LSST} -\subsection{Low-Surface Brightness Intracluster Light} -\tasktitle{Low-Surface Brightness Intracluster Light} +\subsection{Intracluster Light} +\tasktitle{Intracluster Light} \begin{task} \label{task:lsb:icl} \motivation{ The Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. It is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. \\ -Some outstanding scientific questions, which LSST could solve: +Some outstanding scientific questions, which LSST could solve are as follows: \begin{itemize} \item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? \item Does it contain significant substructure? -\item What is its surface brightness profile and does it have a colour dependence, which would indicate age/metallicity gradients? +\item What is its surface brightness profile and does it have a color dependence, which would indicate age/metallicity gradients? \item Where does the ICL begin and the large diffuse cD halo of the Brightest Cluster Galaxy (BCG) end and do they have the same origin? \end{itemize} } +~\\ \activities{ -The preparation work for the ICL component of the LSB case involves investigating LSST specific issues for large LSB features and the known properties of the ICL itself. +The preparation work for the ICL component of the LSB case involves investigating LSST-specific issues for large LSB features and the known properties of the ICL itself. \\ -The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce low surface brightness signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for the LSB team to liaise with LSST strategy, telescope, instrument and data reduction teams. +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce low surface brightness signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for our team to liaise with LSST strategy, telescope, instrument and data reduction teams. \\ -The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. +The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want to study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Investigate any telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. -\item Investigate observation specific issues that affect the measurement of large LSB features: dither pattern strategy. -\item Investigate image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. -\item Feasibility: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? -\item Investigate stacking clusters to obtain faint ICL - this is difficult as will require very strong masking of even the faintest observable cluster members. +\item An investigation of telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. +\item An investigation of observation specific issues that affect the measurement of large LSB features: dither pattern strategy. +\item An investigation of image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. +\item A feasibility analysis: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? +\item An investigation of the feasibility of stacking clusters to obtain faint ICL - this is difficult as will require very strong masking of even the faintest observable cluster members. \end{enumerate} } \end{task} -\end{tasklist} \ No newline at end of file +\end{tasklist} +} diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index 2166542..9b0516a 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -1,48 +1,54 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} - -For a photometric survey like LSST, the ability to measure -vast distances to galaxy samples, understand the time evolution -and spatial clustering of galaxy populations, surmise the -stellar mass, age, and metallicity of objects, and to identify -unusual objects at various cosmic epochs relies heavily on -methodologies for constructing photometric redshifts from the data. -The following important preparatory science tasks address both the -systematic uncertainties on photometric redshifts associated -with the LSST observatory and with the requisite +{\justify +For a photometric survey like LSST, our abilities to accurately measure distances to huge samples of galaxies, to constrain the stellar masses, ages, and metallicities of objects as a function of time, to measure the spatial clustering of galaxy populations, and to identify unusual objects at various cosmic epochs will all rely heavily on +photometric redshift measurements. +The following important preparatory science tasks address both the systematic uncertainties on photometric redshifts associated with the LSST observatory and with the requisite stellar population synthesis models. +It is important to note that a major effort within the LSST Dark Energy Science Collaboration (DESC) is focused on the development of photometric redshift algorithms for LSST, including the incorporation of joint probability distributions between redshift and astrophysical parameters of interest for the study of galaxy evolution. Efforts within the Galaxies collaboration should be able to leverage work happening in DESC and build upon it to ensure that photometric redshifts optimized for galaxy science are available. + \begin{tasklist}{PZ} -\subsection{Impact of Filter Variations on Galaxy photo-z Precision} -\tasktitle{Impact of Filter Variations on Galaxy photo-z Precision} +\subsection{Impact of Filter Variations on Galaxy photo-$z$ Precision} +\tasktitle{Impact of Filter Variations on Galaxy photo-$z$ Precision}\label{pzfiltervar} \begin{task} \label{task:photo_z:filter_variations} \motivation{ -For accurate photometric redshifts, well calibrated photometry is essential. Variations in the telescope system, particularly the broad-band ugrizy filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of local environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane. Such corrections will be SED dependent, and may leave residuals, particularly for specific populations with unusual SEDs. Tests of the amplitude of these residuals, and the impact on photo-z as a whole, and for particular object classes, is an important consideration. Beyond this, if the variations turn out to be very well calibrated, they could potentially be used to further improve, rather than degrade, photo-z performance. The variations in filter response can offer up additional a small amount of extra information on the object SED, given the slight variation in effective filter wavelength, particularly for objects with strong narrow features, i.e. emission lines. Tests of how much information is gained can inform whether or not the extra computational effort used in computing photo-z’s from many slightly different filters as opposed to measurements corrected to the six fiducial filters of the survey. +For accurate photometric redshifts, well-calibrated photometry is essential. Variations in the telescope system, particularly the broad-band $ugrizy$ filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. Preliminary tests show that the filter variation may have a relatively small impact, but further tests are necessary to ensure that these variations will not dominate the photometric error budget.\\ +~\\ +In addition, the effective passbands of the LSST filters will depend significantly upon atmospheric conditions and airmass, particularly in the $y$ filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of large-scale environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane or between, incorporating approximate models for galaxy SEDs (which may be based upon photometric redshift estimates). Such corrections may be imperfect and leave residuals, particularly for specific populations with unusual SEDs.~\\ +~\\ +Tests of the amplitude of these residuals and their impact on photo-$z$'s, especially for particular object classes of interest, will be important for determining to what degree DM data products can be used directly for galaxies work.If the variations can be calibrated well, they could potentially be used to further improve, rather than degrade, photo-$z$ performance. The variations in filter response can offer up a small amount of extra information on the object SED given the slight variation in effective filter wavelength, particularly for objects with strong narrow features (i.e., emission lines). Tests of how much information is gained can inform whether or not the extra computational effort required for computing photo-$z$’s that incorporate the effective passband from every individual LSST observation of an object will be superior to estimates incorporating DM measurements corrected to the six fiducial filters of the survey. All topics discussed above are also being examined by the LSST Dark Energy Science Collaboration Photometric Calibration working group, and there are several related tasks described in the DESC Science Roadmap document\footnote{The DESC Science Roadmap is available at: \url{http://lsst-desc.org/sites/default/files/DESC_SRM_V1_0.pdf}}. Communication and coordination with the Photometric Calibration group will be very important to maximize the impact of work on these areas of shared interest. } +~\\ \activities{ -Tests of the SED-dependent residuals in photometric redshifts induced by photometric calibration systematics.} +Tests of the SED-dependent residuals in photometric redshifts induced by photometric calibration systematics at the expected level.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Improved photometric calibration for LSST across all pass bands. -\item Identification of SED classes where photometric redshift failures are prominent. +\item Quantification of the amplitude of photometric uncertainties in the LSST filters due to variation in filter throughputs and atmospheric transmission. +\item Identification of SED classes where residuals in DM calibration of effective passbands will be prominent. \end{enumerate} } \end{task} -\subsection{Photometric Reshifts in the LSST Deep Drilling Fields} -\tasktitle{Photometric Reshifts in the LSST Deep Drilling Fields} +\subsection{Photometric Redshifts in the LSST Deep Drilling Fields} +\tasktitle{Photometric Redshifts in the LSST Deep Drilling Fields} \begin{task} \label{task:photo_z:ddf} \motivation{ -The LSST Deep Drilling Fields present different challenges than the main survey, including more confusion between sources, and the ability to use the best subsets of the images due to their being many repeat observations. These properties allow investigations of galaxies of brightness close to the noise in the main survey at higher signal to noise. +The LSST Deep Drilling Fields present different challenges than the main survey, including increasing rates of confusion between sources, but they also provide the ability to use subsets of the data to construct higher resolution images due to the large number of repeat observations. These properties allow investigations of galaxies of brightness which are close to the noise floor in the main survey. Having an accurate error model is essential for optimal photo-z performance; the larger number of repeat observations in the Deep Drilling Fields enables empirical checks on the magnitude and flux uncertainties generated by the LSST pipeline, through both higher signal-to-noise stacks and using subsets of the data to model the uncertainties. As LSST imaging data will not be available for several more years, such studies of subset stacks to examine seeing and error properties would have to use pre-existing data sets, e.~g.~Hyper Suprime Camera data, when testing such algorithms and putting needed infrastructure in place so that it can be used once LSST data is flowing.\\~\\ +In addition to providing useful information about main-survey photometric redshift quality, the Deep Drilling Fields will pose particular challenges for photometric redshift determination, as spectroscopy for complete samples down to the DDF depth for photo-$z$ training and calibration will be completely infeasible, and the DDF area is likely too small for high-precision calibration by cross-correlation techniques. } +~\\ \activities{ -Assessing robustness of photo-zs with spectroscopic surveys will be difficult at the faintest fluxes, but the relationship to clustering redshifts is critically important. +Tests of confusion limits in deeper coadds than available in the main survey, as well as improvements enabled by ''best seeing" subsamples on precursor data sets. Tests of the flux error model using subsets and higher signal-to-noise coadds. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item {\bf TBD} -\item {\bf TBD} +\item Studies of confusion and deblending in deep stacks and ``best seeing" conditions using precursor data sets. +\item Estimates of gains in studying faint galaxy populations at higher signal-to-noise than available in the main survey. +\item A check on LSST flux error models using both higher signal-to-noise coadds and subsets of the data to main survey depth using precursor data sets. \end{enumerate} } \end{task} @@ -52,17 +58,25 @@ \subsection{Multivariate Physical Properties of Galaxies from Photometric Redshi \begin{task} \label{task:photo_z:physical_properties} \motivation{ -The knowledge of the derived physical properties underlies much of the work involving galaxies and their evolution. Derived physical properties include, among others: star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity. When it comes to scientific analysis, in recent years the derived physical properties have largely supplanted fluxes and luminosities in the UV, optical and near-IR bands. This is because derived properties require no redshift (K) corrections, are dust-corrected, and are therefore easier to relate across surveys and studies and to compare with the models. Stellar mass has emerged as a parameter of choice for selecting galaxy types and making apple-to-apple comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a rough estimate of galaxy’s SF history. Dust attenuation and stellar metallicity are also indicative of various processes important for understanding galaxy evolution. -} +Measurements of key derived physical properties are critical for much work on galaxies and their evolution. The properties measurable from SEDs include star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity.\\ +~\\ +Many recent science analyses have relied upon derived physical properties rather than fluxes and luminosities in the UV, optical and near-IR bands. This is largely a matter of convenience: utilizing tables of derived properties require no redshift (K) corrections or extra dust corrected, as those are effectively applied in the measurement process; they are also closer to the quantities best determined in simulations. However, derived quantities have the disadvantage of the potential for significant systematic errors in measurement, as well as non-uniformity in their definition (e.g., differences in adopted IMF can change stellar masses by $\sim 0.5$ dex). \\~\\ +Stellar mass has emerged as a parameter of choice for selecting galaxy samples and attempting to make apples-to-apples comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a measure of a galaxy’s star formation history. Dust attenuation and stellar metallicity can help to probe processes important for understanding galaxy evolution.\\ +~\\ +This Task shares some goals with the Dark Energy Science Collaboration Photometric Redshifts working group, as laid out in their Science Roadmap (see ~\ref{pzfiltervar} footnote for document link), who are also interested in multidimensional probability density functions joint in redshift and stellar mass, star formation rate, and dust content of the galaxies. Coordination on this area with the DESC Photo-z working group will benefit both groups. +} +~\\ \activities{ -Deriving physical properties, usually accomplished by spectral energy distribution (SED) fitting, is an involved process and the results depend on the number of factors, including: underlying population models, assumed dust attenuation law, assumed star formation histories, choice of model priors, choice of IMF, emission line corrections, choice of input fluxes, type of flux measurements, treatment of flux errors, SED fitting methodology, interpretation of the resulting probability distribution functions (PDF) (e.g., Salim et al. 2016). In the case of LSST, the additional challenge is that the redshifts are for the most part photometric, and carry a PDF (a measure of uncertainty) of their own. In principle, the redshifts could be determined as part of the SED fitting (and vice versa, physical parameters can be obtained from some photo-z codes), but it is not clear whether this joint approach is the best. Alternatives are to use empirical training sets to obtain the photo-z (some “best” estimate or a PDF) and then feed it into the SED fitting code. -\\ -Activities will consist of testing whether the determination of physical parameters and photo-z should be performed jointly or not, based on training sets with spectroscopic redshifts, at a range of redshifts. Furthermore, testing should be performed on mock galaxies to understand which choices of methods and assumptions (specifically related to LSST data) produces the best results in the sense of retrieving the “known” properties. +Deriving physical properties, usually accomplished by spectral energy distribution (SED) fitting, is an involved process and the results depend on a number of factors, including the underlying population models, assumed dust attenuation law, assumed star formation histories, choice of model priors, choice of IMF, emission line corrections, choice of input fluxes, type of flux measurements, treatment of flux errors, SED fitting methodology, and interpretation of the resulting probability distribution functions \citep[PDFs; e.g.,][]{salim2016a}.\\ +~\\ +In the case of LSST, an additional challenge is that the redshifts available will generally be photometric, and carry a PDF (a measure of uncertainty) of their own. In principle, the redshift and SED (or specific physical parameter) should be determined simultaneously, as the inferred galaxy properties such as luminosity and stellar mass are correlated with redshift. One alternative approach is to estimate the redshift PDF using empirical training sets, then estimate best fitting SEDs at each redshift to determine physical parameters. This approximation enables the use of potentially more accurate machine learning based methods to estimate the redshift PDF, at the possible expense of adding biases and degeneracies due to the assumptions inherent in treating the redshift and physical properties separately. Further study is necessary to determine whether the benefits of this approximation outweigh the drawbacks. +Activities will consist of testing whether the determination of physical parameters and photo-$z$ should be performed jointly or not, based on training sets with spectroscopic redshifts at a range of redshifts. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-z and properties, together with the software to be used. -\item With LSST data: the production of catalogs of properties to be used by the collaboration. +\item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-$z$ and properties, together with the software to be used. +\item With LSST data: in consultation with the DESC Photo-z working group, the production of catalogs of properties to be used by the collaboration. \end{enumerate} } \end{task} @@ -72,42 +86,16 @@ \subsection{Identifying Spectroscopic Redshift Training Sets for LSST} \begin{task} \label{task:photo_z:specz_training_sets} \motivation{ -Require deep spectroscopic redshift data in order to help train algorithms, improve algorithms with clustering etc, and also provide a basis for determining accuracy of photo-z algorithms. +Accurate photometric redshift estimates require deep spectroscopic redshift data in order to help train algorithms, either directly in the case of machine learning based algorithms, or to train Bayesian priors and adjust zero points, transmission curves, or error models for template-based methods. Representative spectroscopic samples can be used to investigate the accuracy of photo-$z$ algorithms. Obtaining representative training sets is a problem across multiple science tasks, and in fact, across many current and upcoming large surveys. As the telescope resources necessary will be quite extensive, coordination with the other large surveys is essential. A detailed study of spectroscopic training needs and potential spectroscopic instruments that will be available in the coming years was undertaken by \citet[]{newman2015a}. We must now begin our attempts to obtain the necessary samples. We must also identify any needs that are unique to galaxy science that may not be prioritized in the cosmology-focused efforts to date, e.~g.~are faint galaxy populations sampled adequately in the planned spectroscopic samples? } -\activities{Collate existing spectroscopic redshift data over both DDF and wider fields, along with selection biases for each spectroscopic data set. Assess robustness of existing data, determine colour space where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. +~\\ +\activities{In coordination with other large surveys, collate existing spectroscopic redshift data over both DDF and wider fields, and assess the biases due to selection and redshift incompleteness for each spectroscopic data set. Assess the robustness of existing data, and determine color spaces where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. This work should become much more efficient once PFS and MOONS become available. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item {\bf TBD} -\item {\bf TBD} -\end{enumerate} -} -\end{task} - -\subsection{Develop Techniques to Identify Specific Sub-Populations of Galaxies} -\tasktitle{Develop Techniques to Identify Specific Sub-Populations of Galaxies} -\begin{task} -\label{task:photo_z:subpops} -\motivation{ Studying properties related with the star formation activity of galaxies, such as color and specific star formation rate (sSFR), as a function of mass, environment and redshift is relevant for understanding the different physical processes in galaxy formation and evolution. The aim is to develop techniques in order to identify specific sub-populations with the aforementioned properties (e.g. blue/star-forming and red/quenched galaxies) based on photometric data. Another interesting sub-population is galaxies which contain an active nucleus. The identification of AGN candidates will also be explored. -\\ -This task is potentially cross-cutting with the theory/mock catalogs, machine learning, clusters, lss, AGN, and DESC working groups and collaborations. -} -\activities{ -We can use simulations and mock catalogs to obtain prior estimates of the calibrations used to identify specific galaxy sub-populations. These calibrations will depend on mass and redshift (z). One technique to explore is fitting two Gaussians to the corresponding color and sSFR distributions in different mass and redshift bins to identify populations of red and blue galaxies. It is important that the mass definition assumed in the mocks be comparable to that estimated for observations. Note that the stellar mass would be used as the alpha parameter in the joint probability distribution functions, p(z,alpha). -\\ -Furthermore, we will make efforts to identify AGNs to obtain a sample of AGN candidates and, also, isolate them from “normal” galaxy samples without AGNs. The information of color and star formation described above can be used for this aim. -\\ -The techniques can be probed as a function of environment, which can be defined using different approaches at both small and large scales (e.g. number of neighbor galaxies, location in large-scale structures such as filaments, voids, knots, or Voronoi tessellation techniques). This would enable the characterization of galaxy sub-populations according to the environment. The resulting galaxy sub-populations can be used as training sets to be implemented on machine learning models. -} -\deliverables{Deliverables over the next several years from the activities described above include the following: -\begin{enumerate} -\item Obtaining mass from mock catalogs compatible with the mass used in p(z,mass). -\item Developing techniques that depend on this mass and redshift using mock catalogs for selecting samples with red/blue colors. -\item Developing multiple techniques that depend on this mass and redshift using mock catalogs for selecting star-forming/quenched samples. -\item Developing techniques that may depend on star formation, color and redshift for selecting AGN samples. -\item Defining several environment estimators in simulated datasets. -\item Probing techniques in b), c) and d) as a function of the environments defined in e). -\item Obtaining training sets to be implemented on machine learning models. +\item A list of existing {\it robust} spectroscopic objects, and identified gaps in the currently available training samples. +\item Telescope proposals for spectroscopic campaigns to fill in the sample gaps. \end{enumerate} } \end{task} @@ -117,41 +105,58 @@ \subsection{Simulations with Realistic Galaxy Colors and Physical Properties} \begin{task} \label{task:photo_z:color_simulations} \motivation{ -As representative samples of spectroscopic redshifts will be very difficult to compile for LSST, simulations will play a key role in calibrating estimates of physical properties such as galaxy stellar mass, star formation rate, and other properties. This is particularly problematic for photometric surveys, where photometric redshift and physical property estimates must be calculated jointly. In addition, we must include prominent effects that will influence the expected photometric performance, for example the presence of an active galactic nucleus can significantly impact the color of a galaxy and the inferred values for the physical parameters, so models of AGN components of varying strength must be included in the simulations. Many current generation simulations cannot or do not simultaneously match observed color distributions and physical property characteristics for the galaxy population at high redshift. As photo-z algorithms are highly dependent on accurate photometry, realistic color distributions are required to test the bivariate redshift-physical property estimates. Working with the galaxy simulations and high redshift galaxy working groups to develop new simulations with more accurate high redshift colors is a priority. These photo-z needs are not unique, and the improved simulations will benefit the wider Collaboration as a whole. +As representative samples of spectroscopic redshifts will be very difficult to compile for LSST, simulations will play a key role in calibrating estimates of physical properties such as galaxy stellar mass, star formation rate, and other properties. This is particularly problematic for photometric surveys, where photometric redshift and physical property estimates must be calculated jointly. In addition, we must include prominent effects that will influence the expected photometric performance; for example, the presence of an active galactic nucleus can significantly impact the color of a galaxy and the inferred values for the physical parameters, so models of AGN components of varying strength must also be included in simulations. \\ +~\\ + Many current-generation simulations cannot or do not simultaneously match observed color distributions and physical property characteristics for the galaxy population at high redshift. As photo-$z$ algorithms are highly dependent on accurate photometry, realistic color distributions are required to test the bivariate redshift-physical property estimates. Working with the galaxy simulations and high redshift galaxy working groups to develop new simulations with more accurate high redshift colors is a priority. These photo-$z$ needs are not unique, and the improved simulations will benefit both the Galaxies Collaboration and other science collaborations. Indeed, one fruitful way to proceed with this work may be to incorporate new tests into the DESCQA framework being used by the LSST Dark Energy Science Collaboration to improve mock catalogs for DESC work (Mao et al. 2017, in prep.). } +~\\ \activities{ -The main activity for this task is to bring together the knowledge gained from observational studies of high redshift galaxies to act as input for improved simulation metrics. This will require expertise from the photo-z group, the high redshift galaxies group, the AGN group, and the simulations group. In order to test whether mock high-z populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions. Assuming that the simulations are valid beyond the test intervals, we can then test bivariate photo-z/physical process determinations to develop improved algorithms. -} +The main activity for this task is to develop improved simulation metrics based upon observational studies of both low- and high-redshift galaxies. This will require expertise from the photo-$z$ high-redshift galaxies, AGN, and simulations working groups. In order to test whether mock galaxy populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions.\\ +~\\ +If we then assume that the simulations are valid beyond the test intervals, we can use them as a testbed to develop improved algorithms for a wide variety of applications, e.~g.~selecting specific sub-populations of galaxies. +One key aspect of this work is that spectral energy distributions in simulations cannot be generated from discrete templates, but instead must span a continuous range of properties. If only a finite set of restframe SEDs are used in the simulation, the photo-$z$ problem would be unnaturally simplified and falsely strong photometric redshift predictions would result. Thus a method is required that simultaneously reproduces galaxy colors without resorting to a restricted set of SEDs. For example, this could be done by creating complete SEDs based on an extended set of principal components (e.g., extending the $kcorrect$ or EAZY basis set), though in general additional constraints are required with PCA-like techniques to ensure that unphysical spectra are not generated.\\ +~\\ +With sufficiently realistic simulations that reproduce the ensemble of galaxy star formation histories and the mapping between those histories and spectral energy distributions, we can use simulated catalogs to test techniques for identifying specific galaxy sub-populations. For some studies, we may wish to examine the relationship between galaxies in specific sub-populations and their large-scale structure environment. Thus, realistic density and clustering properties are also important in the simulation. There are a wide variety of techniques that may be used for environmental measures, operating on a variety of scales. As small-scale measurements can be noisy and/or washed out by photometric redshift errors, it may be more effective to measure the average overdensity/environment as a function of galaxy properties, rather than the reverse.\\ +~\\ +} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Determination of a list of which physical parameters are important for galaxy science. \item Compiling observable datasets that can be used as comparators for simulated datasets. -\item Developing a set of metrics to compare simulations to the observational data. +\item Developing a set of metrics to compare simulations to the observational data. These may be implemented in the DESCQA framework. \item Use the metrics in deliverable B to create updated simulations with more realistic parameter distributions. \item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc.). +\item Development of improved spectral extended basis sets to create galaxy colors which match observations, including emission lines, etc. +\item Using mock catalogs, developing techniques that for selecting specific galaxy sub-samples. +\item Developing environment estimators for simulated datasets and algorithms able to measure the strength of environmental dependence on galaxy properties. \end{enumerate} } \end{task} -\subsection{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} -\tasktitle{Using Galaxy Size and Surface Brightness distributions as Photo-z Priors} +\subsection{Incorporating Galaxy Size and Surface Brightness into Photometric Redshift Estimates} +\tasktitle{Incorporating Galaxy Size and Surface Brightness into Photometric Redshift Estimates} \begin{task} \label{task:photo_z:size_and_sb_priors} \motivation{ -Photometric redshift algorithms traditionally use galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information in the form of the galaxy’s size/shape/surface brightness (SB) profile adds additional information that can aid in constraining both the redshift and type of the galaxy, breaking potential degeneracies that using colors alone would miss. Adding type information beyond just the rest frame SED may help to constrain bivariate galaxy properties that correlate with morphological type as well. If sufficient training samples are available, a Bayesian prior on colors and SB profile, p(z|C,SB), can be constructed that should lead to improved photometric redshifts. +Photometric redshift algorithms most commonly have used galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information on a galaxy’s size, shape, overall surface brightness (SB), or detailed surface brightness (SB) profile can provide additional information that can aid in constraining the redshift and/or type of a galaxy, breaking potential degeneracies that using colors alone would miss. Gains can be particularly substantial at low redshift where LSST will at least partially resolve galaxies. Incorporating morphological information may help to improve joint predictions for galaxy properties and redshift as well, at the cost of imposing assumptions about links between morphology and color/SED that may not apply to all galaxies. +If sufficient training samples are available, priors for redshift and SED parameters given morphological parameters, $p(z, SED | P)$, can be constructed that can be incorporated into Bayesian analyses of photometric redshifts and potentially lead to improved constraints on the redshift PDF (i.e., $p(z | P, C )$ , where $P$ represents observed morphological parameters, $C$ represents observed flux/color measurements, and $SED$ represents one or more parameters representing the restframe SED of a galaxy). } +~\\ \activities{ -The primary activity in this task is to develop an algorithm to compute a parameterized SB profile fit (e.g. Sersic index, though other measures may be appropriate) for a large number of galaxies. The algorithm must be fast enough to compute SB profiles for large numbers of galaxies. Simulated datasets may be necessary to calibrate this code in the limits of galaxy sizes approaching the size of the PSF, and in the limit of low signal-to-noise ratios. With SB measurements in hand, the computation of a Bayesian prior on redshift given galaxy photometry and SB. This can be done with either simulated datasets, or real observations with spectroscopic redshifts. Tests will then show the performance of such a prior relative to using galaxy photometry alone. +The first activity for this task will be to assess whether LSST Data Management algorithms for multiple-Sersic model fits to galaxy photometry are sufficient for the needs of this working group. Evaluation of DM pipeline-processed precursor datasets in regions with HST imaging may be particularly valuable. +With measures of morphological parameters in hand, a useful next step would be to evaluate whether photometric redshift estimates in fact improve with the incorporation of morphological information (in the domain where training is perfect, i.e., with training sets and test sets with matching properties); this may be done using machine learning-based codes, which can make maximal use of all information available in the parameter set provided without requiring the development of a detailed model (such methods extrapolate poorly, but that is not a problem for this test). +If incorporating morphological information does in fact yield improvements, the next step would be the development of Bayesian priors for redshift given galaxy photometry and morphology measurements for incorporation into template-based methods. This may be done using either pipeline-processed simulated datasets (if they are sufficiently realistic) or real observations with spectroscopic redshifts. Tests will then show the performance of photometric redshifts incorporating morphological priors relative to performance using galaxy photometry alone. } +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item A fast, scalable algorithm for measuring the surface brightness profile of galaxies. -\item A cross matched catalog with objects at known redshifts and measured surface brightness profiles. -\item A Bayesian prior $p(z|C,SB)$ that can be used to improve photo-z measurements. +\item Tests of LSST DM algorithms for measuring morphological parameters for galaxies. +\item A cross-matched catalog containing objects with known redshifts and DM pipeline-measured morphology measurements. +\item Tests of whether incorporating morphological information improves photometric redshift measurements using machine learning-based algorithms, as well as examination of what parameters are most informative +\item Bayesian priors $p(z, SED | P)$ that can be incorporate into template-based algorithms and used to improve photo-$z$ measurements. \end{enumerate} } \end{task} \end{tasklist} - - - +} diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index fbbea34..b0e1fad 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -1,18 +1,9 @@ - -% LSST Extragalactic Roadmap +% LSST Galaxies Science Roadmap % Chapter: task_lists % First draft by \chapter[Task Lists by Science Area]{Task Lists by Science Area} \label{ch:task_lists} - -%\input{task_lists/chapter_intro.tex} -%\input{task_lists/black_holes/black_holes.tex} -%\input{task_lists/informatics/informatics.tex} -%\input{task_lists/lss/lss.tex} -%\input{task_lists/strong_lensing/strong_lensing.tex} -%\input{task_lists/weak_lensing/weak_lensing.tex} - \input{task_lists/agn/agn.tex} \newpage \input{task_lists/clss/clss.tex} @@ -28,3 +19,5 @@ \input{task_lists/photo_z/photo_z.tex} \newpage \input{task_lists/tmc/tmc.tex} +\newpage +\input{task_lists/aux/aux.tex} diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index bd4ba11..26d3540 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -1,13 +1,13 @@ \section{Theory and Mock Catalogs}\label{sec:tasks:tmc} - +{\justify A critical challenge for interpreting the vast LSST dataset in the context of a cosmological model for galaxy formation -is the development of theory, both in the practical applications +involves the development of theory, both in the practical applications of realistic simulations and the engineering of new physical models for the important processes that govern the observable properties of galaxies. The following preparatory science tasks for LSST-related theoretical efforts range from understanding the -detail properties of galaxies that LSST will uncover to predicting +detailed properties of galaxies that LSST will uncover to predicting the large-scale properties of galaxy populations that LSST will probe on unprecedented scales. @@ -18,17 +18,25 @@ \subsection{Image Simulations of Galaxies with Complex Morphologies} \begin{task} \label{task:tmc:complex_morphology} \motivation{ -LSST images will contain significant information about the dynamical state of galaxies. In principle, this can be exploited to learn about their formation and evolutionary histories. Examples of such features include spiral arms, tidal tails, double nuclei, clumps, warps, and streams. A wide variety of analysis and modeling techniques can be applied to determine the past, present, or future states of observed galaxies with complex morphologies, and therefore improve our understanding of galaxy assembly. +LSST images will contain significant information about the dynamical state of galaxies. In principle, we can exploit +this morphological information to learn about the formation and evolutionary histories +of both individual and populations of galaxies. +Examples of important morphological features include spiral arms, tidal tails, double nuclei, clumps, warps, and streams. +A wide variety of analysis and modeling techniques can help determine the past, present, or future states of observed galaxies with complex morphologies, +and thereby improve our understanding of galaxy assembly. } +~\\ \activities{ -Activities include creating synthetic LSST observations containing a wide variety of galaxies with complex morphologies, for the purpose of testing analysis algorithms such as de-blending, photometry, and morphological characterization. Supporting activities include creating databases of galaxy images from models (such as cosmological simulations) or existing optical data, analyzing them using LSST software or prototype algorithms, and distributing the findings of these studies. These analyses can be performed on small subsets of the sky and do not necessarily have to include very-large-area image simulations or match known constraints on source density. Results will include predicting the incidence of measured morphological features, optimizing level-3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} +Activities include creating synthetic LSST observations containing a wide variety of galaxies with complex morphologies, for the purpose of testing analysis algorithms such as de-blending, photometry, and morphological characterization. Supporting activities include creating databases of galaxy images from models (such as cosmological simulations) or existing optical data, analyzing them using LSST software or prototype algorithms, and distributing the findings of these studies. These analyses may involve small subsets of the sky and do not necessarily require very-large-area image simulations or need to match known constraints on source density. +Results will include predicting the incidence of measured morphological features, optimizing level-3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Creating synthetic LSST images of galaxies with complex morphology from simulations. \item Creating synthetic LSST images based on prior observations in similar filters. -\item Making these LSST-specific complex galaxy data products widely available. -\item Publicizing results of algorithm tests based on these simulations. -\item Assessing level-3 measurements to propose and/or apply to maximize the return of LSST catalogs for complex galaxy morphology science. +\item Making LSST-specific complex galaxy data products widely available. +\item Publicizing results from algorithm tests based on these LSST simulations. +\item Assessing Level 3 measurements to propose and/or apply in maximizing the return of LSST catalogs for complex galaxy morphology science. \end{enumerate} } \end{task} @@ -39,16 +47,35 @@ \subsection{New Theoretical Models for the Galaxy Distribution} \begin{task} \label{task:tmc:galaxy_distribution} \motivation{ -Our aim is to bring together key areas of expertise to meet the challenge of building synthetic, computer generated mock surveys which will be used in the preparation for Galaxy science with LSST. Surveys like LSST will collect more data than is contained in the current largest survey, the SDSS, every night for ten years. The analysis of such data demands a complete overhaul of traditional techniques and will require the incorporation of ideas from different disciplines. The mock catalogs we will produce offer the best means to test and constrain theoretical models using observational data. -Computer mock catalogs play a well established role in modern galaxy surveys. For the first time, the scientific potential of the new surveys will be limited by systematic errors rather than sampling errors driven by the volume mapped. The signals from viable, competing cosmological models are already extremely close. Distinguishing between the models requires that we build the best possible theoretical predictions to understand the measurements and how they should be analyzed. We also need to understand the errors on the measurements. +OMeeting the challenge of building synthetic, computer-generated mock surveys for use in the preparation +of extragalactic science with LSST will require the assembly of experts in key theoretical areas. +LSST will collect more data than contained in the current largest survey, the SDSS, +every night for ten years. The analysis of such data demands a complete overhaul of traditional techniques and will require the incorporation of ideas from different disciplines. +Mock catalogs +offer the best means to test and constrain theoretical models using observational data, and +play a well-established role in modern galaxy surveys. +For the first time, systematic uncertainties will limit +the scientific potential of the new surveys, rather than sampling errors driven by the volume mapped. +A variety of viable, competing cosmological models already provide only subtly discernable +signals in survey data. +Distinguishing between the models requires that we build the best possible theoretical predictions to understand the measurements and their subsequent analysis, and to +understand the uncertainties on the measurements. } +~\\ \activities{ -Develop a new state-of-the-art in physical models of the galaxy distribution combining models of the physics of galaxy formation with high resolution N-body simulations which track the hierarchical growth of structure in the matter distribution. The key task is to take the results of calculations in moderate volume cosmological N-body simulations and to develop schemes to embed this information into very large volume simulations. The large volume simulations will be bigger than the target survey, allowing a robust assessment of the systematic errors on large-scale structure measurements.} +Develop a new state-of-the-art in physical models of the galaxy distribution by +combining models of the physics of galaxy formation with high resolution N-body simulations that track the hierarchical growth of structure in the matter distribution. +The key task involves performing moderate volume cosmological N-body simulations, generating +predictions from an associated model of galaxy formation, and then embedding +this information into very large volume simulations that can represent LSST datasets. +The large volume simulations will extend beyond the volume of the target survey, +allowing a robust assessment of the systematic uncertainties on large-scale structure measurements.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Physically motivated mock galaxy catalogues on volumes larger than will be sampled by LSST, with a consistently evolving population of galaxies. -\item Base catalogues of dark matter haloes and their merger trees that will be available for other theoretical models of populating these with galaxies (halo and subhalo occupation/abundance matching techniques). -\item Small volume simulations for further tests. +\item Physically motivated mock galaxy catalogues on volumes larger than those sampled by LSST, with a consistently evolving population of galaxies. +\item Base catalogues of dark matter haloes and their merger trees suitable for use by theoretical models for populating these with galaxies (halo and subhalo occupation/abundance matching techniques). +\item Small volume simulations for further tests of baryonic physics and detailed observational comparisons. \end{enumerate} } \end{task} @@ -58,13 +85,30 @@ \subsection{Design of New Empirical Models for the Galaxy Distribution.} \begin{task} \label{task:section:title} \motivation{ -We will explore the galaxy-halo connection, using the simulations of the galaxy formation process as encapsulated in physically motivated models to build better empirical models. Empirical models can be adjusted to reproduce observational results as closely as possible, whereas physical models are computationally expensive, so only a small number of examples can be run, and the results cannot be tuned in the same way. Empirical models also have the advantage of being extremely fast, allowing large parameter spaces to be explored. +The galaxy-halo connection represents the end state of the combined physics of baryonic galaxy formation and dark matter structure formation processes. +A full exploitation of the LSST dataset for understanding galaxy formation will +necessarily involve the exploration of the galaxy-halo connection, +using the simulations of the galaxy formation process to build better empirical models. +Empirical models can adjust to reproduce observational results as closely as possible, whereas computationally expensive physical models often prove too expensive to +tune in the same manner. +Empirical models also have the advantage of being extremely fast, allowing large parameter spaces to be explored. } +~\\ \activities{ -There are two stages here: one is to test current models to see how well they can reproduce the predictions of physical models and the second is to use the physical models to devise new parametrizations to describe galaxy selections for which there is little or no current observational data. This is particularly relevant for upcoming surveys which will probe regimes that remain largely unmapped.} +Developing models of the galaxy-halo connection for LSST require two main stages. The +first step tests current empirical models to judge the fidelity with which they +reproduce the predictions of physical models based on simulations. The second step +uses physical models to devise new parameterizations for empirical models to +describe galaxy populations for which little or no data yet exists, providing enhanced +empirical models relevant for upcoming surveys that will probe regimes that remain +largely unmapped.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item The evolution of the clustering predicted by the physical models may allow us to model how parameters should change in the empirical models, thereby reducing the number of parameters which we need to fit and to populate catalogs on the observer’s past lightcone. +\item Predictions for the evolution of clustering from physical models. +\item Enhanced paramertizations for empirical models with reduced freedom, greater +applicability, and more rapid population of catalogs to describe the observer's past +lightcone. \end{enumerate} } \end{task} @@ -75,11 +119,13 @@ \subsection{Estimating Uncertainties for Large-Scale Structure Statistics} \begin{task} \label{task:tmc:uncertainties} \motivation{ -The ability to interpret the relation between galaxies and the matter density field will depend critically on how well we understand the errors on large-scale structure measurements. The accurate estimation of the covariance on a large-scale structure measurement such as the correlation function would require tens of thousands of simulations. +The ability to interpret the relation between galaxies and the matter density field will depend critically on how well we understand the uncertainties of large-scale structure measurements. The accurate estimation of the covariance on a large-scale structure measurement such as the correlation function would require tens of thousands of simulations. } +~\\ \activities{ -Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, based for example on perturbation theory. -Coordinate with WGs of the Dark Energy Science Collaboration as these covariance matrices can also be applied to Cosmological parameter constraints.} +Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, such as those based on perturbation theory. +Coordinate with Dark Energy Science Collaboration Working Groups, as these covariance matrices can also inform Cosmological parameter constraints.} +~\\ \deliverables{Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Physically motivated estimates of covariance matrices for galaxy occupation (and other) parameter searches. @@ -87,3 +133,4 @@ \subsection{Estimating Uncertainties for Large-Scale Structure Statistics} } \end{task} \end{tasklist} +} From d8e7b86bf16e2329263f33aa4d04417a627f6442 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 19 Jul 2017 22:18:19 -0700 Subject: [PATCH 23/64] Changes to introduction. --- introduction/introduction.tex | 27 ++++++++++++--------------- references.bib | 11 +++++++++++ task_lists/agn/agn.tex | 6 +++--- task_lists/aux/aux.tex | 14 +++++++------- task_lists/clss/clss.tex | 6 +++--- task_lists/galaxies/galaxies.tex | 8 ++++---- task_lists/photo_z/photo_z.tex | 4 ++-- 7 files changed, 42 insertions(+), 34 deletions(-) diff --git a/introduction/introduction.tex b/introduction/introduction.tex index c56c1ba..9ffb62a 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -7,15 +7,15 @@ {\justify The Large Synoptic Survey Telescope (LSST) is a wide-field, ground-based -telescope, designed to image a substantial fraction of the sky in six optical +observatory designed to image a substantial fraction of the sky in six optical bands every few nights. -The observatory will operate for at least a decade, allowing the +The observatory will operate for at least a decade, allowing stacked images to detect galaxies to redshifts well beyond unity. LSST and its Deep-Wide-Fast and Deep Drilling Field surveys will meet the requirements of a broad range of science goals in astronomy, astrophysics and cosmology \citep{ivezic2008a}. The LSST ranked first among large ground-based initiatives in the -2010 National Academy of Sciences decadal survey in astronomy and astrophysics, +2010 National Academy of Sciences decadal survey in astronomy and astrophysics \citep{nrc2010a}, and will begin survey operations early in the next decade. This document, the {\it Large Synoptic Survey Telescope Galaxies Science Roadmap}, outlines critical preparatory research efforts needed to leverage fully the power of LSST for extragalactic science. @@ -24,15 +24,15 @@ focus on a broad range of topics in astronomy and cosmology that the LSST could address. Members of these collaborations have proven instrumental in helping to develop the science case for LSST (encapsulated in the LSST Science Book; -\citet{LSSTSciBook}), to -refine the concepts for the survey and for the data processing, and to educate +\citealt{LSSTSciBook}), +refine the concepts for the survey and for the data processing, and educate other scientists and the public about the promise of this unique observatory. The Dark Energy Science Collaboration (DESC) has taken the -next logical step beyond the science book. They identified they most critical +next logical step beyond the Science Book. They identified they most critical challenges the community will need to overcome to realize LSST’s potential for -measuring the nature and effects of Dark Energy. The +measuring the nature and effects of dark energy. The DESC looked at five complementary techniques for tackling dark energy, and outlined high-priority tasks for their Science Collaboration during construction. The DESC designated sixteen @@ -43,7 +43,7 @@ overall DESC preparatory science effort, indicates clearly the importance of the advance work, and connects individual research projects together into a broader -enterprise to enable Dark Energy science with LSST. +enterprise to enable dark energy science with LSST. Following the lead of DESC, several other LSST community organizations including the AGN, Milky Way and Local Volume, and Solar System Science @@ -51,24 +51,21 @@ started to develop Roadmaps to outline critical preparatory tasks in their science domains. This document, led by members of the LSST Galaxies Science Collaboration, -acts as an Roadmap for extragalactic science covering +acts as a Roadmap for extragalactic science covering galaxy formation and evolution writ large, the influence of dark matter structure formation on the properties of galaxy populations, and the impact of supermassive black holes on their host galaxies. This Roadmap identifies the major high-level science themes of these investigations, outlines how complementary techniques will contribute, and identifies areas where advance work will prove essential. For this -advance work, the Extragalactic Roadmap emphasizes areas that are not adequately +preparatory work, the {\it Galaxies Science Roadmap} emphasizes areas that are not adequately covered in the DESC Roadmap. -%As convenient shorthand, we use the acronym GALLA (Galaxies, AGN, Lensing -%Large-scale Structure and Astro-informatics) joint roadmap of the overlapping -%science collaborations. -Chapter \ref{ch:science_background} gives a brief summary of the science background. +Chapter \ref{ch:science_background} gives a brief summary of the LSST galaxies science background. Many of the themes and projects are already set out in the LSST Science Book, which provides more details for many of the science investigations. Chapter \ref{ch:task_lists} presents preparatory science tasks for -Extragalactic science with LSST. These tasks are organized by science topic. +extragalactic science with LSST, organized by science topic. The science task list content assumes that the work plan of the DESC will be executed and that the resulting software and other data products resulting from the DESC efforts will be made available to the other science collaborations. diff --git a/references.bib b/references.bib index 8d1938f..0e791bf 100644 --- a/references.bib +++ b/references.bib @@ -26,6 +26,17 @@ @ARTICLE{LSSTDESC adsurl = {http://adsabs.harvard.edu/abs/2012arXiv1211.0310L}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@BOOK{nrc2010a, + author = "National Research Council", + title = "New Worlds, New Horizons in Astronomy and Astrophysics", + isbn = "978-0-309-15799-5", + doi = "10.17226/12951", + abstract = "Driven by discoveries, and enabled by leaps in technology and imagination, our understanding of the universe has changed dramatically during the course of the last few decades. The fields of astronomy and astrophysics are making new connections to physics, chemistry, biology, and computer science. Based on a broad and comprehensive survey of scientific opportunities, infrastructure, and organization in a national and international context, New Worlds, New Horizons in Astronomy and Astrophysics outlines a plan for ground- and space- based astronomy and astrophysics for the decade of the 2010's.\nRealizing these scientific opportunities is contingent upon maintaining and strengthening the foundations of the research enterprise including technological development, theory, computation and data handling, laboratory experiments, and human resources. New Worlds, New Horizons in Astronomy and Astrophysics proposes enhancing innovative but moderate-cost programs in space and on the ground that will enable the community to respond rapidly and flexibly to new scientific discoveries. The book recommends beginning construction on survey telescopes in space and on the ground to investigate the nature of dark energy, as well as the next generation of large ground-based giant optical telescopes and a new class of space-based gravitational observatory to observe the merging of distant black holes and precisely test theories of gravity.\nNew Worlds, New Horizons in Astronomy and Astrophysics recommends a balanced and executable program that will support research surrounding the most profound questions about the cosmos. The discoveries ahead will facilitate the search for habitable planets, shed light on dark energy and dark matter, and aid our understanding of the history of the universe and how the earliest stars and galaxies formed. The book is a useful resource for agencies supporting the field of astronomy and astrophysics, the Congressional committees with jurisdiction over those agencies, the scientific community, and the public.\n ", + url = "https://www.nap.edu/catalog/12951/new-worlds-new-horizons-in-astronomy-and-astrophysics", + year = 2010, + publisher = "The National Academies Press", + address = "Washington, DC" +} %AAAAAAAAAAA @ARTICLE{abraham1994a, author = {{Abraham}, R.~G. and {Valdes}, F. and {Yee}, H.~K.~C. and {van den Bergh}, S. diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index b9eebe9..d94b53f 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -176,8 +176,8 @@ \subsection{AGN Photometric Redshifts from LSST Data} %\end{tasklist} %\begin{tasklist}{T} -\subsection{AGN Merger Signature from LSST Data} -\tasktitle{AGN Merger Signature from LSST Data} +\subsection{AGN Merger Signatures from LSST Data} +\tasktitle{AGN Merger Signatures from LSST Data} \begin{task} \label{task:agn:mergers} \motivation{ @@ -204,4 +204,4 @@ \subsection{AGN Merger Signature from LSST Data} } \end{task} \end{tasklist} -} \ No newline at end of file +} diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex index 80efe14..9ce7445 100644 --- a/task_lists/aux/aux.tex +++ b/task_lists/aux/aux.tex @@ -5,8 +5,8 @@ \section{Auxiliary Data}\label{sec:tasks:aux} \begin{tasklist}{AUX} -\subsection{A database of extra-galactic optical/NIR spectroscopy within the LSST footprint} -\tasktitle{AUX} +\subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} +\tasktitle{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} \begin{task} \label{task:aux:spectroscopy} \motivation{ @@ -45,10 +45,10 @@ \subsection{A database of extra-galactic optical/NIR spectroscopy within the LSS -\subsection{A Universal database of panchromatic imaging within the LSST footprint} -\tasktitle{AUX} +\subsection{Panchromatic Imaging within the LSST Footprint} +\tasktitle{Panchromatic Imaging within the LSST Footprint} \begin{task} -\label{task:lsb:panchromatic} +\label{task:aux:panchromatic} \motivation{ LSST will only cover a small portion of the electro-magnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life-cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available x-ray, UV, IR, and radio data. \\ @@ -91,8 +91,8 @@ \subsection{A Universal database of panchromatic imaging within the LSST footpri } \end{task} -\subsection{Tully-Fisher with LSST and SKA Pathfinders} -\tasktitle{AUX} +\subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} +\tasktitle{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} \begin{task} \label{task:HI} \motivation{ diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 23a8198..7157a4f 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -276,8 +276,8 @@ \subsection{Disentangling Complicated Lines of Sight} -\subsection{Forward Modeling LSST Clusters and Groups} -\tasktitle{Forward Modeling LSST Clusters and Groups} +\subsection{Forward Modeling of LSST Clusters and Groups} +\tasktitle{Forward Modeling of LSST Clusters and Groups} \begin{task} \label{task:clss:cluster_fm} \motivation{ @@ -339,4 +339,4 @@ \subsection{Forward Modeling LSST Clusters and Groups} \end{tasklist} -} \ No newline at end of file +} diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 96a8964..1d7849a 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -224,8 +224,8 @@ \subsection{Optimizing Galaxy Morphology Measurements} \end{task} -\subsection{Galaxy structural parameters} -\tasktitle{Galaxy structural parameters} +\subsection{Galaxy Structural Parameters} +\tasktitle{Galaxy Structural Parameters} \begin{task} \label{task:gal:struc_param} @@ -247,8 +247,8 @@ \subsection{Galaxy structural parameters} \end{task} \bigskip -\subsection{Optimizing galaxy mass profile measurement} -\tasktitle{Optimizing galaxy mass profile measurement} +\subsection{Optimizing Galaxy Mass Profile Measurements} +\tasktitle{Optimizing Galaxy Mass Profile Measurements} % foreground lens galaxy sample selection % completeness % shear simulations diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index 9b0516a..056b243 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -8,8 +8,8 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} It is important to note that a major effort within the LSST Dark Energy Science Collaboration (DESC) is focused on the development of photometric redshift algorithms for LSST, including the incorporation of joint probability distributions between redshift and astrophysical parameters of interest for the study of galaxy evolution. Efforts within the Galaxies collaboration should be able to leverage work happening in DESC and build upon it to ensure that photometric redshifts optimized for galaxy science are available. \begin{tasklist}{PZ} -\subsection{Impact of Filter Variations on Galaxy photo-$z$ Precision} -\tasktitle{Impact of Filter Variations on Galaxy photo-$z$ Precision}\label{pzfiltervar} +\subsection{Impact of Filter Variations on Galaxy Photometric Redshift Precision} +\tasktitle{Impact of Filter Variations on Galaxy Photometric Redshift Precision}\label{pzfiltervar} \begin{task} \label{task:photo_z:filter_variations} \motivation{ From cf059f9533b8e2b836a285408b030d098577635e Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 19 Jul 2017 22:56:16 -0700 Subject: [PATCH 24/64] Edits to science background. --- introduction/introduction.tex | 4 +- science_background/science_background.tex | 68 ++++++++++++++--------- task_lists/lsb/lsb.tex | 16 +++--- 3 files changed, 53 insertions(+), 35 deletions(-) diff --git a/introduction/introduction.tex b/introduction/introduction.tex index 9ffb62a..83fa022 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -17,7 +17,7 @@ The LSST ranked first among large ground-based initiatives in the 2010 National Academy of Sciences decadal survey in astronomy and astrophysics \citep{nrc2010a}, and will begin survey operations early in the next decade. -This document, the {\it Large Synoptic Survey Telescope Galaxies Science Roadmap}, outlines critical preparatory research efforts needed +This document, the {\it LSST Galaxies Science Roadmap}, outlines critical preparatory research efforts needed to leverage fully the power of LSST for extragalactic science. In 2008, eleven separate quasi-independent science collaborations were formed to @@ -58,7 +58,7 @@ This Roadmap identifies the major high-level science themes of these investigations, outlines how complementary techniques will contribute, and identifies areas where advance work will prove essential. For this -preparatory work, the {\it Galaxies Science Roadmap} emphasizes areas that are not adequately +preparatory work, the {\it LSST Galaxies Science Roadmap} emphasizes areas that are not adequately covered in the DESC Roadmap. Chapter \ref{ch:science_background} gives a brief summary of the LSST galaxies science background. diff --git a/science_background/science_background.tex b/science_background/science_background.tex index 31b6b9f..9a6da5d 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -48,7 +48,7 @@ dark matter structures allows for astronomers to achieve gains in each field using the same datasets. -The Large Synoptic Survey Telescope (LSST) will provide a +LSST will provide a digital image of the southern sky in six bands ($ugrizy$). The area ($\sim18,000~\mathrm{deg}^2$) and depth ($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of @@ -58,11 +58,11 @@ For studies of galaxies, LSST provide both an unequaled catalogue of billions of extragalactic sources and high-quality multiband imaging of individual objects. This section of -the {\it Galaxies Science Roadmap} presents scientific +the {\it LSST Galaxies Science Roadmap} presents scientific background for studies of these galaxies with LSST to provide a context for considering how the astronomical community can best leverage the catalogue and imaging datasets and for -identifying any required preparatory science tasks. +identifying required preparatory science tasks. LSST will begin science operations during the next decade, more than twenty years after the start of the Sloan @@ -86,8 +86,8 @@ \section{Star Formation and Stellar Populations in Galaxies} Light emitted by stellar populations will provide all the direct measurements made by LSST. This information will be filtered through -the six passbands utilized by the survey -($ugrizy$), providing constraints on the +the six passbands utilized by the survey, +providing constraints on the rest-frame ultraviolet SEDs of galaxies to redshift $z\sim6$ and a probe of rest-frame optical spectral breaks to $z\sim1.5$. By @@ -170,7 +170,7 @@ \section{Star Formation and Stellar Populations in Galaxies} Deep Extragalactic Survey \citep{grogin2011a,koekemoer2011a}. While LSST will be comparably limited in redshift -selection, its $~30,000$ times larger area +selection, its $\sim30,000$ times larger area will enable a much fuller sampling of the star formation--stellar mass plane, allowing for a characterization of the distribution @@ -227,7 +227,7 @@ \section{Galaxies as Cosmic Structures} of the light distribution including the Gini and M20 metrics that quantify the surface brightness uniformity and spatial moment of -dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume of the LSST dataset, which will also change on short timescales in terms of depth, new machine-learning algorithms \citep[e.g.][]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume of the LSST dataset, which will also change on short timescales in terms of depth, new machine-learning algorithms \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided by analyzing the LSST imaging data will enable a consummate determination of the relation between structural properties and other features of @@ -288,7 +288,8 @@ \section{Galaxies as Cosmic Structures} wide variation in environments probed by a survey of half the sky, the image quality of LSST will permit studies of galaxy structures in the very low surface -brightness regime. This will allow for the characterization of stellar halos that +brightness regime. This capability +will allow for the characterization of stellar halos that surround nearby galaxies. Structures in stellar halos, such as tidal features produced by mergers and interactions and density inhomogeneities, originate from the hierarchical formation process and their @@ -296,15 +297,21 @@ \section{Galaxies as Cosmic Structures} on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. Observational studies using small, deep surveys like the SDSS Stripe 82 \citep[e.g.][]{kaviraj2014a,kaviraj2014b} and recent work using small telescopes \citep{martinez-delgado2008a,atkinson2013,abraham2014a,van_dokkum2014a} have -demonstrated the critical importance of probing the low surface-brightness Universe in order to test the hierarchical galaxy formation paradigm. Since low-mass galaxies far outnumber their massive counterparts, the assembly history of massive galaxies is dominated by mergers of unequal mass ratios (`minor' mergers). However, such mergers typicaly produce tidal features that are fainter than the surface brightness limits of current surveys like the SDSS. Hence, the vast majority of merging remains, from an empirical point of view, unquantified. In other words, deep wide surveys like LSST, with its unrivalled entendue, are crucial for empirically testing the hierarchical paradigm and understanding the role of galaxy merging in driving star formation, black hole growth and morphological transformation over cosmic time \citep{kaviraj2014b}. - -Furthermore, the examination of stellar halos around galaxies will +demonstrated the critical importance of probing the low surface brightness universe +in order to test the hierarchical galaxy formation paradigm. +Since low-mass galaxies far outnumber their massive counterparts, the assembly history of massive galaxies is dominated by mergers of unequal mass ratios (`minor' mergers). +However, such mergers typically produce tidal features that are fainter +than the surface brightness limits of current surveys like the SDSS. +Hence, the majority of merging remains, from an empirical point of view, unquantified. +Deep-wide surveys like LSST are crucial for empirically testing the hierarchical paradigm +and understanding the role of galaxy merging in driving star formation, black hole growth, and morphological transformations over cosmic time \citep{kaviraj2014b}. +The examination of stellar halos around galaxies will result in the identification of small mass satellites whose sizes, luminosities, and abundances can constrain the nature of dark matter and models of the galaxy formation process at the extreme low-mass end of the mass function. -Finally, observational measures of the outermost regions of thin disks can constrain +Finally, observational measures of the outermost regions of thin disks can reveal how such disks ``end'', how dynamical effects might truncate disks, and whether some disks smoothly transition into stellar halos. LSST will provide such measures and help quantify the @@ -322,8 +329,8 @@ \section{Galaxies as Cosmic Structures} The LSST survey uniquely enables precision statistical studies of galaxy mass -distribution via weak gravitational lensing of the 40 background -galaxies per square arcminute. From the radial dependence of +distribution via weak gravitational. +From the radial dependence of the galaxy-mass correlation function, galaxy morphological properties can be compared with the mass distribution, as a function of redshift of the lens galaxy population (Choi et al. 2012, @@ -332,7 +339,7 @@ \section{Galaxies as Cosmic Structures} mapping of samples of hundreds of thousands of dwarf galaxies. With a sample of hundreds of millions of foreground galaxies, for the first time trends in galaxy stellar evolution and type -can be correlated with halo mass and mass environment out beyond several Mpc. +can be correlated with halo mass and mass environment on cosmological scales. \section{Probing the Extremes of Galaxy Formation} \label{sec:sci:gal:bkgnd:rare} @@ -357,7 +364,7 @@ \section{Probing the Extremes of Galaxy Formation} early times may immediately proceed the formation of bright quasars. LSST has all the requisite survey properties (area, mutliband imaging, and -depth) to investigate this long-standing problem. +depth) to investigate this long-standing problem \citep{robertson2007a}. The creation of LSST Deep Drilling fields will enable a measurement of the very bright end @@ -376,7 +383,7 @@ \section{Probing the Extremes of Galaxy Formation} fields satisfy this need by achieving sensitivities beyond the rest of the survey. -Lastly, the spatial rarity of extreme objects discovered +The spatial rarity of extreme objects discovered in the wide LSST area may reflect an intrinsically small volumetric density of objects or the short duration of an event that gives rise to the observed properties of the @@ -398,16 +405,27 @@ \section{Probing the Extremes of Galaxy Formation} \section{Photometric Redshifts} \label{sec:sci:gal:bkgnd:photoz} -As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, lacking a spectroscopic component, adding the third dimension of cosmic distance to each galaxy must come from calculating photometric redshifts (photo-$z$'s). Spectroscopic distance estimates rely on expensive (in terms of telescope time and resources) identification of atomic or molecular transitions in high resolution spectra. In contrast, photometric redshifts estimate the rough distance to an object based on its broad-band photometric colors (and, potentially, other properties measurable from imaging). The measurement of a photo-$z$ can be thought of as akin to determining redshifts from a very low-resolution but high signal-to-noise spectrum, with each broad-band filter contributing a single pixel to that spectrum. They are therefore sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.,~the 4000~\AA\ and Lyman breaks), but in general lack the definitiveness of a redshift measured from multiple well-centroided spectral features (e.g., a pair of emission or absorption lines of known separation). As a result, photometric redshifts will generally be more uncertain than spectroscopic redshift estimates and can be affected by degeneracies in the color-redshift relation. +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. +However, the third dimension of cosmic distance to each galaxy must often +come from photometric redshifts (photo-$z$'s). +Spectroscopic distance estimates rely on the identification of atomic or molecular transitions in expensive, +high resolution spectra. In contrast, photometric redshifts estimate the rough distance to an object based on its broad-band photometric colors and, potentially, other properties measurable from imaging. +Photo-$z$ measurements are akin to determining redshifts from a very low-resolution but high signal-to-noise spectrum, where each broad-band filter contributes a single sample in that spectrum. Photometric +redshifts are therefore sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.,~the 4000~\AA\ and Lyman breaks), but in general lack the definitiveness of a redshift measured from multiple well-centroided spectral features (e.g., a pair of emission or absorption lines of known separation). As a result, photometric redshifts will generally be more uncertain than spectroscopic redshift estimates and can be affected by degeneracies in the color-redshift relation. -By relying on imaging data alone, we will be able to measure photo-$z$'s for billions of galaxies in the LSST survey. -As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys. For example, assigning an incorrect redshift to a galaxy also assigns it an incorrect luminosity (due to misestimation of both the distance modulus and $k$-corrections), and hence can bias estimates of the luminosity function. Errors in redshift will also bias the inferred restframe colors of a galaxy, propagating to errors in the inferred spectral type, stellar mass, star formation rate, and other quantities. Estimating any physical quantities should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if we plan to make measurements in an unbiased way. +By relying on imaging data alone, we will be able to measure photo-$z$'s for billions of galaxies in the LSST survey. +As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys.Assigning an incorrect redshift to a galaxy also assigns an incorrect luminosity +owing to misestimation of both the distance modulus and $k$-corrections, and hence can bias estimates of the luminosity function. Errors in redshift will also bias the inferred rest-frame colors of a galaxy, propagating to errors in the inferred spectral type, stellar mass, star formation rate, and other quantities. +Ideally, estimates of any physical quantity should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if measurements are to be +made in an unbiased way. -In order to develop optimal estimates of photo-$z$'s for a particular survey, we need to train the photo-z algorithms using a set of galaxies with known redshifts. If spectroscopy is obtained for a fully representative sub-sample of the underlying galaxy population spanning the full domain of application, this spectroscopy can also be used to characterize the biases and uncertainties in the photometric redshift estimates, calibrating their use for science. +To develop optimal estimates of photo-$z$'s for a particular survey, photo-$z$ algorithms +should be trained using a set of galaxies with known redshifts. If spectroscopy is obtained for a fully representative sub-sample of the underlying galaxy population spanning the full domain of application, this spectroscopy can also be used to characterize the biases and uncertainties in the photometric redshift estimates, calibrating their use for science. -However, in practice, obtaining such a fair sample will be very difficult to achieve due to limitations in spectroscopic instrumentation, telescope time, and the astrophysical properties of galaxies (e.g., objects with only extremely weak spectral features are exceedingly difficult to measure redshifts for). We can attempt to identify and remove any biases due to incomplete training data using a variety of redshift calibration techniques; the most prominent one relies on spatially cross-correlating photo-z selected data sets with a sample of objects with secure redshifts over wide fields, as will be provided by DESI and 4MOST \citep{newman2008a}. A detailed plan describing the spectroscopic needs for training and calibrating photometric redshifts for LSST is laid out in \citet[]{newman2015a}, which also details potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be available in the near future. +Obtaining such a fair spectroscopic sample for LSST will be very difficult to achieve due to limitations in instrumentation, telescope time, and the astrophysical properties of galaxies (e.g., weak spectral features). +Biases owing to incomplete training data can be identified and removed using a variety of redshift calibration techniques, such as spatially cross-correlating photo-$z$-selected datasets with a sample of objects with secure redshifts over wide fields, as will be provided by DESI and 4MOST \citep{newman2008a}. A detailed plan describing the spectroscopic needs for training and calibrating photometric redshifts for LSST is laid out in \citet[]{newman2015a}, where potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be available in the near future are detailed. -As a nearly representative set of galaxies designed to span all relevant galaxy properties, this data set could prove very useful not only for photo-$z$ training, but also to help us to study galaxy formation and evolution. The insights about the formation and evolution of galaxies we expect to gain from LSST can also be used to improve photo-$z$ algorithms, both by constraining the family of spectral energy distributions of galaxies as a function of redshift and by improving our knowledge of distributions of other observable quantities such as size and surface brightness. This mutual synergy between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both areas as the survey progresses. +The insights about the formation and evolution of galaxies we expect to gain from LSST can also be used to improve photo-$z$ algorithms, both by constraining the family of spectral energy distributions of galaxies as a function of redshift and by improving our knowledge of distributions of other observable quantities such as size and surface brightness. This mutual synergy between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both areas as the survey progresses. \vspace{-0.05in} \section{Science Book} @@ -417,7 +435,7 @@ \section{Science Book} detailed descriptions of foundational science enabled by LSST. The LSST Galaxies Science Collaboration authored the Chapter 9 ``Galaxies'' of the Science Book, and the -table of contents of that chapter follow below to +table of contents of that chapter follows below to provide an example list of topics in extragalactic science that LSST data will help revolutionize. The interested reader is referred to the LSST Science @@ -460,4 +478,4 @@ \section{Science Book} \item Special Populations of Galaxies \item Public Involvement \end{enumerate} -} \ No newline at end of file +} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 8b434be..13e27fe 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -1,15 +1,15 @@ -\section{Low-Surface Brightness Science}\label{sec:tasks:lsb} +\section{Low Surface Brightness Science}\label{sec:tasks:lsb} {\justify The exquisite data quality of LSST will open up a brand new regime in -low-surface brightness (LSB) science, over unprecedentedly large areas of the sky. LSST's unique deep-wide capabilities will enable us to uncover new evidence for and measures of the cosmic merger rate (via tidal features that result from galaxy interactions), reveal the signatures of hierarchical structure formation in extragalactic stellar halos, and probe the LSB outskirts around local galaxies. The following science tasks provide an enumeration of the critical preparatory research tasks required for fully leveraging the LSST dataset for LSB science. +low surface brightness (LSB) science, over unprecedentedly large areas of the sky. LSST's unique deep-wide capabilities will enable us to uncover new evidence for and measures of the cosmic merger rate (via tidal features that result from galaxy interactions), reveal the signatures of hierarchical structure formation in extragalactic stellar halos, and probe the LSB outskirts around local galaxies. The following science tasks provide an enumeration of the critical preparatory research tasks required for fully leveraging the LSST dataset for LSB science. \begin{tasklist}{LSB} -\subsection{Low-Surface Brightness Tidal Features} -\tasktitle{Low-Surface Brightness Tidal Features} +\subsection{Low Surface Brightness Tidal Features} +\tasktitle{Low Surface Brightness Tidal Features} \begin{task} \label{task:lsb:tidal_features} \motivation{ -A key advantage of LSST over previous large-area surveys (e.g. the SDSS) is its ability to detect low-surface-brightness (LSB) tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be 2 mags deeper than the SDSS almost immediately after start of operations, and 5 mags deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionise LSB tidal feature science, enabling us, for the first time, to empirically reconstruct the assembly histories of galaxies over at least two-thirds of cosmic time, provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth and morphological transformation over a significant fraction of cosmic time. +A key advantage of LSST over previous large area surveys (e.g. the SDSS) is its ability to detect LSB tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be 2 mags deeper than the SDSS almost immediately after start of operations, and 5 mags deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionise LSB tidal feature science, enabling us, for the first time, to empirically reconstruct the assembly histories of galaxies over at least two-thirds of cosmic time, provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth and morphological transformation over a significant fraction of cosmic time. \\ Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected using criteria that are difficult to quantify (e.g. visual inspection, that can be somewhat subjective) or reproduce in theoretical models. Furthermore, previously used techniques for the identification and characterization of features, such as visual inspection, cannot be easily applied to the unprecedented volume of data expected from the next generation of telescopes like LSST. Given the depth and volume of data expected from LSST, it is critical that we automate the detection, measurement and characterization of LSB tidal features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. } @@ -35,8 +35,8 @@ \subsection{Low-Surface Brightness Tidal Features} \end{task} -\subsection{Low-Surface Brightness Galaxies} -\tasktitle{Diffuse and Low-Surface Brightness Galaxies} +\subsection{Low Surface Brightness Galaxies} +\tasktitle{Low Surface Brightness Galaxies} \begin{task} \label{task:lsb:galaxies} \motivation{ @@ -124,7 +124,7 @@ \subsection{Intracluster Light} \activities{ The preparation work for the ICL component of the LSB case involves investigating LSST-specific issues for large LSB features and the known properties of the ICL itself. \\ -The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce low surface brightness signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for our team to liaise with LSST strategy, telescope, instrument and data reduction teams. +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce LSB signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for our team to liaise with LSST strategy, telescope, instrument and data reduction teams. \\ The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want to study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. } From e59739234a6d8ecc79eb6df1afb0bcc98efc117d Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 19 Jul 2017 23:11:19 -0700 Subject: [PATCH 25/64] Edits to AGN section. --- task_lists/agn/agn.tex | 44 ++++++++++++++++++++++-------------------- 1 file changed, 23 insertions(+), 21 deletions(-) diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index d94b53f..1ed338c 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -1,7 +1,9 @@ \section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} {\justify -Active Galactic Nuclei (AGN) phenomena enable us to understand the growth of supermassive black holes (BHs), understand aspects of galaxy evolution, probe the high redshift universe, and study other physical activity including accretion physics, jets, and magnetic fields. +Active Galactic Nuclei (AGN) phenomena enable an understanding of +the growth of supermassive black holes (BHs), aspects of galaxy evolution, the high redshift universe, +and other physical activity including accretion physics, jets, and magnetic fields. While AGN represent a distinct topic within the LSST Science Collaborations, the LSST dataset will reveal some aspects of AGN science via their role as an evolutionary stage of galaxies in addition to their ability to probe accretion physics around BHs. @@ -23,7 +25,7 @@ \subsection{AGN Selection from LSST Data} These LSST photometric, multiwavelength, and variability-selected samples may probe unique aspects of AGN phenomena. A better understanding of the AGN role in galaxy evolution requires -that we understand how and why these selection methods include or exclude particular sources +an understanding of how and why these selection methods include or exclude particular sources or phases of AGN-galaxy co-evolution. } ~\\ @@ -38,11 +40,9 @@ \subsection{AGN Selection from LSST Data} near-infrared data that LSST will provide. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Creation of a cross-matched catalog of known AGN selected and verified using different methods. -\item Development of morphological parameters beyond star/galaxy separation and an understanding of the efficacy of LSST Level 2 data products for morphological selection of AGN. -\item Development of color selection criteria that accounts for morphology. \item Understanding of AGN variability sensitivity given the nominal LSST cadence. \item Development of algorithms for color selection account for AGN variability. \end{enumerate} @@ -58,7 +58,8 @@ \subsection{AGN Host Galaxy Properties from LSST Data} \label{task:agn:host_galaxies} \motivation{ Morphological characterizations from parameterized models, such as multiple-component -\cite{sersic1968a} profiles, or non-parametric measures like CAS and Gini-M20 \cite{abraham1994a,conselice2000a,lotz2004a} can help identify mergining galaxies in the LSST data. +\cite{sersic1968a} profiles, or non-parametric measures like CAS and Gini-M20 +\citep{abraham1994a,conselice2000a,lotz2004a} can help identify mergining galaxies in the LSST data. The ability of these techniques to characterize efficiently and accurately the morphology of AGN host galaxies identified via their variability remains unproven. } @@ -74,11 +75,13 @@ \subsection{AGN Host Galaxy Properties from LSST Data} recovery of morphological properties in AGN host galaxies. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Characterization of the accuracy and precision afforded by the LSST dataset for the recovery of basic morphology properties as a function of AGN brightness and wavelength. -\item Understaing of the effects of AGN brightness and variability on host-galaxy classification diagrams. +\item Understanding of the effects of AGN brightness and variability on host-galaxy classification diagrams. +\item Development of morphological parameters beyond star/galaxy separation and an understanding of the efficacy of LSST Level 2 data products for morphological selection of AGN. +\item Development of color selection criteria that accounts for morphology. \end{enumerate} } \end{task} @@ -90,11 +93,10 @@ \subsection{AGN Feedback in Clusters} \label{task:agn:feedback_in_clusters} \motivation{ Brightest Cluster/Group Galaxies (hereafter BCGs) represent the most massive galaxies in the local -universe, residing at/near the centers of galaxy clusters/groups. +universe, residing at or near the centers of galaxy clusters and groups. BCGs contain the largest known supermassive BHs that can influence the host galaxy properties, cluster gas, and other cluster members via the mechanical energy produced by their $>100$kpc scale jets (``AGN feedback''). -\\ The relative proximity of low-redshift galaxy clusters enable detailed studies of stars, gas, and AGN jets that may reveal the ramifications of AGN feedback. LSST will provide a large sample of moderate- to high-redshift clusters @@ -102,8 +104,8 @@ \subsection{AGN Feedback in Clusters} } ~\\ \activities{ -By assembling a multi-wavelength dataset (optical, X-ray, and radio) we can obtain the BCG mass, cluster mass, ICM temperature, and the mechanical power injected into the ICM. -We can use this to study the interplay between the BCG, its black hole, and the cluster gas, +By assembling a multi-wavelength dataset (optical, X-ray, and radio), the BCG mass, cluster mass, ICM temperature, and mechanical power injected into the ICM by supermassive BHs can be constrained. +The interplay between the BCG, its black hole, and the cluster gas can then be studied, providing an assessment of the balance of energies involved and a direct comparison with theoretical models of AGN feedback. SDSS has enabled this multi-wavelength analysis for a few hundred clusters at $z<0.3$, but LSST cluster datasets to reach $z>1$. @@ -112,10 +114,10 @@ \subsection{AGN Feedback in Clusters} cluster mass. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Investigation of the number of BCGs and the mass range of their clusters with redshift that LSST will likely observe. -\item Assessment of radio and X-ray data available for AGN Feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS, etc.). +\item Compilation of existing and forthcoming radio and X-ray data available for AGN feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS, etc.). \item Assessment of theoretical predictions expected for the multi-wavelength properties of AGN host galaxies in clusters or groups (e.g., cosmological simulations such as EAGLE or more detailed single cluster studies). \end{enumerate} @@ -138,10 +140,10 @@ \subsection{AGN Variability Selection in LSST Data} \activities{ Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate and study simulations using parameters selected from these models using observational constraints, and determine the appropriateness of simulations for carrying out various types of AGN variability science including power spectrum models, quasi-periodic oscillation searches, and binary AGN models.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Observational constraints on AGN variability models. -\item MAF metrics quantifying the goodness of different survey strategies for AGN variability science. +\item Metrics for quantifying the efficacy of different survey strategies for AGN variability science. \end{enumerate} } \end{task} @@ -166,7 +168,7 @@ \subsection{AGN Photometric Redshifts from LSST Data} non-host galaxies at a variety of redshifts will help engineer color selection criteria for identifying AGN hosts, and whether variability can break photo-$z$ degeneracies. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Development of AGN host color selection criteria, and an identification of objects for which color selection might prove ambiguous or degenerate. \item Exploration of multiwavelength, morphological, or variability information that might break photo-$z$ degeneracies. @@ -192,14 +194,14 @@ \subsection{AGN Merger Signatures from LSST Data} Create simulated or identify real images that contain known galaxy mergers, including systems with and without visible AGN. Run the LSST software stack on these images, and -engineer metrics that describe/quantify +engineer metrics that quantify the accurate detection of galaxy mergers with and without AGN. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Improve the ability of the LSST Level 2 data to enable the detection of galaxy mergers with AGN. -\item Identify merging galaxy properties or categories that will prove challenging to measure using the LSST datasets. +\item Characterization and optimization of the ability of the LSST Level 2 data to enable the detection of galaxy mergers with AGN. +\item Identification of merging galaxy properties or categories that will prove challenging to measure using the LSST datasets. \end{enumerate} } \end{task} From 2977211d584fc7909dd340975e7ddf6dd67dec02 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 19 Jul 2017 23:15:19 -0700 Subject: [PATCH 26/64] Page number suppression on title page. --- main.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/main.tex b/main.tex index 4ac7009..243a165 100644 --- a/main.tex +++ b/main.tex @@ -17,7 +17,7 @@ %---------------------------------------------------------------------------------------- % TITLE PAGE %---------------------------------------------------------------------------------------- - +\thispagestyle{empty} {\Huge Large Synoptic Survey Telescope} \linebreak \linebreak From af107010534db877006246d042e49f8f96f608b4 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 00:04:21 -0700 Subject: [PATCH 27/64] Edits to the CLSS section. --- task_lists/clss/clss.tex | 241 ++++++++++++++++++--------------------- 1 file changed, 114 insertions(+), 127 deletions(-) diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 7157a4f..7b8efae 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -1,58 +1,52 @@ \section{Clusters and Large Scale Structure}\label{sec:tasks:clss} {\justify The cosmological process of galaxy formation inextricably links -the together, environment and large scale structure with the detailed +together environment and large scale structure with the detailed properties of galaxy populations. The extent of this connection ranges from the scales of superclusters down to small groups. The following preparatory science tasks focus on this critical connection -between galaxy formation, clusters, and large scale structure. +between galaxy formation, clusters, and large scale structure (LSS). \begin{tasklist}{CLSS} -\subsection{Cluster/LSS Sample Emulator} -\tasktitle{Cluster/LSS Sample Emulator} +\subsection{Cluster and Large Scale Structure Sample Emulator} +\tasktitle{Cluster and Large Scale Structure Sample Emulator} \begin{task} \label{task:clss:emulator} \motivation{ -To prepare for galaxies and galaxy group/cluster science with LSST, we -need to know how many galaxies will be detected in a given range of -redshift, brightness, color, etc., and likewise how many groups and -clusters will be detected in given ranges of redshift, richness, mass, +To prepare for galaxy group/cluster and LSS science with LSST, +the samples of cluster/group galaxies detected in a given range of +redshift, brightness, color, need to be estimated, along with the +group and +cluster populations identified in given ranges of redshift, richness, mass, and other physical parameters. } ~\\ \activities{ LSST has advanced simulations of its 10-year Wide Fast Deep survey available from the Operations Simulator. The output databases can be -analyzed to determine the depth LSST is expected to reach in its final -detection image at each sky location, and \citet{awan2016a} turns these depths +analyzed to determine the expected time-dependent depth of LSST +detection images at each sky location. These depths can be converted into predicted numbers of galaxies as a function of redshift and -brightness. +brightness \citep[e.g.,][]{awan2016a}. \\ To predict galaxy sample sizes as a function of physical parameters, -the ``raw'' predicted galaxy numbers from \citet{awan2016a} will be +the ``raw'' predicted galaxy numbers can be interfaced with semi-analytical models painted on large N-body -simulations by Risa Wechsler and collaborators. This will extend the -predictions to include observed properties of color, size, morphology -and physical properties of halo mass, stellar mass, and star formation -rate. -\\ -To predict group/cluster sample sizes as a function of physical -parameters, the properties such as temperature, richness, etc., will -be painted on to dark matter halos drawn from a numerical simulation. -The properties will be based on simple scaling laws, with the user -allowed freedom to choose the parameters of the scaling laws, -including how they evolve. This will then be interfaced with the -``raw'' predicted galaxy numbers from \citet{awan2016a}, to determine -which of the groups and clusters should be detectable in the LSST -data.} +simulations. This approach can extend the +predictions for cluster/LSS samples +to include the observed properties of color, size, morphology, +and the physical properties of halo mass, stellar mass, and star formation +rate. The combination of these models will produce an LSST Cluster/LSS +Sample Emulator for understanding the detailed science return of +LSST for cluster and group science.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Create a public LSST Extragalactic Sample Emulator with a -simple GUI. Enable user input of a range of redshift, and +\item Creation of a public LSST Extragalactic Sample Emulator with a +simple user interface, allowing for the estimation of sample sizes +detected by LSST as a function of redshift and physical parameters (e.g.~galaxy magnitudes, colors, size, morphology, -cluster richness, mass, temperature, etc.) to estimate the size of a -given sample detected by LSST. +cluster richness, mass, temperature, etc.). \end{enumerate} } \end{task} @@ -65,18 +59,18 @@ \subsection{Identifying and Characterizing Clusters} \motivation{ LSST photometry will make it possible to search for and study the galaxy populations of distant clusters and -proto-clusters over huge volumes of the high-$z$ Universe. These -clusters are testbeds for cosmology, hierarchical structure formation, -intergalactic medium heating and metal enrichment, as well as -laboratories for studying galaxy evolution. +proto-clusters over cosmological volumes. These +clusters are testbeds for theories of +hierarchical structure formation, +intergalactic medium heating, metal enrichment, and galaxy evolution. However, standard approaches for identifying clusters, such as the red sequence method, will be hampered by the limited wavelength coverage of LSST. For example, at $z \gtrsim 1.5$, near-IR photometry is required to identify systems with Balmer/$4000$\AA\ breaks. -To maximize cluster science with LSST, we must devise new techniques -for cluster identification as well as incorporate complementary data -from projects such as \emph{Euclid}, \emph{eROSITA}, etc. +To maximize cluster science with LSST, new techniques +for cluster identification and the incorporate complementary data +from projects such as \emph{Euclid} or \emph{eROSITA} must be devised. } ~\\ \activities{ @@ -86,9 +80,9 @@ \subsection{Identifying and Characterizing Clusters} Specifically, this work should characterize the selection function, completeness, and contamination rate for different cluster identification algorithms. -This requires realistic light-cone simulations spanning extremely +Such characerizations require realistic light-cone simulations spanning extremely large volumes, so as to capture significant numbers ($\gg10,000$) of -simulated galaxy clusters at high $z$. +simulated galaxy clusters at high redshift. Potential algorithms to be tested include adaptations of RedMaPPer \citep{rykoff2014a} as well as methods that search for galaxy overdensities over a range of scales \citep[e.g.,][]{chiang2014a,wang2016a}. @@ -97,12 +91,12 @@ \subsection{Identifying and Characterizing Clusters} high-$z$ clusters and in the confirmation and characterization of systems at all redshifts.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item The primary product of this analysis will be improved cluster +\item Improved cluster identification algorithms that can be applied to LSST data once science operations commence. -\item In addition, this work will produce a compilation of ancillary data +\item Compilation of ancillary data that will be helpful in cluster identification and characterization, such as X-ray (e.g.~XCS, eROSITA, etc.), SZ (Planck, SPT, ACT) and radio (SKA and its pathfinders, SUMSS), within the LSST footprint. @@ -124,13 +118,14 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} \citep{baldry2006a,cooper2010a,pasquali2010a}. Unlike spectroscopic surveys, LSST will lack the precise line-of-sight velocity measurements to robustly identify satellite galaxies in -lower-mass groups, where the expected photo-$z$ precision will greatly -exceed the velocity dispersion of the host halo. +lower-mass groups, where the expected photo-$z$ precision will be much +coarser than the corresponding +the velocity dispersion of typical host halos. Instead, LSST will likely be better suited to measuring environment by -tracing the local galaxy density (and identifying filaments). However, +tracing the local galaxy density and identifying filaments. However, LSST is unlike any previous photometric survey and may require new approaches to measuring environment. -The challenge remains to find the measure(s) of local galaxy density +The challenge remains to find measures of local galaxy density with the greatest sensitivity to the true underlying density field (or to host halo mass, etc.), so as to enable analyses of environment's role in galaxy evolution with LSST. @@ -138,23 +133,23 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} ~\\ \activities{ Using mock galaxy catalogs created via -semi-analytic techniques, we will compare different tracers of local +semi-analytic techniques, tracers of local galaxy density (i.e.~''environment'') measured on mock LSST -photometric samples to the underlying real-space density of galaxies -(or to host halo mass). In addition to testing existing density +photometric samples will be compared to the underlying real-space density of galaxies +or host halo mass. In addition to testing existing density measures, such as $N^{\rm th}$-nearest-neighbor distance and counts in -a fixed aperture, we will explore new measures that may be better -suited to LSST. For each measure, we will examine the impact of +a fixed aperture, new measures will be explored that may be better +suited to LSST. For each measure, the impact of increasing survey depth and photo-$z$ precision over the course of the -survey.} +survey will be examined.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item With an improved understanding of the strengths and weaknesses of different environment measures as applied to LSST, this effort will yield code to measure local galaxy density (likely in multiple ways) within the LSST dataset. -\item Create a Level 3 data product for use by the entire project. +\item Creation of methods to generate galaxy environmental measures as Level 3 data products for use by the entire project. \end{enumerate} } \end{task} @@ -167,33 +162,32 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} Contemporary galaxy surveys have transformed the study of large-scale structure, enabling high precision measurements of clustering statistics. The correlation -function provides the most fundamental way to characterize the galaxy +function provides a fundamental way to characterize the galaxy distribution. The dependence of clustering on galaxy properties and the evolution of clustering provide fundamental constraints on theories of galaxy formation and evolution. Interpreting these measurements provides crucial insight into the relation between galaxies and dark matter halos. Understanding how galaxies relate to -the underlying dark matter is also essential for optimally utilizing +the underlying dark matter is essential for optimally utilizing the large-scale distribution of galaxies as a cosmological probe. } ~\\ \activities{ -Preparatory work will be along two main -tracks. The first one will be support work to define and characterize +Support work to define and characterize the upcoming galaxy samples from LSST to enable clustering -measurements from them. Several distinct sets of information need to +measurements. Several distinct sets of information need to be made available or be calculable from pipeline data. Such requirements include a detailed understanding of any selection effects impacting the observed galaxies, the angular and radial completeness of the samples, and the detailed geometry of the survey (typically provided in terms of random catalogs that cover the full survey area). -\\ -The second track will be the development, testing, and optimization of +Further efforts will concern the development, testing, and optimization of algorithms for measuring galaxy clustering using LSST data. One aspect to address is how best to handle the large data sets involved -(e.g.~the ``gold'' galaxy sample will include about $4$~billion -galaxies over $20$,$000$~square degrees). Another is to develop the -methodology to optimally incorporate the LSST photo-$z$ estimates with +(e.g.~the LSST ``gold'' galaxy sample will include about $4$~billion +galaxies over $18$,$000$~square degrees). Another issue is the development +of a +methodology to incorporate optimally the LSST photo-$z$ estimates with the angular data to obtain ``2.5-dimensions'' for pristine clustering measurements. \\ @@ -204,12 +198,12 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} requires cooperation of the DESC-PhotoZ working group and the Galaxies Theory and Mock Catalogs working group.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Ensuring LSST galaxy pipelines include all the necessary +\item Guidance for LSST galaxy pipelines to include all the necessary information for measurements of the correlation function and related -statistics to take place once data is available -\item Developing and refining techniques for measuring galaxy clustering of +statistics to take place once LSST data is available. +\item Development and refinement of techniques for measuring galaxy clustering of large LSST galaxy samples. Together these will enable realizing the full potential of LSST data for large-scale structure studies and galaxy formation inferences thereof. @@ -218,18 +212,18 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} \end{task} -\subsection{Disentangling Complicated Lines of Sight} -\tasktitle{Disentangling Complicated Lines of Sight} +\subsection{Disentangling Complicated Lines-of-Sight} +\tasktitle{Disentangling Complicated Lines-of-Sight} \begin{task} \label{task:clss:los} \motivation{ -Lines of sight through galaxy clusters and groups are the most -challenging lines of sight along which to measure reliable photometric -redshifts because crowding of galaxies complicates the basic process +Lines-of-sight through galaxy clusters and groups rank among the most +challenging lines-of-sight along which to measure reliable photometric +redshifts as crowding of galaxies complicates the basic process of galaxy photometry, and the presence of significant correlated -large-scale structure (LSS) complicates interpretation of the P(z) of -the galaxies that has been computed by an algorithm that ignores the -presence of the LSS. Numerous science goals require the most robust +LSS complicates interpretation of any galaxy redshift distribution +computed by algorithms that ignore the +presence of LSS. Numerous science goals require the most robust probabilistic statements possible as to the location of galaxies along lines of sight through clusters, for example, identification of background galaxies for weak-lensing, identification of faint cluster @@ -239,36 +233,37 @@ \subsection{Disentangling Complicated Lines of Sight} } ~\\ \activities{ -The LSST will deliver the most information rich dataset ever in +LSST will deliver the most information rich dataset ever in relation to the masses and internal structures of clusters and their infall regions. Moreover, the dataset can be enhanced significantly via the addition of data at other wavelengths, including X-ray, millimeter, and near-infrared. -\\ -A tool is therefore envisaged, that can take an input catalogue of -cluster centres that has been obtained from LSST or any other dataset -(e.g.~\emph{Planck}, \emph{eROSITA}). The tool will pull out the +~\\ +A tool is therefore envisaged that can take an input catalogue of +cluster centers that has been obtained from LSST or any other dataset +(e.g.~\emph{Planck}, \emph{eROSITA}), extract the basic L2 LSST photometry of objects within a cone centred on the -cluster centre, and compute the $p(z)$ of each galaxy based on a -cluster-specific algorithm. This algorithm will take account of the -following where they are available: brightness and extent of X-ray +cluster center, and compute the redshift probability distribution +$p(z)$ of each galaxy based on a +cluster-specific algorithm. When available, t +his algorithm will take account of the brightness and extent of X-ray emission, over-density of galaxies as a function of magnitude and -colour, any available spectroscopic redshifts, amplitude and extent of +colour, any available spectroscopic redshifts, and the amplitude and extent of any SZ decrement/increment. The algorithm will likely adopt a Bayesian -hierarchical modelling approach to forward model the problem. The -algorithm can be tested on existing datasets from surveys such as the -Local Cluster Substructure Survey (LoCuSS), XXL, HSC data processed by -DM Stack within LSST, and any others that would like to join in. +hierarchical modeling approach to forward model the problem, +and can be tested on existing datasets from surveys such as the +Local Cluster Substructure Survey (LoCuSS), XXL, and HSC data processed by +DM Stack within LSST. \\ -This work has links with the work on deblending/ICL, forward modelling +This work links with efforts on deblending/ICL, forward modeling of cluster and groups, environmental measures, cluster detection, -complementary data, and also work in the DESC Clusters WG via $p(z)$ -of background galaxies.} +complementary data, and work in the DESC Clusters Working Group via +the determination of $p(z)$ for background galaxies.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item A new cluster-specific photometric redshift algorithm that can be -applied to a list of cluster detections that is itself based on LSST +applied to a list of cluster detections based on LSST or external data. \end{enumerate} } @@ -283,54 +278,46 @@ \subsection{Forward Modeling of LSST Clusters and Groups} \motivation{ Most of the interesting cluster and group physics from LSST and its union with complementary surveys will be derived from studies that -explore the full range of halo mass relevant to groups and clusters: -$M_{200}\simeq10^{13}-10^{15}M_\odot$. This is a wider range than -cluster cosmologists (e.g. colleagues in DESC, with whom we -collaborate) aim to incorporate into their cosmological inference -- -they restrict attention to $M_{200}>10^{14}M_\odot$. -\\ -Another important difference between the cluster/group physics -explored here, and the dark energy-motivated DESC work, is that the -requirement on controlling systematic biases is roughly an order of -magnitude less stringent here than in DESC. Arguably, $\sim10\%$ +explore the full range of halo mass relevant to groups and clusters +$M_{200}\simeq10^{13}-10^{15}M_\odot$. This mass range extends +beyond that used by cluster cosmologists (e.g. colleagues in DESC), +who typically restrict attention to objects with masses +$M_{200}>10^{14}M_\odot$. +However, the +requirement on controlling systematic biases for cluster/group physics +is roughly an order of +magnitude less stringent than for dark energy science. Arguably, $\sim10\%$ control of systematic biases in weak-lensing measurements of low redshift clusters ($\gtrsim2\times10^{14}M_\odot$) has already been achieved \citep{okabe2013a,applegate2014a,hoekstra2015a,okabe2016a}. -Therefore in this Science -Collaboration we have the challenge of maintaining that level of +This science task focuses on the challenge of maintaining that level of control down to smaller masses and out to higher redshifts. -\\ +} +~\\ +\activities{ A growing number of studies are adopting an approach of forward modeling the cluster population simultaneously with the cosmological model to obtain constraints on scaling relations and cosmological -parameters. Here, the idea is to borrow this same approach, but adopt +parameters. Here, the idea is to borrow this same approach, but adopt a fixed cosmological model, broaden the mass range of systems considered, and expand the forward modeling to include additional -relationships of interest. For example, simultaneously fitting +relationships of interest. For example, one could simultaneously fit density profile models to the shear profiles, the mass-concentration relation, and the star-formation rates of clusters and groups. -Overall, this will provide a robust Bayesian inference code with which +Overall, this effort will provide a robust Bayesian inference code with which to constrain the physics of galaxies and hot gas in groups and clusters, tied directly to the halo mass function via weak-lensing. +Related activities include the selection of elements of the cluster population to include in the model, +and the development and testing of the code on simulated data. +Once developed, the code can be improved by extending the range of physics +explored by adding more physical relations, and by testing the code on existing +datasets from pointed surveys (e.g. LoCuSS, others) and wide area surveys (e.g. LoCuSS, DES, others). } ~\\ -\activities{ -Key activities include: -% -\begin{itemize} -\item Select the elements of the cluster population to include in the model -\item Write the first version of the code, and test on simulated (toy model and n-body) data -\item Improve code and consider extending range of physics explored by adding more relations -\item Test code on existing datasets from pointed surveys (e.g. LoCuSS, others) and wide area surveys (e.g. LoCuSS, DES, others) -\item Combine this development work other work packages within Galaxies and DESC -\end{itemize} -} -~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Bayesian inference code to simultaneously model cluster shear -profiles, scaling relations (including and beyond cosmological scaling -relations, across the full range of halo mass of groups and clusters, +\item A Bayesian inference code to simultaneously model cluster shear +profiles and scaling relations across the full range of halo mass of groups and clusters, to $\sim10\%$ control on systematics. \end{enumerate} } From 67f27171e3d847197b066dbfb85256f6fe6b4e1c Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 00:14:07 -0700 Subject: [PATCH 28/64] Edits to the DDF section. --- task_lists/ddf/ddf.tex | 43 ++++++++++++++++++++---------------------- 1 file changed, 20 insertions(+), 23 deletions(-) diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index 11c4a28..d628772 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -25,21 +25,17 @@ \subsection{Coordinating Ancillary Observations} } ~\\ \activities{ -The major challenge in supporting the LSST DDFs is the huge investment of telescope time. +A major challenge in supporting the LSST DDFs is the huge investment of telescope time. Providing supporting multiwavelength data sets requires -coordination across facilities and collaborations to make the most efficient use of telescope time. Current coordination occurs somewhat haphazardly, but there has not to date been a dedicated effort to organize potential stakeholders involved in developing a coherent plan. The LSST Science Collaborations can and should take the lead here. +coordination across facilities and collaborations to make the most efficient use of telescope time. Current coordination occurs somewhat haphazardly, but there has not to date been a dedicated effort to organize potential stakeholders involved in developing a coherent plan. The LSST Science Collaborations can and should take the lead. The SERVS program to observe the already-designated DDFs with Spitzer provides a good example of where coordination can prove fruitful \citep{mauduit2012a}, but substantial -further work remains. Activities include: -\begin{itemize} -\item Workshops to discuss LSST DDF coordination. -\item Proposals for major surveys or even new instrumentation to provide supporting data. -\item Execution of supporting programs. -\item Work to integrate the data from supporting programs with the LSST data. -\item Work to enable DDF support through policies and strategic planning at major observatories. -\end{itemize} +further work remains. Activities include organizing workshops to discuss LSST DDF coordination, +and proposals for major surveys or even new instrumentation to provide supporting data. +If the proposals are successful, then they must be successfully executed with an eye toward integrating +with the future LSST data. These collective efforts will require additional work to enable DDF support through policies and strategic planning at major observatories. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Workshops on LSST DDF supporting observations. \item Annually updated roadmap of supporting observations (conceived, planned, or executed). @@ -57,17 +53,17 @@ \subsection{Observing Strategy Cadence} The LSST DDF observing strategy will need to serve diverse needs. For galaxy evolution science, the time series aspect of the observation may prove less important than the depth, image quality, and mix of filters. Non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data will influence the observing strategy optimization. For example, for many science goals completing the observations of one DDF to the final 10-year depth in the first year could prove very beneficial. -But justifying this investment will require work, including the selection of a suitable DDF +Justifying this investment will require work, including the selection of a suitable DDF and the identification of synergies with other LSST science areas (e.g., DESC, AGN, transients). } ~\\ \activities{ The LSST observing strategy is optimized using the Operations Simulator (OpSim). The Project works with the community to develop both baseline observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Figures of Merit via MAF for use by OpSim. -\item Proposed observing strategies for DDFs with rationale. +\item Figures of Merit via MAF for use by OpSim in evaluating DDF strategies. +\item Proposed observing strategies for DDFs with corresponding scientific rationale. \item Proposing and/or helping to assess selection of additional DDFs. \end{enumerate} } @@ -78,7 +74,8 @@ \subsection{Data Processing} \begin{task} \label{task:ddf:data_processing} \motivation{ -Getting the most out of the DDFs may require data processing beyond that required for the WFD Survey. A variety of issues will need consideration in trying to optimize the science output, +Getting the most out of the DDFs may require data processing beyond that required for the +LSST WFD Survey. A variety of issues will need consideration in trying to optimize the science output, including different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features, deblending overlapping objects, or estimating photometric redshifts. Reprocessing the DDF data while utilizing supporting observations may prove feasible. While there exists a clear advantage to issue one ``official'' LSST-released catalog at Level 2, @@ -90,19 +87,19 @@ \subsection{Data Processing} \activities{ Identify the most important DDF-specific science drivers and any processing requirements distinct from the WFD survey. Coordinate with the Project and Science Collaborations to provide a coherent set of specifications and priorities for data processing. \\ -Develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection). This activity may stress the inputs to the image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low-surface brightness features. Use of the supporting data sets in Level 2 or 3 processing requires careful thought. For example, +Develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection). This activity may stress the inputs to the LSST image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low surface brightness features. Use of the supporting data sets in Level 2 or 3 processing requires careful thought. For example, pixel-level information from either Euclid or WFIRST may improve source identification and photometry. However, these ancillary data sets will not be available for all the DDFs and does not currently reflect the baseline observing plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The Science Collaborations need to work with the various projects to identify a clear path forward.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Science drivers and input to the development of Level 2 processing of the DDFs. -\item Specifications for galaxy-evolution oriented Level 3 DDF processing. -\item Specifications for data-processing using supporting data from other facilities. -\item Simulations tailored to the DDFs. -\item Level 3 data processing code, or augmentations to the LSST Level 2 pipeline. +\item Science drivers and input into to the development of Level 2 processing for the DDFs. +\item Specifications for galaxy evolution-oriented Level 3 DDF processing. +\item Specifications for data processing using supporting data from other facilities. +\item Data simulations tailored to the DDFs. +\item Level 3 data processing code, or augmentations to the LSST Level 2 pipeline, to fully leverage the depth of the DDFs. \end{enumerate} } \end{task} From ea09d18c30ac2f401877101f9d2da8780e3b27d0 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 01:17:33 -0700 Subject: [PATCH 29/64] Edits to the Galaxy section. --- authorlist.tex | 1 + task_lists/galaxies/galaxies.tex | 195 +++++++++++++++++-------------- task_lists/lsb/lsb.tex | 4 +- 3 files changed, 110 insertions(+), 90 deletions(-) diff --git a/authorlist.tex b/authorlist.tex index 1b6a3ab..b70a93a 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -26,6 +26,7 @@ Conselice, Christopher J.$^{21}$, Davies, Jonathan$^{22}$, Demarco, Ricardo$^{23}$, +Dickinson, Mark E.$^{13}$, Galaz, Gaspar$^{14}$, Grazian, Andrea$^{24}$, Holwerda, Benne W.$^{25}$, diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 1d7849a..2ebd3bf 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -18,18 +18,18 @@ \section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} the detection and characterization of low-surface brightness features or unusual morphologies. -The task list presented here highlights the preparatory research needed in the next $\sim3-4$ -years. +The task list presented here highlights the preparatory research needed +before LSST first light. Tasks of primary importance and particular urgency include those that might influence the detailed survey design or the algorithms used in the LSST Software Stack to construct catalogs. Other critical tasks remain reasonably independent of the LSST survey design and data pipeline optimization, but will help ensure good support for LSST galaxy studies. -\subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:gal:techniques_and_algorithms} +\begin{tasklist}{G} -\begin{tasklist}{G-TAS} -\tasktitle{Techniques for finding low-surface-brightness features or galaxies} +\subsection{Techniques for Finding Low Surface Brightness Features or Galaxies} +\tasktitle{Techniques for Finding Low Surface Brightness Features or Galaxies} % Tidal streams % Intracluster diffuse light \begin{task} @@ -62,7 +62,7 @@ \subsection{Techniques, Algorithms, or Software Development} \label{sec:tasks:ga Level 2 processing and observing strategies about the needs of LSB science, and (4) developing a strategy for finding and measuring LSB features through some combination of Level 2 measurements, database queries, and Level 3 processing.\\ -The instertion of realistic LSB features into LSST simulated images will provide +The insertion of realistic LSB features into LSST simulated images will provide ``data challenges'' to test methods for their extraction and measurement, allowing for the exploration of different techniques or algorithms for performing LSB feature detection and characterization. @@ -127,11 +127,11 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} \begin{task} \label{task:gal:deblending} \motivation{ -The Level 2 data products provide the most relevant starting point -for galaxy-evolution science. In the LSST nomenclature, {\tt Objects} +Level 2 data products will provide the starting point +for galaxy evolution science with LSST. In the LSST nomenclature, objects represent astrophysical entities (stars, galaxies, quasars, etc.), while -{\tt Sources} represent their single-epoch observations. -The Software Stack will generate the master list of Objects in Level 2 +sources represent their single-epoch observations. +The LSST Software Stack will generate the master list of objects in Level 2 by associating and deblending the list of single-epoch source detections and the lists of sources detected on co-adds. The exact strategies for @@ -139,20 +139,22 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} engagement with the science community will prove essential. While each data release will provide unique object IDs, if the first few generations of catalogs limit the science performed through data base -queries the consequences may impede early LSST science.\\ +queries the consequences may impede early LSST science. +~\\ For galaxies science, the issue of deblending holds critical importance. For example, searches for high-redshift galaxies via color selection or photometric redshifts involve model or template spectra that make the prior assumption that each analyzed object does not consist of a blend of two objects at two different redshifts. Therefore, to get a reliable estimate of the evolution of classes of galaxies -over redshift we need to (a) create reasonably clean catalogs to start with +over redshift we need to (a) create reasonably clean initial catalogs and (b) model the effects of blending on the sample selection and derivation of redshift and other parameters. These issues critically affect not just galaxy evolution science, but also lensing and large-scale structure studies. Another example involves the evolution of galaxy morphologies, where the effects of blending and confusion -may well dominate measurement uncertainties. \\ +may dominate measurement uncertainties. +~\\ For the Level 2 catalogs, the planned approach involves using the Software Stack to deblend sources hierarchically and then maintain this hierarchy in the catalog. @@ -177,14 +179,14 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} from all the LSST filters and perhaps even EUCLID and WFIRST might help to disentangle them. Some attempts over the past few years have incorporated color gradient information into the deblending algorithm, but this approach needs -much more attention for developing and testing algorithms, and +much more attention for developing and testing algorithms, and for deciding on figures-of-merit for their performance. } ~\\ \deliverables{ -Deliverables over the next several years from the activities described above include the following: +%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Production of realistic galaxy image inputs to the ImSim team. +\item Production of realistic galaxy image inputs to the LSST ImSim team. \item Development of tests and figures of merit to quantify the effects on several science objectives; \item Assessment of the current baseline plan for Level 2 deblending and for parameter estimation for blended objects. \item Development of prototype implementations of deblending algorithms that take advantage of the LSST color information. @@ -200,25 +202,33 @@ \subsection{Optimizing Galaxy Morphology Measurements} \begin{task} \label{task:gal:morphology} \motivation{ -Morphology encodes key signatures of the formation histories of galaxies, and measurements of galaxy morphology are an important tool for constraining models of galaxy evolution. While simple measures of galaxy ellipticity and position -angles may be sufficient for the Dark Energy science goals, more sophisticated measurements of morphology are needed for galaxy-evolution science. While the ``multifit'' approach of fitting simple parametric models to galaxy profiles is useful to zeroth order, this is insufficient for the detailed morphological information that will be required for much of the galaxy science that is planned using LSST. +Morphology encodes key signatures of the formation histories of galaxies, and measurements of galaxy morphology +provide an important tool for constraining models of galaxy evolution. +While simple measures of galaxy ellipticity and position +angles may be sufficient for the dark energy science goals, more sophisticated measurements of morphology are needed for galaxy-evolution science. While the ``multifit'' approach of fitting simple parametric models to galaxy profiles is useful to zeroth order, this approach may be insufficient for the detailed morphological information +required for much of the galaxy science that is planned using LSST. \\ -For well-resolved galaxies the baseline requirement is to have separate measures of bulge and disk, and spiral-arm structure, measures of concentration, asymmetry, and clumpiness. These ought to be measured as part of the level 2 processing, to enable database queries to extract subclasses of galaxies. Both parametric and non-parametric measures are desirable. While there will no doubt be optimization in level 3 processing, it is important to have enough information in the level 2 output products to pick reasonable subsets of galaxies. +For well-resolved galaxies the baseline requirement is to have separate measures of bulge and disk, spiral arm structure, measures of concentration, asymmetry, and clumpiness. These +properties ought to be measured as part of the Level 2 processing, to enable database queries to extract subclasses of galaxies. Both parametric and non-parametric measures are desirable. While Level 3 processing methods will be +developed to further optimize galaxy measurements, +the Level 2 products should supply enough information to select reasonable subsets of galaxies. \\ -More importantly, while the traditional parametrisations of morphology described above will be useful, it is essential that new, more powerful methods of measuring galaxy morphology are developed and implemented, in order to leverage the exquisite volume and depth of LSST data. In this regard fast, unsupervised machine-learning techniques \citep[e.g.][]{hocking2015a}, which are able to efficiently separate LSST galaxy populations into different morphological classes, are particularly relevant and powerful (supervised techniques may not be as well-suited to LSST, since the sheer volume of data expected, coupled with the speed with which datasets will change in depth, makes producing training sets, via e.g. visual inspection, prohibitively time consuming. +More importantly, while the traditional parameterizations of morphology described above will be useful, it is essential that new, more powerful methods of measuring galaxy morphology are developed and implemented, in order to leverage the exquisite volume and depth of LSST data. In this regard fast, +machine-learning techniques \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that can efficiently separate LSST galaxy populations into different morphological classes are particularly relevant and powerful. } ~\\ -\activities{The preparation work will focus on defining morphological parameters and developing unsupervised machine-learning algorithms to enable users to easily query galaxy morphologies from the LSST database. Two aspects of LSST data make this a significant research project: the fact that LSST provides multi-band data with a high degree of uniformity, and the fact that the individual observations will have varying point-spread functions. The former offers the opportunity to use much more information than has been generally possible. The latter means that it will take some effort to optimize and calibrate the traditional non-parametric measures of morphology (e.g. the CAS, GINI and M20 parameters), develop new LSST-optimized parameters, and tune machine-learning algorithms to operate on this type of data. +\activities{The preparation work will focus on defining morphological parameters and developing machine-learning algorithms to enable users to easily query galaxy morphologies from the LSST database. +Two aspects of LSST data make this a significant research project: the fact that LSST provides multi-band data with a high degree of uniformity, and the fact that the individual observations will have varying point-spread functions. The former offers the opportunity to use much more information than has been generally possible. The latter means that it will take some effort to optimize and calibrate the traditional non-parametric measures of morphology (e.g. the CAS, GINI and M20 parameters), develop new LSST-optimized parameters, and tune machine-learning algorithms to operate on this type of data. \\ -Given the very large data set expected from LSST, which will change on short timescales in terms of depth, morphological parameters (e.g. CAS) will likely need to be calibrated on realistic data from hydro-dynamical simulations in cosmological volumes, possibly augmented by training sets classified by humans. Similarly, unsupervised machine-learning algorithms will have to be developed and implemented using a mixture of realistic simulations and precursor datasets, such as the Hyper Suprime Cam Survey. A series of ``classification challenges'' prior to the LSST survey could help to refine these techniques. +Given the very large data set expected from LSST, which will change on short timescales in terms of depth, morphological parameters (e.g. CAS) will likely need to be calibrated on realistic data from hydrodynamical simulations in cosmological volumes, possibly augmented by training sets classified by humans. Similarly, machine-learning algorithms will have to be developed and implemented using a mixture of realistic simulations and precursor datasets, such as the HyperSuprimeCam Survey. A series of ``classification challenges'' prior to the LSST survey could help to refine these techniques. } ~\\ \deliverables{ -Deliverables over the next several years from the activities described above include the following: +%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Providing realistic galaxy image inputs from hydro-dynamical simulations and precursor datasets for classification tests -\item Human classification of image subsets for calibration of morphologial parameters -\item Unsupervised machine-learning algorithms that will provide fast morphological classification of LSST datasets, developed using and implemented on precursor datasets such as the Hyper Suprime Cam Survey +\item Realistic galaxy image inputs from hydrodynamical simulations and precursor datasets for classification tests. +\item Human classification of image subsets for calibration of morphological parameters. +\item Machine-learning algorithms that will provide fast morphological classification of LSST datasets, developed using and implemented on precursor datasets such as the HyperSuprimeCam Survey or the Dark Energy Survey. \end{enumerate} } \end{task} @@ -230,18 +240,22 @@ \subsection{Galaxy Structural Parameters} \begin{task} \label{task:gal:struc_param} \motivation{ -The image quality provided by the camera (0.2"/pixel), the wide field coverage (9.6deg2) over 18.000 deg2 in optical and NIR (ugrizy bands), promise to provide unique data to cast light on the evolution of the internal structure of galaxies and galaxy clusters and their dark matter haloes, up to redshift well beyond unity. The full depth of the Deep-Wide-Fast (r $\sim$27.5 coadded) will allow us to identify dwarf galaxies at z~0.5, and up to $M_*+2$ galaxies in clusters and field at z~1.5, and reach enough SNR to study the structural parameters (size, Sérsic index, ellipticity etc.) of $M_*$ galaxies at z~1.2 (for seeing<0.5"). The evolution of the structural parameters, especially the size, Sersic index and B/D over billion of galaxies will allow to correlate them with mass, colours and other intrinsic properties at different epochs and clarify the mechanisms that drive the galaxy assembly and transformation. Other science directly connected is the strong lensing (in model subtracted images) and galaxy dark matter content and the dark-to-luminous mass connection in galaxies. +The image quality provided by the LSST camera (0.2"/pixel) and the wide field coverage (9.6deg$^2$) over 18,000 deg$^2$ in optical and NIR bands promise to provide unique data for studying the evolution of the internal galaxy structure. +The full depth of the Wide Fast Deep survey (r $\sim$27.5 coadded) +will allow for the identification dwarf galaxies at $z\sim0.5$, and up to $M_*+2$ galaxies in clusters and field at $z\sim1.5$, and reach deep enough to study the structural parameters (size, Sersic index, ellipticity etc.) of $M_*$ galaxies at $z\sim1.2$ (for seeing$<0.5$"). The LSST data will allow for size, Sersic index, and bulge-to-disk ratio for over a billion galaxies to be correlatedd with mass, color, and other intrinsic properties at different epochs and thereby clarify the mechanisms that drive the galaxy assembly and transformation. } ~\\ -\activities{ Most of the preparatory work will consist on testing parametric methods for seeing convolved 2D fitting of the galaxy light distribution both on precursor surveys (e.g. Subaru or KiDS) and on simulated LSST images. The aim is to provide the collaboration viable tools for automatic image masking, catalogue extraction, source classification and 2D galaxy fitting. A specific aspect of this task is to optimise tool performances in order to guarantee big data analysis in reasonable time (e.g. 100 millions of LSST galaxies in all bands on a single week). The surface brightness profile of galaxies in different bands will finally generate a catalog of all relevant structural parameters via Level 3 products. +\activities{Preparatory work will consist of testing parametric methods for seeing-convolved 2D fitting of the galaxy light distribution on precursor surveys (e.g. Subaru or KiDS) and on simulated LSST images, with the aim of providing viable tools for automatic image masking, catalogue extraction, source classification, and 2D galaxy fitting +in Level 3 datasets. +This task will involve optimizing tool performance to guarantee meet time metrics (e.g., processing 100 million LSST galaxies in all bands on a single week). The surface brightness profile of galaxies in different bands will finally generate a catalog of all relevant structural parameters via Level 3 products. } ~\\ -\deliverables{From the activities described above we expect to provide the following deliverables: +\deliverables{%From the activities described above we expect to provide the following deliverables: \begin{enumerate} -\item benchmarks for different existing and newly developed tools for galaxy surface photometry; -\item automatic masks (star haloes and spikes, reflections etc.) and related procedures; -\item catalog of structural parameters in different bands; -\item machine learning algorithm for the identification of faint substructures in model subtracted images (e.g. streams, merging, rings, strong lensing arcs, etc.) +\item Benchmarks for existing and newly developed tools for galaxy surface photometry. +\item Automatic masks for star halos, spikes, and reflections, and related procedures for Level 3 analyses. +\item Tools to catalog structural parameters in different bands. +\item Machine learning algorithms for the identification of faint substructures in model subtracted images (e.g. streams, merging, rings, strong lensing arcs, etc.). \end{enumerate} } \end{task} @@ -259,47 +273,54 @@ \subsection{Optimizing Galaxy Mass Profile Measurements} \label{task:gal:mass} \motivation{Galaxies form and evolve dynamically via the gravitational influence of the underlying dark matter structure. This non-baryonic dark mass is intimately -involved in the evolution of the baryonic component which ultimately generates the +involved in the evolution of the baryonic component that ultimately generates the stellar component visible in the optical. LSST can uniquely probe both of these tracers for hundreds of millions of galaxies over a range of look-back time. -This provides an opportunity to probe the detailed relation between mass and light structure -evolution for the first time. This has been attempted before in a limited way using LSST -precursor surveys. Using 300,000 lens galaxies in the Deep Lens Survey, \citep{choi2012a} +This sample provides an opportunity to probe the detailed relation between baryonic and dark +matter structure +evolution. Such studies have been attempted before in a limited way using LSST +precursor surveys. Using 300,000 lens galaxies in the Deep Lens Survey, \citep{choi2012a} studied the mass profile of galaxies in three luminosity bins out to several Mpc. Using a similar number of lens galaxies in the COSMOS ACS data,\citep{leauthaud2012a} derived constraints on the evolution of the stellar-to-dark matter connection in the context of halo models. -LSST will provide a billion lens galaxies and more accurate photometric redshifts . +LSST will provide a billion lens galaxies and more accurate photometric redshifts, revolutionizing +this measurement. } ~\\ \activities{ -The question to be addressed is: how far down the galaxy mass function can -we expect to detect the mass profile in selected large samples of galaxies. One must start -with a model of the mass distribution in galaxies. This will -involve use of existing n-body galaxy formation simulations and resulting analytic models; -foreground lens galaxy sample selection; the weak lens shear simulations of LSST observing over -a large area (1000 sq.deg) containing a large sample of lens galaxies; stacked simulations of -the galaxy-mass correlation function out to significant radii for mass environment tests (3-10 Mpc); -sample cuts on morphological surface brightness type vs redshift; and assessment of SNR for -dwarf galaxy samples and sample completeness. The LSST main survey will -have hundreds of thousands of dwarf galaxies in a range of redshift from 0.2 - 0.6 which act as lenses. -The shear SNR is high: A simulation of just 20 LSST visits to a single $z=0.5$ galaxy -with total $10^{11} M_\odot$ virial mass yields a shear SNR of 10 out to several Mpc projected radius. +An important issue to address is how far down the galaxy mass function can one detect +the mass profile in selected large samples of galaxies. One must start +with a model of the mass distribution in galaxies, which will +involve use of existing galaxy formation simulations and resulting analytic models. +Foreground lens galaxy sample selection must be explored, +weak lens shear simulations of LSST observing over +a large area (1000 deg$^2$) containing a large sample of lens galaxies performed, +stacked simulations of +the galaxy-mass correlation function out to significant radii for mass environment tests (3-10 Mpc) +computed, +sample cuts on morphological surface brightness type vs. redshift engineered, and an assessment of +signal-to-noise (SNR) for +dwarf galaxy samples and sample completeness determined. +The LSST main survey will +have hundreds of thousands of dwarf galaxies in a range of redshift $z = 0.2 - 0.6$ which act as lenses. +The shear SNR is high -- a simulation of just 20 LSST visits to a single $z=0.5$ galaxy +with total $10^{11} M_\odot$ virial mass yields a shear SNR$\approx10$ out to several Mpc in projected radius. Stacking a million dwarf galaxies should thus yield high precision mass profiles, even when cut on -parameters such as mass environment, surface brightness type, stellar mass, redshift, etc. +parameters such as mass environment, surface brightness type, stellar mass, and redshift. } ~\\ -\deliverables{Deliverables over the next several years from the activities -described above include the following: +\deliverables{%Deliverables over the next several years from the activities +%described above include the following: \begin{enumerate} -\item using a set of n-body full hydro models of galaxies at stages in development, -select a set of template galaxies for use as lenses in ray-trace simulations; -\item galaxy - mass shear simulations over at least 1000 sq.deg, using the -latest LSST OpSim run and full end-to-end weak lens ray trace, including PSF -and detector effects -- for a representative set of galaxies over a range of masses; -\item galaxy-mass correlation functions using these stacked LSST shear -simulations, for sets of populations of galaxies over a wide mass range; -\item assess SNR vs galaxy mass, and ability to correlate mass profile with -optical surface brightness and type, over a range of redshift. +\item A selection for a set of template galaxies for use as lenses in ray-trace simulation, +using a set of simulated models of galaxies at various stages in development. +\item Galaxy - mass shear simulations over at least 1000 square degrees, using the +latest LSST OpSim run and full end-to-end weak lens ray tracing, including PSF +and detector effects, and incorporating a representative set of galaxies over a range of masses. +\item Computation of galaxy-mass correlation functions using these stacked LSST shear +simulations, for sets of populations of galaxies over a wide mass range. +\item Assessment SNR vs galaxy mass, and the ability to correlate mass profile with +optical surface brightness and type over a range of redshift. \end{enumerate} } \end{task} @@ -315,15 +336,15 @@ \subsection{Optimizing Galaxy Photometry} \begin{task} \label{task:gal:photometry} \motivation{ -Systematic uncertainties will dominate over random uncertainties for almost any -research question one can imagine addressing with LSST. The most basic measurement -of a galaxy is its flux in each band, but this is a remarkably subtle measurement -for a variety of reasons: galaxies do not have well-defined edges, their shapes +Systematic uncertainties will dominate over random uncertainties for many +research questions addressed with LSST. The most basic measurement +of a galaxy is its flux in each band, but flux is a remarkably subtle measurement +for a variety of reasons as galaxies do not have well-defined edges, their shapes vary, they have close neighbors, they cluster together, and lensing affects both their brightness and clustering. These factors all affect photometry in systematic ways, potentially creating spurious correlations that can obscure or masquerade as astrophysical effects. For example, efforts to measure the effect of neighbors -on galaxy star-formation rates can be thrown off if the presence of a neighbor +on galaxy star-formation rates can be erroneous if the presence of a neighbor affects the basic photometry. Measurements of galaxy magnification or measurements of intergalactic dust can be similarly affected by systematic photometric biases. It is thus important to hone the photometry techniques prior to the survey to @@ -333,7 +354,7 @@ \subsection{Optimizing Galaxy Photometry} } ~\\ \activities{ -The core photometry algorithms will end up being applied in level 2 processing, +The core photometry algorithms will end up being applied in Level 2 processing, so it is important that photometry be vetted for a large number of potential science projects before finalizing the software. Issues include the following. (1) Background estimation, which, for example, can greatly affect the photometry @@ -350,13 +371,13 @@ \subsection{Optimizing Galaxy Photometry} } ~\\ \deliverables{ -Deliverables over the next several years from the activities described above include the following: +%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item developing metrics for various science cases to help evaluate the level 2 photometry; -\item providing realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies); +\item Development of metrics for various science cases to help evaluate the Level 2 photometry. +\item Realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies). \end{enumerate} Deliverables over the longer term include developing optimal techniques for forced photometry -using priors from the space missions. +using priors from space-based missions. } \end{task} @@ -366,35 +387,33 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} \begin{task} \label{task:gal:stellarpops} \motivation{ -The colors of galaxies carry information about their star-formation histories, -each interval of redshift being a snapshot of star-formation up until that time. -Unfortunately, estimates of star-formation rates and star-formation histories +The colors of galaxies carry information about their star formation histories, +each interval of redshift being a snapshot of star formation up until that time. +Unfortunately, estimates of star formation rates and histories for a single galaxy based on only the LSST bands will be highly uncertain, -due largely to degeneracies between age, dust extinction and metallicity. +owing largely to degeneracies between age, dust extinction, and metallicity. Strategies for overcoming the degeneracies include hierarchical modeling -- using ensembles of galaxies to constrain the hyper-parameters that govern -the star-formation histories of sets of galaxies rather than individuals, +the star formation histories of sets of galaxies rather than individuals, and using ancillary data from other wavelengths. } ~\\ \activities{ Activities in this area include developing scalable techniques for hierarchical Bayesian inference on very large data sets. These can be -tested on semi-analytical or hydrodynamical models, where the answer is known, -even if it does not correctly represent galaxy evolution. The models should -also be analyzed to find simple analytical expressions for star-formation -histories, chemical evolution and the evolution and behavior of dust to -make the Bayesian inference practical.\\ -Another important activity is to identify the ancillary data sets and -observing opportunities, especially for the deep fields. +tested on semi-analytical or hydrodynamical models, where the answer is known +even if they do not correctly represent galaxy evolution. The models should +also be analyzed to find simple analytical expressions for star formation +histories, chemical evolution, and the evolution and behavior of dust to +make the Bayesian inference practical. } ~\\ \deliverables{ -Deliverables over the next several years from the activities described above include the following: +%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item developing and refining techniques for constraining star-formation histories of large ensembles of galaxies; -\item providing model inputs to guide in developing these techniques; -\item refining the science requirements for ancillary multi-wavelength data to support LSST. +\item Development and refinement of techniques for constraining star-formation histories of large ensembles of galaxies. +\item Model inputs to guide in developing these techniques. +\item Refinement of the science requirements for ancillary multi-wavelength data to support LSST. \end{enumerate} } \end{task} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 13e27fe..ef60ad9 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -83,9 +83,9 @@ \subsection{Faint Outskirts of Galaxies} \label{task:lsb:faint_outskirts} \motivation{ The outskirts of nearby galaxies, loosely defined as the regions below $25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). -\\ +~\\ The main science driver here is understanding the assembly, formation, and evolution of galaxies. This can be studied through imaging and subsequent parametrization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar haloes. From numerical modelling we know that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo, are tightly related to the accretion and merging history. This is illustrated by the imaging of the stars in the outskirts of M31 and other local group galaxies, which show detailed structure. -\\ +~\\ Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams will be less affected by overall PSF. } ~\\ From 7f9410c58878604bb0f777ea0d5eae120ea83192 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 01:26:53 -0700 Subject: [PATCH 30/64] Edits to the high-z section. --- task_lists/high_z/high_z.tex | 27 +++++++++++++-------------- 1 file changed, 13 insertions(+), 14 deletions(-) diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index 07e50a7..1cd69c2 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -2,7 +2,7 @@ \section{High-Redshift Galaxies}\label{sec:tasks:high_z} {\justify Observations of distant galaxies provide critical information -into the efficiency of the galaxy formation process, the end +about the efficiency of the galaxy formation process, the end of the reionization era, the early enrichment of the intergalactic medium, and the initial conditions for the formation of modern galaxies at later times. Through its wide area and sensitivity @@ -28,7 +28,6 @@ \subsection{Optimizing Galaxy Photometry for High-Redshift Sources} The highest redshift searches will LSST will necessarily require combining with space-based infrared surveys like Euclid and WFIRST. Since Euclid and WFIRST will provide data with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogeneous flux measurements for sources across the different surveys. -\\ It remains unclear whether the current LSST Level 2 data will meet all the requirements for identifying and characterizing high-redshift galaxy populations, motivating an investigation before the start of LSST operations. } @@ -38,15 +37,15 @@ \subsection{Optimizing Galaxy Photometry for High-Redshift Sources} requires clarification. Photometric catalogues produced using the reddest LSST (e.g. $z$- or $y$-band) images as the detection image will prove critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. Similarly, negative fluxes for undetected galaxies together with their corresponding errorbars provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. Coordinating with the LSST Project to ensure the application of forced photometry in Level 2 in a manner appropriate for high-redshift galaxy selection may be sufficient, or Level 3 data products may be required. - \\ -Second, the determination of a suitable approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection will be required. -We will need to determine the optimal measure of an optical-IR color for sources from these two datasets. Sources resolved in Euclid or WFIRST data could be blended in LSST, and may therefore +~\\ +Second, the determination of a suitable approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection will be required, including optimal measures of an optical-IR color for sources from these combined datasets. +Sources resolved in Euclid or WFIRST data could be blended in LSST, and may therefore require deblending using the higher resolution IR data as a prior before reliable flux and color measurements can be made. The engineering of this combined analysis likely will require Level 3 efforts, and tests using existing datasets (e.g., Dark Energy Survey and Hubble Space Telescope data) may already commence.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Clarification of LSST Level 2 data suitability for high-redshift science, and an identification of any Level 3 needs. \item Development of Level 3 tools to produce optimal combined photometry from ground and space-based surveys, and the testing of these tools on existing datasets. @@ -68,10 +67,10 @@ \subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} cool brown dwarfs in our own Milky Way and low-redshift, dusty and/or red galaxies. These objects can mimic the colors of high-redshift sources and therefore prove difficult to distinguish. -This is particularly a problem for the highest redshift objects detected by LSST, which, unless data at redder wavelengths is available (such as near-infrared imaging from VISTA/Euclid/WFIRST, and/or mid-infrared imaging from Spitzer/WISE) will be only detected in one or two red-optical filters. -Using the LSST simulations, we want to devise the most effective way of separating these different populations by utilizing both photometric and morphological information for the sources. +This issue is particularly a problem for the highest redshift objects detected by LSST, which, unless data at redder wavelengths is available (such as near-infrared imaging from VISTA/Euclid/WFIRST, and/or mid-infrared imaging from Spitzer/WISE) will be only detected in one or two red-optical filters. +Using the LSST simulations, one wants to devise the most effective way of separating these different populations by utilizing both photometric and morphological information for the sources. Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA, -we expect LSST images to spatially resolve at least some of the most luminous $z > 6$ galaxies \citep{willott2013a, bowler2017a}. +one expects LSST images to spatially resolve at least some of the most luminous $z > 6$ galaxies \citep{willott2013a, bowler2017a}. For fainter high-redshift galaxies however, a morphological distinction between faint ultra-cool brown dwarfs may not be possible, and further information such as near-infrared colours or proper motions will be required for identification. } ~\\ @@ -88,12 +87,12 @@ \subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} (i.e., Euclid or WFIRST). } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} -\item Incorporate high-z galaxies (and quasars) into LSST simulations with a realistic and representative set of properties. -\item Incorporate cool Milky Way brown dwarfs into LSST simulations. -\item Provide a prediction of the likely number density of brown dwarfs over the different DDFs. -\item Extend simulations to other datasets beyond LSST (e.g., Euclid and WFIRST filters). +\item Incorporation of high-$z$ galaxies and quasars into LSST simulations with a realistic and representative set of properties. +\item Incorporation pf cool Milky Way brown dwarfs into LSST simulations. +\item Predictions of the likely number density of brown dwarfs over the different DDFs. +\item Extension of simulations to other datasets beyond LSST (e.g., Euclid and WFIRST filters). \end{enumerate} } \end{task} From df6bac767a537a756e11a25b0e089275aa9160eb Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 01:57:06 -0700 Subject: [PATCH 31/64] Edits to the LSB section. --- task_lists/lsb/lsb.tex | 76 +++++++++++++++++++----------------------- 1 file changed, 35 insertions(+), 41 deletions(-) diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index ef60ad9..688df3b 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -9,7 +9,8 @@ \subsection{Low Surface Brightness Tidal Features} \begin{task} \label{task:lsb:tidal_features} \motivation{ -A key advantage of LSST over previous large area surveys (e.g. the SDSS) is its ability to detect LSB tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be 2 mags deeper than the SDSS almost immediately after start of operations, and 5 mags deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionise LSB tidal feature science, enabling us, for the first time, to empirically reconstruct the assembly histories of galaxies over at least two-thirds of cosmic time, provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth and morphological transformation over a significant fraction of cosmic time. +A key advantage of LSST over previous large area surveys (e.g. the SDSS) is its ability to detect LSB tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be two magnitudes deeper than the SDSS almost immediately after start of operations, and five magnitudes deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionize LSB tidal feature science, enabling, for the first time, the empirically reconstruction of the assembly histories of galaxies over at least two-thirds of cosmic time. +These histories provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth, and morphological transformation over a significant fraction of cosmic time. \\ Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected using criteria that are difficult to quantify (e.g. visual inspection, that can be somewhat subjective) or reproduce in theoretical models. Furthermore, previously used techniques for the identification and characterization of features, such as visual inspection, cannot be easily applied to the unprecedented volume of data expected from the next generation of telescopes like LSST. Given the depth and volume of data expected from LSST, it is critical that we automate the detection, measurement and characterization of LSB tidal features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. } @@ -18,18 +19,18 @@ \subsection{Low Surface Brightness Tidal Features} Several activities are of critical importance and need to be completed before LSST commissioning and the survey proper: \begin{enumerate} \item Simulating realistic LSST images and LSB features (using e.g. new high-resolution hydrodynamical simulations in cosmological volumes, such as Horizon-AGN, EAGLE, Illustris and others). -\item Identifying precursor datasets (e.g. the Hyper Suprime Cam Survey or the Dark Energy Camera Legacy Survey (DECaLS)) that can be used as testbeds for developing LSB tools for use on LSST data. +\item Identifying precursor datasets (e.g. the HyperSuprimeCam Survey or the Dark Energy Camera Legacy Survey (DECaLS)) that can be used as testbeds for developing LSB tools for use on LSST data. \item Using such simulations to develop algorithms for auto-detection, measurement and characterisation of LSB features (e.g. using the properties of LSB tidal features to back-engineer the properties of the mergers which created them). -\item Applying these algorithms to the precursor datasets to test their suitability +\item Applying these algorithms to the precursor datasets to test their suitability. \item Ensuring that LSST level-2 processing strategies and observing strategies are aligned with the needs of LSB tidal-feature science. \end{enumerate} } ~\\ -\deliverables{Deliverables over the next several years (especially in the run up to commissioning) from the activities described above include the following: +\deliverables{%Deliverables over the next several years (especially in the run up to commissioning) from the activities described above include the following: \begin{enumerate} -\item Realistic mock LSST images from hydro cosmological simulations (including re-simulations of individual objects were necessary) with spatial resolutions of $\sim1$ kpc or better -\item Algorithms for finding galaxies with LSB tidal features, measuring the properties of these features and characterising them i.e. using the properties of LSB tidal features to reconstruct the properties of the mergers which created them (e.g. mass ratios, time elapsed since the merger, etc.). -\item A baseline concept for a value-added LSST database of LSB tidal features. +\item Realistic mock LSST images from cosmological simulations (including re-simulations of individual objects where necessary) with spatial resolutions of $\sim1$ kpc or better. +\item Algorithms for finding galaxies with LSB tidal features, measuring the properties of these features and characterizing them i.e. using the properties of LSB tidal features to reconstruct the properties of the mergers which created them (e.g. mass ratios, time elapsed since the merger, etc.). +\item A baseline concept for a value-added LSST database of LSB tidal features. \end{enumerate} } \end{task} @@ -40,33 +41,24 @@ \subsection{Low Surface Brightness Galaxies} \begin{task} \label{task:lsb:galaxies} \motivation{ -The objective of this task is to investigate objects that have surface brightnesses much less than that of the background night sky and that which is typical of the Milky Way galaxy we live within. Many authors have previously shown how difficult it is to LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to the spiral galaxy that we live within. Thus, the Universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? +The objective of this task is to investigate objects that have surface brightnesses much less than the background night sky and are typical of the Milky Way galaxy within which we live. Many authors have previously shown how difficult it is to identify LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to our own spiral galaxy. Thus, the universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? \\ -Additionally, this LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via HI surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies are still quite easy to detect in LSST images. +Additionally, the LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via neutral hydrogen surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies will still be quite easy to detect in LSST images. \\ -At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting SB of the LSST combined with the large FOV make this instrument unique to probe the existence of large LSBs, similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. +At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting surface brightness limit of the LSST combined with the large field-of-view make this facility unique for probing the existence of large LSBs similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This issue is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. \\ -To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5~\mathrm{mag}~\mathrm{arcsec}^{-2}$ and that from a space telescope typically an order of magnitude fainter $\approx25.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28~\mathrm{mag}~\mathrm{arcsec}^{-2}$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32~\mathrm{mag}~\mathrm{arcsec}^{-2}$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into luminous stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the Universe using LSST to at least a surface brightness level of $30~\mathrm{mag}~\mathrm{arcsec}^{-2}$. +To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5~\mathrm{mag}~\mathrm{arcsec}^{-2}$ and that from a space telescope typically an order of magnitude fainter $\approx25.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28~\mathrm{mag}~\mathrm{arcsec}^{-2}$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32~\mathrm{mag}~\mathrm{arcsec}^{-2}$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into luminous stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the universe using LSST to at least a surface brightness level of $30~\mathrm{mag}~\mathrm{arcsec}^{-2}$. } ~\\ -\activities{The key activities for this task are as follows: -\begin{enumerate} -\item Production of simulated data e.g. from new hydro-dynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. -\item Analysis of simulated images to ensure that LSB galaxies can be accurately detected -\item The development of new object detection software specifically designed for the detection of LSB galaxies, in particular: -\begin{itemize} -\item Objects with large size. -\item Objects near or melted with large size, bright galaxies. -\item Highly irregular and distorted objects. -\end{itemize} -\item Identification of precursor data sets that can be used to test our methods. We can use data generated using numerical simulations to look at the types of galaxies produced that have sufficient angular momentum to become LSB disks. These disks can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. We will develop new methods of detecting LSB objects. These will include pixel clustering methods and the labeling of pixels with certain properties i.e. surface brightness level, SED shape, proximity to other similar pixels etc. We will trial our methods on other currently available data sets (KIDS, CFHT etc). -\item Production of realistic simulated LSST images of nearby dwarf galaxies (from high resolution hydro-dynamical simulations like New Horizon which has resolutions of tens of parsecs) -\item Identify nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools. -\item Develop and test the database search queries for finding candidates of several shapes and sizes. -\end{enumerate} +\activities{The key activities for this task include the production of simulated data e.g. from new hydrodynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. Once produce, analysis of simulated images is needed to ensure that LSB galaxies can be accurately detected. This analysis will require the development of new object detection software specifically designed for the detection of LSB galaxies, in particular objects with large size, near or melted with brighter galaxies, and highly irregular and distorted objects. Precursor data sets that can be used to test our methods +will need to be identified. Data generated using numerical simulations can be used to examine the types of galaxies produced that have sufficient angular momentum to become LSB disks. These disks can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. +New methods of detecting LSB objects will be engineered, including pixel clustering methods and the labeling of pixels with certain properties, i.e., surface brightness level, SED shape, and proximity to other similar pixels. We will trian our methods on other currently available data sets (KIDS, CFHT etc). These analyses will further +require the production of realistic simulated LSST images of nearby dwarf galaxies (from high resolution hydrodynamical simulations like New Horizon which has resolutions of tens of parsecs), the +identification of nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools, +and the development and testing of the database search queries for finding candidates of several shapes and sizes. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Realistic mock LSST images of LSB galaxies from simulations. \item Detection and selection algorithms for LSB galaxies from observational datasets. @@ -82,11 +74,12 @@ \subsection{Faint Outskirts of Galaxies} \begin{task} \label{task:lsb:faint_outskirts} \motivation{ -The outskirts of nearby galaxies, loosely defined as the regions below $25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in HI, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). +The outskirts of nearby galaxies, loosely defined as the regions below $ +25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in neutral +hydrogen, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). The main science driver for studying the outskirts of galaxies is understanding the assembly, formation, and evolution of galaxies. These studies can be performed +through imaging and subsequent parameterization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar halos. From numerical modeling, it is known that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo are tightly related to the accretion and merging history, as illustrated by the imaging of structures in the stars in the outskirts of M31 and other local group galaxies. ~\\ -The main science driver here is understanding the assembly, formation, and evolution of galaxies. This can be studied through imaging and subsequent parametrization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar haloes. From numerical modelling we know that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo, are tightly related to the accretion and merging history. This is illustrated by the imaging of the stars in the outskirts of M31 and other local group galaxies, which show detailed structure. -~\\ -Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000's of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and then foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, which needs to be understood before stacking. They will affect some items more than others, e.g. linear features such as tidal streams will be less affected by overall PSF. +Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000s of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, need to be understood before stacking. The systematics will affect some measurements more than others -- for instance, linear features such as tidal streams will be less affected by overall PSF. } ~\\ \activities{ @@ -95,7 +88,7 @@ \subsection{Faint Outskirts of Galaxies} Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item Information on the stability and spatial constancy of the LSST PSF. \item Improved control over systematics for LSB science, and other fields including weak lensing. @@ -110,32 +103,33 @@ \subsection{Intracluster Light} \begin{task} \label{task:lsb:icl} \motivation{ -The Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. It is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. +Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. ICL is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. \\ Some outstanding scientific questions, which LSST could solve are as follows: \begin{itemize} \item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? -\item Does it contain significant substructure? +\item Does the ICL contain significant substructure? \item What is its surface brightness profile and does it have a color dependence, which would indicate age/metallicity gradients? \item Where does the ICL begin and the large diffuse cD halo of the Brightest Cluster Galaxy (BCG) end and do they have the same origin? \end{itemize} } ~\\ \activities{ -The preparation work for the ICL component of the LSB case involves investigating LSST-specific issues for large LSB features and the known properties of the ICL itself. -\\ -The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce LSB signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial for our team to liaise with LSST strategy, telescope, instrument and data reduction teams. -\\ -The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters we can model whether we expect to see ICL at higher redshifts (up to z=1) given dimming, stellar population evolution and the surface brightness limits of LSST. This is crucial if we want to look for an evolution in ICL properties. If we want to study low mass groups or high redshift systems, we may need/want to stack populations to obtain a detection of the ICL. It is important to assess whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members or would faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. +The preparatory work for the ICL component of the LSB case involves investigating LSST-specific issues for large LSB features and the known properties of the ICL itself. +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce LSB signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial to liaise with the LSST Project's strategy, telescope, instrument and data reduction teams. +~\\ +The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters one can model whether it is expected to see ICL at higher redshifts (up to $z=1$) given dimming, stellar population evolution, and the surface brightness limits of LSST. This consideration is crucial for determining possible evolution in ICL properties. For +studies of low mass groups or high redshift systems, it may be required to stack populations to obtain a detection of the ICL. +An assessment of whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members is important, as is a determination of whether faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: \begin{enumerate} \item An investigation of telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. \item An investigation of observation specific issues that affect the measurement of large LSB features: dither pattern strategy. \item An investigation of image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. \item A feasibility analysis: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? -\item An investigation of the feasibility of stacking clusters to obtain faint ICL - this is difficult as will require very strong masking of even the faintest observable cluster members. +\item An investigation of the feasibility of stacking clusters to obtain faint ICL - this is difficult and will require very strong masking of even the faintest observable cluster members. \end{enumerate} } \end{task} From 5f2f8fd9eb3f276cf6bdefb28378b14a18df4ac0 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 02:13:03 -0700 Subject: [PATCH 32/64] Edits to the Photo-z section. --- task_lists/photo_z/photo_z.tex | 36 +++++++++++++++++++++------------- 1 file changed, 22 insertions(+), 14 deletions(-) diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index 056b243..476b49e 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -1,11 +1,11 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} {\justify -For a photometric survey like LSST, our abilities to accurately measure distances to huge samples of galaxies, to constrain the stellar masses, ages, and metallicities of objects as a function of time, to measure the spatial clustering of galaxy populations, and to identify unusual objects at various cosmic epochs will all rely heavily on +For a photometric survey like LSST, our abilities to accurately measure distances to huge samples of galaxies, constrain the stellar masses, ages, and metallicities of objects as a function of time, measure the spatial clustering of galaxy populations, and identify unusual objects at various cosmic epochs will all rely heavily on photometric redshift measurements. The following important preparatory science tasks address both the systematic uncertainties on photometric redshifts associated with the LSST observatory and with the requisite stellar population synthesis models. -It is important to note that a major effort within the LSST Dark Energy Science Collaboration (DESC) is focused on the development of photometric redshift algorithms for LSST, including the incorporation of joint probability distributions between redshift and astrophysical parameters of interest for the study of galaxy evolution. Efforts within the Galaxies collaboration should be able to leverage work happening in DESC and build upon it to ensure that photometric redshifts optimized for galaxy science are available. +A major effort within the LSST Dark Energy Science Collaboration (DESC) is focused on the development of photometric redshift algorithms for LSST, including the incorporation of joint probability distributions between redshift and astrophysical parameters of interest for the study of galaxy evolution. Efforts within the Galaxies collaboration should be able to leverage work happening in DESC and build upon it to ensure that photometric redshifts optimized for galaxy science are available. \begin{tasklist}{PZ} \subsection{Impact of Filter Variations on Galaxy Photometric Redshift Precision} @@ -13,17 +13,21 @@ \subsection{Impact of Filter Variations on Galaxy Photometric Redshift Precision \begin{task} \label{task:photo_z:filter_variations} \motivation{ -For accurate photometric redshifts, well-calibrated photometry is essential. Variations in the telescope system, particularly the broad-band $ugrizy$ filters, will need to be very well understood if we are to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. Preliminary tests show that the filter variation may have a relatively small impact, but further tests are necessary to ensure that these variations will not dominate the photometric error budget.\\ +For accurate photometric redshifts, well-calibrated photometry is essential. Variations in the telescope system, particularly the broad-band $ugrizy$ filters, will need to be very well understood to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. Preliminary tests show that the filter variation may have a relatively small impact, but further tests are necessary to ensure that these variations will not dominate the photometric error budget.\\ ~\\ -In addition, the effective passbands of the LSST filters will depend significantly upon atmospheric conditions and airmass, particularly in the $y$ filter. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of large-scale environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane or between, incorporating approximate models for galaxy SEDs (which may be based upon photometric redshift estimates). Such corrections may be imperfect and leave residuals, particularly for specific populations with unusual SEDs.~\\ +In addition, the effective passbands of the LSST filters will depend significantly upon atmospheric conditions and airmass, particularly in $y$-band. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of large-scale environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane or between, incorporating approximate models for galaxy SEDs (which may be based upon photometric redshift estimates). Such corrections may be imperfect and leave residuals, particularly for specific populations with unusual SEDs.~\\ ~\\ -Tests of the amplitude of these residuals and their impact on photo-$z$'s, especially for particular object classes of interest, will be important for determining to what degree DM data products can be used directly for galaxies work.If the variations can be calibrated well, they could potentially be used to further improve, rather than degrade, photo-$z$ performance. The variations in filter response can offer up a small amount of extra information on the object SED given the slight variation in effective filter wavelength, particularly for objects with strong narrow features (i.e., emission lines). Tests of how much information is gained can inform whether or not the extra computational effort required for computing photo-$z$’s that incorporate the effective passband from every individual LSST observation of an object will be superior to estimates incorporating DM measurements corrected to the six fiducial filters of the survey. All topics discussed above are also being examined by the LSST Dark Energy Science Collaboration Photometric Calibration working group, and there are several related tasks described in the DESC Science Roadmap document\footnote{The DESC Science Roadmap is available at: \url{http://lsst-desc.org/sites/default/files/DESC_SRM_V1_0.pdf}}. Communication and coordination with the Photometric Calibration group will be very important to maximize the impact of work on these areas of shared interest. +Tests of the amplitude of these residuals and their impact on photo-$z$'s, especially for particular object classes of interest, will be important for determining to what degree DM data products can be used directly for galaxies work. +If the variations can be calibrated well, they could potentially be used to further improve, rather than degrade, photo-$z$ performance. +The variations in filter response can offer up a small amount of extra information on the object SED given the slight variation in effective filter wavelength, particularly for objects with strong narrow features (i.e., emission lines). +Tests of how much information is gained can inform whether or not the extra computational effort required for computing photo-$z$'s that incorporate the effective passband from every individual LSST observation of an object will be superior to estimates incorporating DM measurements corrected to the six fiducial filters of the survey. All topics discussed above are also being examined by the LSST Dark Energy Science Collaboration Photometric Calibration working group, and there are several related tasks described in the DESC Science Roadmap document\footnote{The DESC Science Roadmap is available at: \url{http://lsst-desc.org/sites/default/files/DESC_SRM_V1_0.pdf}}. Communication and coordination with the Photometric Calibration group will be very important to maximize the impact of work on these areas of shared interest. } ~\\ \activities{ Tests of the SED-dependent residuals in photometric redshifts induced by photometric calibration systematics at the expected level.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Quantification of the amplitude of photometric uncertainties in the LSST filters due to variation in filter throughputs and atmospheric transmission. \item Identification of SED classes where residuals in DM calibration of effective passbands will be prominent. @@ -36,7 +40,7 @@ \subsection{Photometric Redshifts in the LSST Deep Drilling Fields} \begin{task} \label{task:photo_z:ddf} \motivation{ -The LSST Deep Drilling Fields present different challenges than the main survey, including increasing rates of confusion between sources, but they also provide the ability to use subsets of the data to construct higher resolution images due to the large number of repeat observations. These properties allow investigations of galaxies of brightness which are close to the noise floor in the main survey. Having an accurate error model is essential for optimal photo-z performance; the larger number of repeat observations in the Deep Drilling Fields enables empirical checks on the magnitude and flux uncertainties generated by the LSST pipeline, through both higher signal-to-noise stacks and using subsets of the data to model the uncertainties. As LSST imaging data will not be available for several more years, such studies of subset stacks to examine seeing and error properties would have to use pre-existing data sets, e.~g.~Hyper Suprime Camera data, when testing such algorithms and putting needed infrastructure in place so that it can be used once LSST data is flowing.\\~\\ +The LSST Deep Drilling Fields present different challenges than the main survey, including increasing rates of confusion between sources, but they also provide the ability to use subsets of the data to construct higher resolution images due to the large number of repeat observations. These properties allow investigations of galaxies of brightness which are close to the noise floor in the main survey. Having an accurate error model is essential for optimal photo-z performance; the larger number of repeat observations in the Deep Drilling Fields enables empirical checks on the magnitude and flux uncertainties generated by the LSST pipeline, through both higher signal-to-noise stacks and using subsets of the data to model the uncertainties. As LSST imaging data will not be available for several more years, such studies of subset stacks to examine seeing and error properties would have to use pre-existing data sets, e.~g.~HyperSuprimeCam data, when testing such algorithms and putting needed infrastructure in place so that it can be used once LSST data is flowing.\\~\\ In addition to providing useful information about main-survey photometric redshift quality, the Deep Drilling Fields will pose particular challenges for photometric redshift determination, as spectroscopy for complete samples down to the DDF depth for photo-$z$ training and calibration will be completely infeasible, and the DDF area is likely too small for high-precision calibration by cross-correlation techniques. } ~\\ @@ -44,7 +48,8 @@ \subsection{Photometric Redshifts in the LSST Deep Drilling Fields} Tests of confusion limits in deeper coadds than available in the main survey, as well as improvements enabled by ''best seeing" subsamples on precursor data sets. Tests of the flux error model using subsets and higher signal-to-noise coadds. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Studies of confusion and deblending in deep stacks and ``best seeing" conditions using precursor data sets. \item Estimates of gains in studying faint galaxy populations at higher signal-to-noise than available in the main survey. @@ -73,7 +78,8 @@ \subsection{Multivariate Physical Properties of Galaxies from Photometric Redshi Activities will consist of testing whether the determination of physical parameters and photo-$z$ should be performed jointly or not, based on training sets with spectroscopic redshifts at a range of redshifts. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-$z$ and properties, together with the software to be used. \item With LSST data: in consultation with the DESC Photo-z working group, the production of catalogs of properties to be used by the collaboration. @@ -92,7 +98,8 @@ \subsection{Identifying Spectroscopic Redshift Training Sets for LSST} \activities{In coordination with other large surveys, collate existing spectroscopic redshift data over both DDF and wider fields, and assess the biases due to selection and redshift incompleteness for each spectroscopic data set. Assess the robustness of existing data, and determine color spaces where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. This work should become much more efficient once PFS and MOONS become available. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item A list of existing {\it robust} spectroscopic objects, and identified gaps in the currently available training samples. \item Telescope proposals for spectroscopic campaigns to fill in the sample gaps. @@ -116,11 +123,11 @@ \subsection{Simulations with Realistic Galaxy Colors and Physical Properties} If we then assume that the simulations are valid beyond the test intervals, we can use them as a testbed to develop improved algorithms for a wide variety of applications, e.~g.~selecting specific sub-populations of galaxies. One key aspect of this work is that spectral energy distributions in simulations cannot be generated from discrete templates, but instead must span a continuous range of properties. If only a finite set of restframe SEDs are used in the simulation, the photo-$z$ problem would be unnaturally simplified and falsely strong photometric redshift predictions would result. Thus a method is required that simultaneously reproduces galaxy colors without resorting to a restricted set of SEDs. For example, this could be done by creating complete SEDs based on an extended set of principal components (e.g., extending the $kcorrect$ or EAZY basis set), though in general additional constraints are required with PCA-like techniques to ensure that unphysical spectra are not generated.\\ ~\\ -With sufficiently realistic simulations that reproduce the ensemble of galaxy star formation histories and the mapping between those histories and spectral energy distributions, we can use simulated catalogs to test techniques for identifying specific galaxy sub-populations. For some studies, we may wish to examine the relationship between galaxies in specific sub-populations and their large-scale structure environment. Thus, realistic density and clustering properties are also important in the simulation. There are a wide variety of techniques that may be used for environmental measures, operating on a variety of scales. As small-scale measurements can be noisy and/or washed out by photometric redshift errors, it may be more effective to measure the average overdensity/environment as a function of galaxy properties, rather than the reverse.\\ -~\\ +With sufficiently realistic simulations that reproduce the ensemble of galaxy star formation histories and the mapping between those histories and spectral energy distributions, we can use simulated catalogs to test techniques for identifying specific galaxy sub-populations. For some studies, we may wish to examine the relationship between galaxies in specific sub-populations and their large-scale structure environment. Thus, realistic density and clustering properties are also important in the simulation. There are a wide variety of techniques that may be used for environmental measures, operating on a variety of scales. As small-scale measurements can be noisy and/or washed out by photometric redshift errors, it may be more effective to measure the average overdensity/environment as a function of galaxy properties, rather than the reverse. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Determination of a list of which physical parameters are important for galaxy science. \item Compiling observable datasets that can be used as comparators for simulated datasets. @@ -149,7 +156,8 @@ \subsection{Incorporating Galaxy Size and Surface Brightness into Photometric Re If incorporating morphological information does in fact yield improvements, the next step would be the development of Bayesian priors for redshift given galaxy photometry and morphology measurements for incorporation into template-based methods. This may be done using either pipeline-processed simulated datasets (if they are sufficiently realistic) or real observations with spectroscopic redshifts. Tests will then show the performance of photometric redshifts incorporating morphological priors relative to performance using galaxy photometry alone. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Tests of LSST DM algorithms for measuring morphological parameters for galaxies. \item A cross-matched catalog containing objects with known redshifts and DM pipeline-measured morphology measurements. From 2e57f04bc9835f1d8cd7af989bf220a6fd800efb Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 02:17:50 -0700 Subject: [PATCH 33/64] Edits to TMC. --- task_lists/tmc/tmc.tex | 18 +++++++++++------- 1 file changed, 11 insertions(+), 7 deletions(-) diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index 26d3540..3993d7a 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -28,9 +28,10 @@ \subsection{Image Simulations of Galaxies with Complex Morphologies} ~\\ \activities{ Activities include creating synthetic LSST observations containing a wide variety of galaxies with complex morphologies, for the purpose of testing analysis algorithms such as de-blending, photometry, and morphological characterization. Supporting activities include creating databases of galaxy images from models (such as cosmological simulations) or existing optical data, analyzing them using LSST software or prototype algorithms, and distributing the findings of these studies. These analyses may involve small subsets of the sky and do not necessarily require very-large-area image simulations or need to match known constraints on source density. -Results will include predicting the incidence of measured morphological features, optimizing level-3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} +Results will include predicting the incidence of measured morphological features, optimizing Level 3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Creating synthetic LSST images of galaxies with complex morphology from simulations. \item Creating synthetic LSST images based on prior observations in similar filters. @@ -47,7 +48,7 @@ \subsection{New Theoretical Models for the Galaxy Distribution} \begin{task} \label{task:tmc:galaxy_distribution} \motivation{ -OMeeting the challenge of building synthetic, computer-generated mock surveys for use in the preparation +Meeting the challenge of building synthetic, computer-generated mock surveys for use in the preparation of extragalactic science with LSST will require the assembly of experts in key theoretical areas. LSST will collect more data than contained in the current largest survey, the SDSS, every night for ten years. The analysis of such data demands a complete overhaul of traditional techniques and will require the incorporation of ideas from different disciplines. @@ -58,7 +59,7 @@ \subsection{New Theoretical Models for the Galaxy Distribution} the scientific potential of the new surveys, rather than sampling errors driven by the volume mapped. A variety of viable, competing cosmological models already provide only subtly discernable signals in survey data. -Distinguishing between the models requires that we build the best possible theoretical predictions to understand the measurements and their subsequent analysis, and to +Distinguishing between the models requires the best possible theoretical predictions to understand the measurements and their subsequent analysis, and to understand the uncertainties on the measurements. } ~\\ @@ -71,7 +72,8 @@ \subsection{New Theoretical Models for the Galaxy Distribution} The large volume simulations will extend beyond the volume of the target survey, allowing a robust assessment of the systematic uncertainties on large-scale structure measurements.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Physically motivated mock galaxy catalogues on volumes larger than those sampled by LSST, with a consistently evolving population of galaxies. \item Base catalogues of dark matter haloes and their merger trees suitable for use by theoretical models for populating these with galaxies (halo and subhalo occupation/abundance matching techniques). @@ -103,7 +105,8 @@ \subsection{Design of New Empirical Models for the Galaxy Distribution.} empirical models relevant for upcoming surveys that will probe regimes that remain largely unmapped.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Predictions for the evolution of clustering from physical models. \item Enhanced paramertizations for empirical models with reduced freedom, greater @@ -126,7 +129,8 @@ \subsection{Estimating Uncertainties for Large-Scale Structure Statistics} Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, such as those based on perturbation theory. Coordinate with Dark Energy Science Collaboration Working Groups, as these covariance matrices can also inform Cosmological parameter constraints.} ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Physically motivated estimates of covariance matrices for galaxy occupation (and other) parameter searches. \end{enumerate} From dec383e4cfc8f5636a0f261c92e1d5efc2a12db5 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 02:28:42 -0700 Subject: [PATCH 34/64] Edits to auxillary data section. --- task_lists/aux/aux.tex | 76 +++++++++++++++++++----------------------- task_lists/tmc/tmc.tex | 4 +-- 2 files changed, 37 insertions(+), 43 deletions(-) diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex index 9ce7445..496b0e5 100644 --- a/task_lists/aux/aux.tex +++ b/task_lists/aux/aux.tex @@ -1,6 +1,6 @@ \section{Auxiliary Data}\label{sec:tasks:aux} {\justify -While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing and upcoming external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, x-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation, and during, LSST operations it is therefore prudent to ensure appropriate access, use-ability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. +While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing and upcoming external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, x-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation for and during LSST operations it is therefore prudent to ensure appropriate access, usability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. @@ -16,29 +16,25 @@ \subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} \activities{ Several activities are necessary to compile this spectroscopic database: \begin{enumerate} -\item Establishment of a database structure capable of accommodating and serving both spectra and derived data products including fast SQL database queries -\item Ingestion of existing key public datasets including, for example: 2dFGRS, SDSS, 2QZ, 2SLAQ, 6dF, MGC, GAMA, ESP, VVDS, VIPERS -\item A process for establishing quality control and homogenization of datasets including assignment of revised quality flags -\item A pathway for ingesting future datasets as they become available and potentially in advance via MOU arrangements, e.g., TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. +\item Establishment of a database structure capable of accommodating and serving both spectra and derived data products including fast SQL database queries. +\item Ingestion of existing key public datasets including, for example: 2dFGRS, SDSS, 2QZ, 2SLAQ, 6dF, MGC, GAMA, ESP, VVDS, VIPERS. +\item A process for establishing quality control and homogenization of datasets including assignment of revised quality flags. +\item A pathway for ingesting future datasets as they become available and potentially in advance via MOU arrangements, e.g., TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid, etc. \end{enumerate} Approximately 6 million spectroscopic redshifts are known, with the majority of these already in the public domain; along with associated flux and wavelength calibrated spectra. In addition, derived parameters also exist for many of these spectra including, but not limited too, redshifts, equivalent widths, velocity dispersions, line asymmetries etc. Many of these measurements have been made using bespoke software specific to each originating survey (e.g., SDSS v 2dFGRS), creating an inhomogeneous network of data, measurements and quality control flags within the LSST footprint. -\\ In addition, in the next decade a number of new surveys will expand these measurements from millions to tens of millions of spectra through facilities and programs such as LAMOST, 4MOST, DESI as well as coarse spectroscopic information via GRISM data from Euclid and eventually WFIRST, leading to a wealth of spectroscopic data which will be invaluable to LSST. -\\ The community has two specific problems, i) collating this data and ii) ensuring quality control and standardization. Due to differing observing and analysis techniques not all spectroscopic measurements will be equal, and will depend on the resolution, signal-to-noise and precise software applied. -\\ Within reason some effort should be made to both collate and standardize the data with some provision of a uniform quality control process. At the bare minimum this should result in a database which contains the flux and wavelength calibrated spectra, links or copies of original derived products, and crucially, measurements using a uniform set of software analysis tools (e.g., to produce consistent redshift and equivalent width measurements) with some coherent cross-survey quality control flags. -\\ While this task sounds intimidating, this is exactly what has been achieved within the 200 square degrees of the Galaxy And Mass Assembly survey \citep{driver2011a,driver2016a,liske2015a} and an expansion of this process to the full LSST footprint is not unreasonable or impossible. However, this process needs to commence imminently if the database is to be in place for both LSST and the next generation of spectroscopic surveys. -\\ As the majority of LSST's footprint covers the Southern Hemisphere, where many (but not all) large spectroscopic surveys have been instigated from Australia, this task represents a potential contribution from the Australian LSST contingent. } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} -\item A useable and searchable database of spectra with associated derived products -\item Derived products using standardized analysis codes to measure redshifts, equivalent widths etc -\item A strategy for ingesting additional datasets as they become available +\item A useable and searchable database of spectra with associated derived products. +\item Derived products using standardized analysis codes to measure redshifts and equivalent widths, etc. +\item A strategy for ingesting additional datasets as they become available. \end{enumerate} } \end{task} @@ -50,43 +46,39 @@ \subsection{Panchromatic Imaging within the LSST Footprint} \begin{task} \label{task:aux:panchromatic} \motivation{ -LSST will only cover a small portion of the electro-magnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life-cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available x-ray, UV, IR, and radio data. -\\ +LSST will only cover a small portion of the electromagnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available x-ray, UV, IR, and radio data. While archives of these data exist independently, there is a dire need to establish a Universe database which federates these data in a coherent manner. One of the major concerns of such a database is the accurate multi-wavelength source identification and de-convolution in disparate data with wildly differing resolutions. For example, two closely separated sources in the LSST data may appear as a single source in lower resolution data. As such, significant errors will be made when simply table matching these photometric catalogues. -\\ The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFITs; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to x-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse x-ray halos, discrete x-ray sources and extended radio lobes). } ~\\ \activities{ Several activities are required: \begin{enumerate} -\item Database to host imaging data from diverse sources, including astrometric alignment -\item Software to define aperture in a specified (LSST) band -\item Software to measure flux across panchromatic data taking into account original aperture definition, facility resolution, signal-to-noise limitations, and any physical priors -\item Tool to serve imaging and photometric data either for individual or sets of objects +\item Database to host imaging data from diverse sources, including astrometric alignment. +\item Software to define aperture in a specified (LSST) band. +\item Software to measure flux across panchromatic data taking into account original aperture definition, facility resolution, signal-to-noise limitations, and any physical priors. +\item Tools to serve imaging and photometric data either for individual or sets of objects. \end{enumerate} As galaxies emit radiation across the entire electromagnetic spectrum it is important to be able to trace this breadth of emission deriving from different astrophysical processes. This is particularly important in the LSST optical wavebands where anywhere from 0-90 per cent of the radiation might be attenuated by dust and re-radiated in the far-IR. -\\ The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman- and the 4000Ang-breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. -\\ Finally, x-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star-formation. Unification across the wavelength range requires federation of these very disparate datasets. This will become an increasingly common problem as we move into the ear of Big Data, and hence is worth centralizing prior to LSST operations. -\\ Note a similar task has recently been achieved by the Galaxy And Mass Assembly team for a 200 square degree region \citep[see][and http://www/gama-survey.org/]{driver2016a} and can be extended to the full LSST footprint using similar techniques. } ~\\ -\deliverables{Deliverables over the next few years from the activities described above include: +\deliverables{%Deliverables over the next few years from the activities described above include: +~ \begin{enumerate} -\item A database capable of serving image cutouts at any location over the LSST footprint and any wavelength (see http://cutout.icrar.org/psi.php for a similar database over the GAMA regions). This database will include +\item A database capable of serving image cutouts at any location over the LSST footprint and any wavelength (see http://cutout.icrar.org/psi.php for a similar database over the GAMA regions). This database should include \begin{itemize} -\item x-ray maps from eROSITA +\item X-ray maps from eROSITA \item UV from GALEX -\item Optical from SkyMapper, DES, and Euclid -\item near-IR from VISTA and Euclid -\item mid-IR from WISE -\item far-IR from IRAS, Herschel, Spica -\item Radio continuum and HI from ASKAP(EMU,WALLABY,DINGO), MeerKAT (LADUMA, MIGHTEE, MeerKLASS) and eventually the SKA +\item Optical from SkyMapper, DES, and Euclid. +\item Near-IR from VISTA and Euclid. +\item Mid-IR from WISE. +\item Far-IR from IRAS, Herschel, and Spica. +\item Radio continuum and HI from ASKAP (EMU,WALLABY,DINGO), MeerKAT (LADUMA, MIGHTEE, MeerKLASS), and eventually the SKA. \end{itemize} -\item Derived panchromatic photometry (on the fly or pre-processed) +\item Derived panchromatic photometry (on the fly or pre-processed). \end{enumerate} } \end{task} @@ -106,15 +98,16 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} (b) adaptive optics for these observations filters out the lower surface brightness features such as the rotating disk \citep[see for a review ][]{glazebrook2013a}, and (c) these measurements are made for intrinsically bright samples of galaxies. -However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}.\\ -% +However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}. +~\\ The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b}, detailed kinematics \citep{trachternach2008a}, extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. -The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}.\\ -% +The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}. +~\\ For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), -an accurate photometry measurement, and a disk inclination. The last two critical measurements will be provided by LSST imaging (see XX and YY).\\ -There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST confirmed deep drilling fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments. \\ +an accurate photometry measurement, and a disk inclination. The last two critical measurements will be provided by LSST imaging. +There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST confirmed deep drilling fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments. +~\\ Two other surveys represent the progressively wider/shallower H\,{\sc{i}} survey tiers with the ASKAP telescope \citep{johnston2007a}: DINGO, a survey of the GAMA fields \citep[][Meyer+ {\em in prep}]{driver2009a,duffy2012a,meyer2015a} and WALLABY, the Southern Sky H\,{\sc{i}} survey \citep[][Koribalski+ {\em in prep}]{duffy2012a}. A benefit of the MeerKAT and ASKAP radio surveys is that they are conducted commensally: radio continuum and 21 cm emission line (H\,{\sc{i}}) are observed at the same time. The combination The survey strategy from wide and shallow to single deep field (WALLABY-DINGO-MIGHTEE-LADUMA) is designed to beat down cosmic variance effectively \citep[see e.g.,][]{maddox2016a}. @@ -129,11 +122,12 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} \end{enumerate} } ~\\ -\deliverables{Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Robust and accurate inclination estimates from morphological fits/models. \item Accurate galaxy photometry from deep drilling stacks. -\item stacking code for H\,{\sc{i}} spectra. +\item Stacking code for H\,{\sc{i}} spectra. \end{enumerate} } \end{task} diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index 3993d7a..2b42299 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -82,8 +82,8 @@ \subsection{New Theoretical Models for the Galaxy Distribution} } \end{task} -\subsection{Design of New Empirical Models for the Galaxy Distribution.} -\tasktitle{Design of New Empirical Models for the Galaxy Distribution.} +\subsection{Design of New Empirical Models for the Galaxy Distribution} +\tasktitle{Design of New Empirical Models for the Galaxy Distribution} \begin{task} \label{task:section:title} \motivation{ From 6745533e3441fa81e2424450590f67802e589620 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 02:34:11 -0700 Subject: [PATCH 35/64] Formatting spacing near deliverable lists. --- task_lists/agn/agn.tex | 6 ++++ task_lists/clss/clss.tex | 6 ++++ task_lists/ddf/ddf.tex | 3 ++ task_lists/galaxies/galaxies.tex | 47 ++++++++------------------------ task_lists/high_z/high_z.tex | 2 ++ task_lists/lsb/lsb.tex | 4 +++ 6 files changed, 32 insertions(+), 36 deletions(-) diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index 1ed338c..dd5747d 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -41,6 +41,7 @@ \subsection{AGN Selection from LSST Data} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Creation of a cross-matched catalog of known AGN selected and verified using different methods. \item Understanding of AGN variability sensitivity given the nominal LSST cadence. @@ -76,6 +77,7 @@ \subsection{AGN Host Galaxy Properties from LSST Data} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Characterization of the accuracy and precision afforded by the LSST dataset for the recovery of basic morphology properties as a function of AGN brightness and wavelength. @@ -115,6 +117,7 @@ \subsection{AGN Feedback in Clusters} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Investigation of the number of BCGs and the mass range of their clusters with redshift that LSST will likely observe. \item Compilation of existing and forthcoming radio and X-ray data available for AGN feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS, etc.). @@ -141,6 +144,7 @@ \subsection{AGN Variability Selection in LSST Data} Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate and study simulations using parameters selected from these models using observational constraints, and determine the appropriateness of simulations for carrying out various types of AGN variability science including power spectrum models, quasi-periodic oscillation searches, and binary AGN models.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Observational constraints on AGN variability models. \item Metrics for quantifying the efficacy of different survey strategies for AGN variability science. @@ -169,6 +173,7 @@ \subsection{AGN Photometric Redshifts from LSST Data} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Development of AGN host color selection criteria, and an identification of objects for which color selection might prove ambiguous or degenerate. \item Exploration of multiwavelength, morphological, or variability information that might break photo-$z$ degeneracies. @@ -199,6 +204,7 @@ \subsection{AGN Merger Signatures from LSST Data} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Characterization and optimization of the ability of the LSST Level 2 data to enable the detection of galaxy mergers with AGN. \item Identification of merging galaxy properties or categories that will prove challenging to measure using the LSST datasets. diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 7b8efae..6f6dc4d 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -41,6 +41,7 @@ \subsection{Cluster and Large Scale Structure Sample Emulator} LSST for cluster and group science.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Creation of a public LSST Extragalactic Sample Emulator with a simple user interface, allowing for the estimation of sample sizes @@ -92,6 +93,7 @@ \subsection{Identifying and Characterizing Clusters} systems at all redshifts.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Improved cluster identification algorithms that can be applied to LSST data once @@ -144,6 +146,7 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} survey will be examined.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item With an improved understanding of the strengths and weaknesses of different environment measures as applied @@ -199,6 +202,7 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} Theory and Mock Catalogs working group.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Guidance for LSST galaxy pipelines to include all the necessary information for measurements of the correlation function and related @@ -261,6 +265,7 @@ \subsection{Disentangling Complicated Lines-of-Sight} the determination of $p(z)$ for background galaxies.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item A new cluster-specific photometric redshift algorithm that can be applied to a list of cluster detections based on LSST @@ -315,6 +320,7 @@ \subsection{Forward Modeling of LSST Clusters and Groups} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item A Bayesian inference code to simultaneously model cluster shear profiles and scaling relations across the full range of halo mass of groups and clusters, diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index d628772..ea4d760 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -36,6 +36,7 @@ \subsection{Coordinating Ancillary Observations} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Workshops on LSST DDF supporting observations. \item Annually updated roadmap of supporting observations (conceived, planned, or executed). @@ -61,6 +62,7 @@ \subsection{Observing Strategy Cadence} The LSST observing strategy is optimized using the Operations Simulator (OpSim). The Project works with the community to develop both baseline observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Figures of Merit via MAF for use by OpSim in evaluating DDF strategies. \item Proposed observing strategies for DDFs with corresponding scientific rationale. @@ -94,6 +96,7 @@ \subsection{Data Processing} reflect the baseline observing plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The Science Collaborations need to work with the various projects to identify a clear path forward.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Science drivers and input into to the development of Level 2 processing for the DDFs. \item Specifications for galaxy evolution-oriented Level 3 DDF processing. diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 2ebd3bf..2f70af3 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -109,8 +109,8 @@ \subsection{Techniques for Finding Low Surface Brightness Features or Galaxies} useful resource for a wide variety of investigations. } ~\\ -\deliverables{ -Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Creations of realistic inputs of LSB galaxies or LSB features for the LSST image simulations. \item Development of algorithms for finding and measuring LSB features. @@ -183,8 +183,8 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} deciding on figures-of-merit for their performance. } ~\\ -\deliverables{ -%Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Production of realistic galaxy image inputs to the LSST ImSim team. \item Development of tests and figures of merit to quantify the effects on several science objectives; @@ -223,8 +223,8 @@ \subsection{Optimizing Galaxy Morphology Measurements} Given the very large data set expected from LSST, which will change on short timescales in terms of depth, morphological parameters (e.g. CAS) will likely need to be calibrated on realistic data from hydrodynamical simulations in cosmological volumes, possibly augmented by training sets classified by humans. Similarly, machine-learning algorithms will have to be developed and implemented using a mixture of realistic simulations and precursor datasets, such as the HyperSuprimeCam Survey. A series of ``classification challenges'' prior to the LSST survey could help to refine these techniques. } ~\\ -\deliverables{ -%Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Realistic galaxy image inputs from hydrodynamical simulations and precursor datasets for classification tests. \item Human classification of image subsets for calibration of morphological parameters. @@ -251,6 +251,7 @@ \subsection{Galaxy Structural Parameters} } ~\\ \deliverables{%From the activities described above we expect to provide the following deliverables: +~ \begin{enumerate} \item Benchmarks for existing and newly developed tools for galaxy surface photometry. \item Automatic masks for star halos, spikes, and reflections, and related procedures for Level 3 analyses. @@ -311,6 +312,7 @@ \subsection{Optimizing Galaxy Mass Profile Measurements} ~\\ \deliverables{%Deliverables over the next several years from the activities %described above include the following: +~ \begin{enumerate} \item A selection for a set of template galaxies for use as lenses in ray-trace simulation, using a set of simulated models of galaxies at various stages in development. @@ -372,6 +374,7 @@ \subsection{Optimizing Galaxy Photometry} ~\\ \deliverables{ %Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Development of metrics for various science cases to help evaluate the Level 2 photometry. \item Realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies). @@ -408,8 +411,8 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} make the Bayesian inference practical. } ~\\ -\deliverables{ -%Deliverables over the next several years from the activities described above include the following: +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Development and refinement of techniques for constraining star-formation histories of large ensembles of galaxies. \item Model inputs to guide in developing these techniques. @@ -418,33 +421,5 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} } \end{task} - -%\begin{comment} - -%\subsection{Software Integration} -%\tasktitle{Software Integration} -% Level 2 and Level 3 software -%\begin{task} -%\label{task:gal:integration} -%\motivation{ -%The LSST Project is responsible for level 2 data processing, and the community -%is expected to any processing beyond that as level 3. Furthermore, some algorithms developed -%as part of the level 3 effort are expected to migrate to level 2. There needs -%to be strong coordination between the Project and the community for this concept -%to work. This includes training in developing level 3 software and community engagement in -%defining the requirements and interfaces. -%} -%~\\ -%\activities{ -%The most urgent activity is to develop some early prototypes of level 3 software -%so that the interfaces can be worked out on realistic use cases. -%} -%~\\ -%\deliverables{ADD SOMETHING} -%\end{task} - -%\end{tasklist} -%\end{comment} - \end{tasklist} } diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index 1cd69c2..914ac2d 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -46,6 +46,7 @@ \subsection{Optimizing Galaxy Photometry for High-Redshift Sources} Space Telescope data) may already commence.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Clarification of LSST Level 2 data suitability for high-redshift science, and an identification of any Level 3 needs. \item Development of Level 3 tools to produce optimal combined photometry from ground and space-based surveys, and the testing of these tools on existing datasets. @@ -88,6 +89,7 @@ \subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Incorporation of high-$z$ galaxies and quasars into LSST simulations with a realistic and representative set of properties. \item Incorporation pf cool Milky Way brown dwarfs into LSST simulations. diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 688df3b..5160399 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -27,6 +27,7 @@ \subsection{Low Surface Brightness Tidal Features} } ~\\ \deliverables{%Deliverables over the next several years (especially in the run up to commissioning) from the activities described above include the following: +~ \begin{enumerate} \item Realistic mock LSST images from cosmological simulations (including re-simulations of individual objects where necessary) with spatial resolutions of $\sim1$ kpc or better. \item Algorithms for finding galaxies with LSB tidal features, measuring the properties of these features and characterizing them i.e. using the properties of LSB tidal features to reconstruct the properties of the mergers which created them (e.g. mass ratios, time elapsed since the merger, etc.). @@ -59,6 +60,7 @@ \subsection{Low Surface Brightness Galaxies} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Realistic mock LSST images of LSB galaxies from simulations. \item Detection and selection algorithms for LSB galaxies from observational datasets. @@ -89,6 +91,7 @@ \subsection{Faint Outskirts of Galaxies} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item Information on the stability and spatial constancy of the LSST PSF. \item Improved control over systematics for LSB science, and other fields including weak lensing. @@ -124,6 +127,7 @@ \subsection{Intracluster Light} } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: +~ \begin{enumerate} \item An investigation of telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. \item An investigation of observation specific issues that affect the measurement of large LSB features: dither pattern strategy. From 44babd3014f8b3be5ef988a3b611e3ab3b8647e5 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 20 Jul 2017 02:59:37 -0700 Subject: [PATCH 36/64] Additional formatting. Version sent to LSST Galaxies 07/20/2017. --- task_lists/aux/aux.tex | 6 +++--- task_lists/clss/clss.tex | 14 +++++++------- task_lists/ddf/ddf.tex | 4 ++-- task_lists/galaxies/galaxies.tex | 16 ++++++++++------ task_lists/high_z/high_z.tex | 2 +- task_lists/lsb/lsb.tex | 24 ++++++++++++------------ 6 files changed, 35 insertions(+), 31 deletions(-) diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex index 496b0e5..0b87add 100644 --- a/task_lists/aux/aux.tex +++ b/task_lists/aux/aux.tex @@ -98,15 +98,15 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} (b) adaptive optics for these observations filters out the lower surface brightness features such as the rotating disk \citep[see for a review ][]{glazebrook2013a}, and (c) these measurements are made for intrinsically bright samples of galaxies. -However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}. +However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}.\\ ~\\ The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b}, detailed kinematics \citep{trachternach2008a}, extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. -The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}. +The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}.\\ ~\\ For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), an accurate photometry measurement, and a disk inclination. The last two critical measurements will be provided by LSST imaging. -There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST confirmed deep drilling fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments. +There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST confirmed deep drilling fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments.\\ ~\\ Two other surveys represent the progressively wider/shallower H\,{\sc{i}} survey tiers with the ASKAP telescope \citep{johnston2007a}: DINGO, a survey of the GAMA fields \citep[][Meyer+ {\em in prep}]{driver2009a,duffy2012a,meyer2015a} and WALLABY, the Southern Sky H\,{\sc{i}} survey \citep[][Koribalski+ {\em in prep}]{duffy2012a}. A benefit of the MeerKAT and ASKAP radio surveys is that they are conducted commensally: radio continuum and 21 cm emission line (H\,{\sc{i}}) are observed at the same time. The combination diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 6f6dc4d..dfd88c9 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -27,8 +27,8 @@ \subsection{Cluster and Large Scale Structure Sample Emulator} analyzed to determine the expected time-dependent depth of LSST detection images at each sky location. These depths can be converted into predicted numbers of galaxies as a function of redshift and -brightness \citep[e.g.,][]{awan2016a}. -\\ +brightness \citep[e.g.,][]{awan2016a}.\\ +~\\ To predict galaxy sample sizes as a function of physical parameters, the ``raw'' predicted galaxy numbers can be interfaced with semi-analytical models painted on large N-body @@ -192,8 +192,8 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} of a methodology to incorporate optimally the LSST photo-$z$ estimates with the angular data to obtain ``2.5-dimensions'' for pristine clustering -measurements. -\\ +measurements.\\ +~\\ These algorithms will be tested on realistic LSST mock catalogs, which will also later serve as a tool for obtaining error estimates on the measurements. @@ -252,13 +252,13 @@ \subsection{Disentangling Complicated Lines-of-Sight} cluster-specific algorithm. When available, t his algorithm will take account of the brightness and extent of X-ray emission, over-density of galaxies as a function of magnitude and -colour, any available spectroscopic redshifts, and the amplitude and extent of +color, any available spectroscopic redshifts, and the amplitude and extent of any SZ decrement/increment. The algorithm will likely adopt a Bayesian hierarchical modeling approach to forward model the problem, and can be tested on existing datasets from surveys such as the Local Cluster Substructure Survey (LoCuSS), XXL, and HSC data processed by -DM Stack within LSST. -\\ +the DM Stack within LSST.\\ +~\\ This work links with efforts on deblending/ICL, forward modeling of cluster and groups, environmental measures, cluster detection, complementary data, and work in the DESC Clusters Working Group via diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index ea4d760..e0ca659 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -87,8 +87,8 @@ \subsection{Data Processing} } ~\\ \activities{ -Identify the most important DDF-specific science drivers and any processing requirements distinct from the WFD survey. Coordinate with the Project and Science Collaborations to provide a coherent set of specifications and priorities for data processing. -\\ +Identify the most important DDF-specific science drivers and any processing requirements distinct from the WFD survey. Coordinate with the Project and Science Collaborations to provide a coherent set of specifications and priorities for data processing.\\ +~\\ Develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection). This activity may stress the inputs to the LSST image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low surface brightness features. Use of the supporting data sets in Level 2 or 3 processing requires careful thought. For example, pixel-level information from either Euclid or WFIRST may improve source identification and photometry. diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 2f70af3..23783a5 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -62,6 +62,7 @@ \subsection{Techniques for Finding Low Surface Brightness Features or Galaxies} Level 2 processing and observing strategies about the needs of LSB science, and (4) developing a strategy for finding and measuring LSB features through some combination of Level 2 measurements, database queries, and Level 3 processing.\\ +~\\ The insertion of realistic LSB features into LSST simulated images will provide ``data challenges'' to test methods for their extraction and measurement, allowing for the exploration of different techniques or algorithms for performing LSB @@ -83,6 +84,7 @@ \subsection{Techniques for Finding Low Surface Brightness Features or Galaxies} for very large-scale LSB features. Including a cirrus model as part of the LSST background estimation is worth considering, but the science benefit gained from the additional effort remains unclear.\\ +~\\ Because the LSST source extraction is primarily optimized for finding faint, barely-resolved galaxies, simultaneously finding large LSB structures and cataloging them as @@ -96,6 +98,7 @@ \subsection{Techniques for Finding Low Surface Brightness Features or Galaxies} LSB structures. Then, we need strategies for measuring these background maps, characterizing structures, and developing value-added catalogs to supplement the Level 2 database.\\ +~\\ For smaller structures, the database likely will contain pieces of the structure, either as portions of a hierarchical family of deblended objects or as separate catalog entries. Therefore, we need to @@ -139,7 +142,7 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} engagement with the science community will prove essential. While each data release will provide unique object IDs, if the first few generations of catalogs limit the science performed through data base -queries the consequences may impede early LSST science. +queries the consequences may impede early LSST science.\\ ~\\ For galaxies science, the issue of deblending holds critical importance. For example, searches for high-redshift galaxies via color selection @@ -153,7 +156,7 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} affect not just galaxy evolution science, but also lensing and large-scale structure studies. Another example involves the evolution of galaxy morphologies, where the effects of blending and confusion -may dominate measurement uncertainties. +may dominate measurement uncertainties.\\ ~\\ For the Level 2 catalogs, the planned approach involves using the Software Stack to deblend sources hierarchically and then @@ -174,6 +177,7 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} Inputs should come from hydrodynamical simulations, {\it Hubble} images, and images from precursor surveys such as CFHTLS, DES and HyperSuprimeCam. The Science Collaborations should help provide and vet inputs. \\ +~\\ More challenging activities involve developing techniques and algorithms to improve the deblending. When two galaxies at different redshifts overlap, using observations from all the LSST filters and perhaps even EUCLID and WFIRST might @@ -206,13 +210,13 @@ \subsection{Optimizing Galaxy Morphology Measurements} provide an important tool for constraining models of galaxy evolution. While simple measures of galaxy ellipticity and position angles may be sufficient for the dark energy science goals, more sophisticated measurements of morphology are needed for galaxy-evolution science. While the ``multifit'' approach of fitting simple parametric models to galaxy profiles is useful to zeroth order, this approach may be insufficient for the detailed morphological information -required for much of the galaxy science that is planned using LSST. -\\ +required for much of the galaxy science that is planned using LSST.\\ +~\\ For well-resolved galaxies the baseline requirement is to have separate measures of bulge and disk, spiral arm structure, measures of concentration, asymmetry, and clumpiness. These properties ought to be measured as part of the Level 2 processing, to enable database queries to extract subclasses of galaxies. Both parametric and non-parametric measures are desirable. While Level 3 processing methods will be developed to further optimize galaxy measurements, -the Level 2 products should supply enough information to select reasonable subsets of galaxies. -\\ +the Level 2 products should supply enough information to select reasonable subsets of galaxies.\\ +~\\ More importantly, while the traditional parameterizations of morphology described above will be useful, it is essential that new, more powerful methods of measuring galaxy morphology are developed and implemented, in order to leverage the exquisite volume and depth of LSST data. In this regard fast, machine-learning techniques \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that can efficiently separate LSST galaxy populations into different morphological classes are particularly relevant and powerful. } diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index 914ac2d..ed9403c 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -36,7 +36,7 @@ \subsection{Optimizing Galaxy Photometry for High-Redshift Sources} First, the potential need for Level 3 data products beyond the baseline LSST Level 2 catalog requires clarification. Photometric catalogues produced using the reddest LSST (e.g. $z$- or $y$-band) images as the detection image will prove critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. Similarly, negative fluxes for undetected galaxies together with their corresponding errorbars provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. Coordinating with the LSST Project to ensure the application of forced photometry in Level 2 in a manner appropriate for high-redshift galaxy -selection may be sufficient, or Level 3 data products may be required. +selection may be sufficient, or Level 3 data products may be required.\\ ~\\ Second, the determination of a suitable approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection will be required, including optimal measures of an optical-IR color for sources from these combined datasets. Sources resolved in Euclid or WFIRST data could be blended in LSST, and may therefore diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 5160399..dfb38e1 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -10,8 +10,8 @@ \subsection{Low Surface Brightness Tidal Features} \label{task:lsb:tidal_features} \motivation{ A key advantage of LSST over previous large area surveys (e.g. the SDSS) is its ability to detect LSB tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be two magnitudes deeper than the SDSS almost immediately after start of operations, and five magnitudes deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionize LSB tidal feature science, enabling, for the first time, the empirically reconstruction of the assembly histories of galaxies over at least two-thirds of cosmic time. -These histories provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth, and morphological transformation over a significant fraction of cosmic time. -\\ +These histories provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth, and morphological transformation over a significant fraction of cosmic time.\\ +~\\ Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected using criteria that are difficult to quantify (e.g. visual inspection, that can be somewhat subjective) or reproduce in theoretical models. Furthermore, previously used techniques for the identification and characterization of features, such as visual inspection, cannot be easily applied to the unprecedented volume of data expected from the next generation of telescopes like LSST. Given the depth and volume of data expected from LSST, it is critical that we automate the detection, measurement and characterization of LSB tidal features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. } ~\\ @@ -42,12 +42,12 @@ \subsection{Low Surface Brightness Galaxies} \begin{task} \label{task:lsb:galaxies} \motivation{ -The objective of this task is to investigate objects that have surface brightnesses much less than the background night sky and are typical of the Milky Way galaxy within which we live. Many authors have previously shown how difficult it is to identify LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to our own spiral galaxy. Thus, the universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy? -\\ -Additionally, the LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via neutral hydrogen surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies will still be quite easy to detect in LSST images. -\\ -At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting surface brightness limit of the LSST combined with the large field-of-view make this facility unique for probing the existence of large LSBs similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This issue is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception. -\\ +The objective of this task is to investigate objects that have surface brightnesses much less than the background night sky and are typical of the Milky Way galaxy within which we live. Many authors have previously shown how difficult it is to identify LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to our own spiral galaxy. Thus, the universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy?\\ +~\\ +Additionally, the LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via neutral hydrogen surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies will still be quite easy to detect in LSST images.\\ +~\\ +At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting surface brightness limit of the LSST combined with the large field-of-view make this facility unique for probing the existence of large LSBs similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This issue is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception.\\ +~\\ To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5~\mathrm{mag}~\mathrm{arcsec}^{-2}$ and that from a space telescope typically an order of magnitude fainter $\approx25.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28~\mathrm{mag}~\mathrm{arcsec}^{-2}$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32~\mathrm{mag}~\mathrm{arcsec}^{-2}$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into luminous stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the universe using LSST to at least a surface brightness level of $30~\mathrm{mag}~\mathrm{arcsec}^{-2}$. } ~\\ @@ -79,7 +79,7 @@ \subsection{Faint Outskirts of Galaxies} The outskirts of nearby galaxies, loosely defined as the regions below $ 25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in neutral hydrogen, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). The main science driver for studying the outskirts of galaxies is understanding the assembly, formation, and evolution of galaxies. These studies can be performed -through imaging and subsequent parameterization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar halos. From numerical modeling, it is known that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo are tightly related to the accretion and merging history, as illustrated by the imaging of structures in the stars in the outskirts of M31 and other local group galaxies. +through imaging and subsequent parameterization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar halos. From numerical modeling, it is known that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo are tightly related to the accretion and merging history, as illustrated by the imaging of structures in the stars in the outskirts of M31 and other local group galaxies.\\ ~\\ Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000s of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, need to be understood before stacking. The systematics will affect some measurements more than others -- for instance, linear features such as tidal streams will be less affected by overall PSF. } @@ -106,8 +106,8 @@ \subsection{Intracluster Light} \begin{task} \label{task:lsb:icl} \motivation{ -Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. ICL is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset. -\\ +Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. ICL is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset.\\ +~\\ Some outstanding scientific questions, which LSST could solve are as follows: \begin{itemize} \item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? @@ -119,7 +119,7 @@ \subsection{Intracluster Light} ~\\ \activities{ The preparatory work for the ICL component of the LSB case involves investigating LSST-specific issues for large LSB features and the known properties of the ICL itself. -The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce LSB signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial to liaise with the LSST Project's strategy, telescope, instrument and data reduction teams. +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce LSB signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial to liaise with the LSST Project's strategy, telescope, instrument and data reduction teams.\\ ~\\ The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters one can model whether it is expected to see ICL at higher redshifts (up to $z=1$) given dimming, stellar population evolution, and the surface brightness limits of LSST. This consideration is crucial for determining possible evolution in ICL properties. For studies of low mass groups or high redshift systems, it may be required to stack populations to obtain a detection of the ICL. From b9107e47327e76c6204e1f2018e8010c7f2a9e39 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Mon, 24 Jul 2017 11:02:09 -0700 Subject: [PATCH 37/64] Issue resolution on July 24 Resolves issues #2 , #10 , #8, #4 , #6 , #3 , #9 . --- authorlist.tex | 2 +- introduction/introduction.tex | 2 +- main.pdf | Bin 315294 -> 309135 bytes science_background/science_background.tex | 8 ++++---- task_lists/clss/clss.tex | 2 +- task_lists/lsb/lsb.tex | 2 +- 6 files changed, 8 insertions(+), 8 deletions(-) diff --git a/authorlist.tex b/authorlist.tex index b70a93a..2b4c94d 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -3,7 +3,7 @@ Cooper, Michael C.$^{3}$, Davies, Roger$^{4}$, Driver, Simon P.$^{5}$, -Ferguson, Annette$^{6}$, +Ferguson, Annette M. N.$^{6}$, Ferguson, Henry C.$^{7}$, Gawiser, Eric$^{8}$, Kaviraj, Sugata$^{9}$, diff --git a/introduction/introduction.tex b/introduction/introduction.tex index 83fa022..fd96e3d 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -31,7 +31,7 @@ The Dark Energy Science Collaboration (DESC) has taken the next logical step beyond the Science Book. They identified they most critical challenges the community will need to overcome -to realize LSST’s potential for +to realize the potential of LSST for measuring the nature and effects of dark energy. 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HB;5Z2xOEr` diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index abbcb94..1d6aefb 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -105,7 +105,10 @@ \subsection{Sky Estimation} \begin{task} \label{task:lsb:task_label} \motivation{ -LSST is likely to reveal new aspects of galaxies as low surface brightness objects. A relatively unexplored area is ultra-low surface brightness morphology and tails over a wide range of angular scales at levels of 31-32 mag/sq.~arcsec. Accurate sky estimation is key. There is a wide literature on failed attempts at unbiased sky estimation, from SDSS Photo, to SExtractor, to GalFit and PyMorph. The problem is typically encountered on scales large compared with the PSF where the counts from the object become indistinguishable from the ``sky'' counts. For example, fits of Sersic profiles [after PSF convolution] suffer from bias at large Sersic index due to sky mis-estimation (usually over-subtraction of sky due to systematic non-detection of fainter objects). +LSST is likely to reveal new aspects of galaxies as low surface brightness objects. A relatively unexplored area is ultra-low surface brightness morphology and tails over a wide range of angular scales at levels of 31-32 mag/sq.~arcsec. Accurate sky estimation is key. +The current state of the art algorithms, including SDSS Photo, SExtractor, GalFit, and PyMorph, experience challenges when +attempting unbiased sky estimation with deep data. +The problem is typically encountered on scales large compared with the PSF where the counts from the object become indistinguishable from the ``sky'' counts. For example, fits of Sersic profiles [after PSF convolution] suffer from bias at large Sersic index due to sky mis-estimation (usually over-subtraction of sky due to systematic non-detection of fainter objects). ~\\~\\ The discovery space is large: LSB features can exist on scales of arcseconds to many arcminutes -- spanning the majority of faint galaxies at redshift $z\sim 1$ to more nearby LSB galaxies. In the past it has been assumed that galaxies at all redshifts fit the profiles of low-z galaxies, and that the surface brightness level beyond $\sim$10 half light radii represents the sky background, as opposed to some extended LSB halo. In the era of LSST, we can afford to let the data speak for themselves. ~\\~\\ From d043e339ed53f62247281182b46461347e8d653d Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 2 Aug 2017 11:01:02 -0700 Subject: [PATCH 51/64] Previous LSB sky estimation changes did not propagate. --- task_lists/lsb/lsb.tex | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 1d6aefb..d8a74d5 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -106,7 +106,7 @@ \subsection{Sky Estimation} \label{task:lsb:task_label} \motivation{ LSST is likely to reveal new aspects of galaxies as low surface brightness objects. A relatively unexplored area is ultra-low surface brightness morphology and tails over a wide range of angular scales at levels of 31-32 mag/sq.~arcsec. Accurate sky estimation is key. -The current state of the art algorithms, including SDSS Photo, SExtractor, GalFit, and PyMorph, experience challenges when +Current state-of-the-art algorithms, including SDSS Photo, SExtractor, GalFit, and PyMorph, experience challenges when attempting unbiased sky estimation with deep data. The problem is typically encountered on scales large compared with the PSF where the counts from the object become indistinguishable from the ``sky'' counts. For example, fits of Sersic profiles [after PSF convolution] suffer from bias at large Sersic index due to sky mis-estimation (usually over-subtraction of sky due to systematic non-detection of fainter objects). ~\\~\\ @@ -119,7 +119,7 @@ \subsection{Sky Estimation} The research program starts with the current best methods, improving sky estimates on all angular scales via new algorithms, and then validation via simulations. The sky model in principle can be built using knowledge of the LSST system, locations of bright objects, the observational data, and statistical summaries of faint galaxy counts from HST. The first step is to detect all objects above a position-variable local sky estimate, masking them, and then growing the masks. The remaining pixels contain undetected galaxies, giving an over-estimate of the sky level around compact objects if left uncorrected. Statistical faint galaxy counts can help in making these corrections. When corrected, the Poisson noise from the remaining sky may be fit with a Gaussian. Even then, 3-$\sigma$ clipping and/or one-sided fitting may be required. This entire process is recursive on every angular scale where there are important sky components. ~\\~\\ LSST data management are planning novel algorithms of this general sort, and close coordination will be necessary and beneficial. The Dark Energy Science Collaboration (DESC) Science Roadmap \citep{LSSTDESC} -includes plans for realistic image-based simulations of the LSST sky. In coordination with DESC, the inclusion of faint, large-scale LSB objects in future Data Challenge catalogs and images would benefit all groups involved in testing algorithms and characterizing LSB objects. Improvements we make may be ingested by LSST DM as a Level-3 contribution. LSB ghosts due to reflected bright star light in the camera should also be included. +includes plans for realistic image-based simulations of the LSST sky. In coordination with DESC, the inclusion of faint, large-scale LSB objects in future Data Challenge catalogs and images would benefit all groups involved in testing algorithms and characterizing LSB objects. Improvements we make may be ingested by LSST DM as a Level 3 contribution. LSB ghosts due to reflected bright star light in the camera should also be included. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: From 7a5c7c3a1ee36ddcf277b0266ec56b0385f499d3 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 2 Aug 2017 11:10:15 -0700 Subject: [PATCH 52/64] Last requested change to LSB made. --- authorlist.tex | 2 +- main.pdf | Bin 305146 -> 304859 bytes task_lists/lsb/lsb.tex | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) diff --git a/authorlist.tex b/authorlist.tex index 68e4499..41d2a43 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -49,7 +49,7 @@ Borne, Kirk D.$^{41}$, and Members of the LSST Galaxies Science Collaboration -\vspace*{5mm} +\vspace*{4mm} {\justify\it\small $^{1}$Department of Astronomy and Astrophysics, University of California, Santa Cruz, Santa Cruz, CA 96054, USA, diff --git a/main.pdf b/main.pdf index 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z9whR{xE!i0P)=1^RV?8Sx3%V*G}lyAI(CgOp7anzQ1h&5#SIW;mo4YAzVcQ)Jie&x zMtd(z&6GJfbw&?{&6;zM*rZ$fjA_ORH`&}FYrr~i8tiobb&gj_9{za2!`0abU|Ks{ pd3d^8n>%6ByoUd2e(K?A?(XU9Zf%3f_n-712$P9PUR?q6{{U Date: Wed, 2 Aug 2017 11:28:45 -0700 Subject: [PATCH 53/64] Fixed PUC affiliation typo. Closes issue # --- authorlist.tex | 2 +- main.pdf | Bin 304859 -> 304817 bytes 2 files changed, 1 insertion(+), 1 deletion(-) diff --git a/authorlist.tex b/authorlist.tex index 41d2a43..975993c 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -65,7 +65,7 @@ $^{11}$Departamento de Astrof\'\i sica, Universidad de La Laguna, E-38206 La Laguna, Spain, $^{12}$University of Pittsburgh and PITT PACC, 3941 O{'}Hara St., Pittsburgh, PA 15260, USA, $^{13}$NOAO, 950 N. 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brightness, and color need to be estimated. +Group and +cluster populations must be identified in given ranges of redshift, richness, mass, and other physical parameters. } ~\\ @@ -57,53 +57,57 @@ \subsection{Identifying and Characterizing Clusters} \tasktitle{Identifying and Characterizing Clusters} \begin{task} \label{task:clss:clusters} -\motivation{ -LSST photometry will make it possible to -search for and study the galaxy populations of distant clusters and -proto-clusters over cosmological volumes. These -clusters are testbeds for theories of -hierarchical structure formation, -intergalactic medium heating, metal enrichment, and galaxy evolution. -However, standard approaches for identifying clusters, such as the red -sequence method, will be hampered by the limited wavelength coverage -of LSST. -For example, at $z \gtrsim 1.5$, near-IR photometry is required to -identify systems with Balmer/$4000$\AA\ breaks. -Exploration of optimal filter methods could improve cluster identification -\citep[e.g.,][]{bellagamba2017a}. -To maximize cluster science with LSST, new techniques -for cluster identification and the incorporate complementary data -from projects such as \emph{Euclid} or \emph{eROSITA} must be devised. +\motivation{ LSST photometry will make it possible to search for and +study the galaxy populations of distant clusters and proto-clusters over +cosmological volumes. These clusters are testbeds for theories of +hierarchical structure formation, intergalactic medium heating, metal +enrichment, and galaxy evolution. However, standard approaches for +identifying clusters, such as the red sequence method, will be hampered +by the limited wavelength coverage of LSST. For example, at $z \gtrsim +1.5$, near-IR photometry is required to identify systems with +Balmer/$4000$\AA\ breaks. +To maximize cluster science with LSST, new +techniques for cluster identification and the incorporate complementary +data from projects such as \emph{Euclid} or \emph{eROSITA} must be devised. +Exploration of optimal filter methods +\citep[e.g.,][]{bellagamba2017a} +could improve cluster identification in LSST data. } ~\\ -\activities{ -Using existing imaging datasets and simulations, algorithms need to be -developed and optimised to identify clusters at intermediate -and high redshift within the LSST footprint. -Specifically, this work should characterize the selection -function, completeness, and contamination rate for different cluster -identification algorithms. -Such characerizations require realistic light-cone simulations spanning extremely -large volumes, so as to capture significant numbers ($\gg10,000$) of -simulated galaxy clusters at high redshift. -Potential algorithms to be tested include adaptations of RedMaPPer -\citep{rykoff2014a} as well as methods that search for galaxy -overdensities over a range of scales \citep[e.g.,][]{chiang2014a,wang2016a}. -In parallel, a comprehensive search for multiwavelength data -(specifically IR and X-ray imaging) is needed to aid in the search for -high-$z$ clusters and in the confirmation and characterization of -systems at all redshifts.} +\activities{ Using existing imaging datasets and simulations, algorithms +need to be developed and optimized to identify clusters at intermediate +and high redshift within the LSST footprint. Specifically, this work +should characterize the selection function, completeness, and +contamination rate for different cluster identification algorithms. Such +characerizations require realistic light-cone simulations spanning +extremely large volumes, so as to capture significant numbers +($\gg10,000$) of simulated galaxy clusters at high redshift. Potential +algorithms to be tested include adaptations of RedMaPPer +\citep{rykoff2014a}, methods that search for galaxy +overdensities over a range of scales \citep[e.g.,][]{chiang2014a,wang2016a}, +and +methods designed to select clusters from joint optical/NIR/X-ray +datasets. In parallel, a comprehensive census of the available +multiwavelength data (specifically IR and X-ray imaging) is needed to +enable the new algorithms to be tested on real observational data, +including multiwavelength datasets co-located with LSST Commissioning +observations. It will also be necessary to develop algorithms to +homogenize the external datasets with LSST data at the pixel level, and +enable them to be served to the community.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item Improved cluster -identification algorithms that can be applied to LSST data once -science operations commence. -\item Compilation of ancillary data -that will be helpful in cluster identification and characterization, -such as X-ray (e.g.~XCS, eROSITA, etc.), SZ (Planck, SPT, ACT) and -radio (SKA and its pathfinders, SUMSS), within the LSST footprint. +\item New and improved cluster identification algorithms that can be +applied to LSST commissioning and survey data, and combined +LSST/NIR/X-ray data. +\item Compilation of auxillary data that will aide testing of algorithms +to identify and characterize clusters, such as near-infrared (e.g. +VISTA, UKIDSS), X-ray (e.g.~XMM-Newton, eROSITA, etc.), SZ (Planck, SPT, +ACT), and radio (SKA and its pathfinders, SUMSS) within the LSST +footprint. +\item Algorithms to match optimally and homogenize multiwavelength +data with LSST commissioning and survey data. \end{enumerate} } \end{task} @@ -114,7 +118,7 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} \label{task:clss:environment} \motivation{ Over the past decade, many studies have -shown that ``environment'' plays a important role in shaping galaxy +shown that environment plays a important role in shaping galaxy properties. For example, satellite galaxies in the local Universe exhibit lower star formation rates, more bulge-dominated morphologies, as well as older and more metal-rich stellar populations when compared @@ -138,7 +142,7 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} \activities{ Using mock galaxy catalogs created via semi-analytic techniques, tracers of local -galaxy density (i.e.~''environment'') measured on mock LSST +galaxy density (i.e.~``environment'') measured on mock LSST photometric samples will be compared to the underlying real-space density of galaxies or host halo mass. In addition to testing existing density measures, such as $N^{\rm th}$-nearest-neighbor distance and counts in @@ -186,8 +190,7 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} impacting the observed galaxies, the angular and radial completeness of the samples, and the detailed geometry of the survey (typically provided in terms of random catalogs that cover the full survey area). -Further efforts will concern the development, testing, and optimization of -algorithms for measuring galaxy clustering using LSST data. One aspect +One aspect to address is how best to handle the large data sets involved (e.g.~the LSST ``gold'' galaxy sample will include about $4$~billion galaxies over $18$,$000$~square degrees). Another issue is the development @@ -196,6 +199,8 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} the angular data to obtain ``2.5-dimensions'' for pristine clustering measurements.\\ ~\\ +Further efforts will concern the development, testing, and optimization of +algorithms for measuring galaxy clustering using LSST data. These algorithms will be tested on realistic LSST mock catalogs, which will also later serve as a tool for obtaining error estimates on the measurements. @@ -206,130 +211,182 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item Guidance for LSST galaxy pipelines to include all the necessary information for measurements of the correlation function and related statistics to take place once LSST data is available. This deliverable requires the engineering of ancillary products such as masks and maps of completeness as a function of galaxy properties. +\item Guidance for LSST galaxy pipelines to include all the necessary +information for measurements of the correlation function and related +statistics to take place once LSST data is available. This deliverable +requires the engineering of ancillary products such as masks and maps of +completeness as a function of galaxy properties. \item Development and refinement of techniques for measuring galaxy clustering of -large LSST galaxy samples. Together these will enable realizing the -full potential of LSST data for large-scale structure studies and -galaxy formation inferences thereof. +large LSST galaxy samples. Together, these techniques will enable the +full potential of LSST data for combined studies of large scale structure and +galaxy formation to be realized. \end{enumerate} } \end{task} -\subsection{Disentangling Complicated Lines-of-Sight} -\tasktitle{Disentangling Complicated Lines-of-Sight} +\subsection{Enabling Cluster Science through Robust Photometry and Photometric Redshifts} +\tasktitle{Enabling Cluster Science through Robust Photometry and Photometric Redshifts} \begin{task} \label{task:clss:los} \motivation{ -Lines-of-sight through galaxy clusters and groups rank among the -most challenging situations for measuring reliable photometric -redshifts as crowding of galaxies complicates the basic process -of galaxy photometry, and the presence of significant correlated -LSS complicates interpretation of any galaxy redshift distribution -computed by algorithms that ignore the -presence of LSS. Numerous science goals require the most robust -probabilistic statements possible as to the location of galaxies along -lines of sight through clusters, for example, identification of -background galaxies for weak-lensing, identification of faint cluster -members to study the evolution of the luminosity function in clusters, -identification of star-forming galaxies in clusters and their infall -regions to probe the physics of quenching of star formation. +Lines-of-sight through the cores of galaxy clusters and +groups (hereafter "clusters") rank among the most challenging +observations in which to identify robustly distinct extragalactic +objects and to infer a reliable photometric redshift distribution + $p(z)$ from the available data. +Challenges that must be overcome include crowding of galaxies, a highly +non-uniform background principally caused by the diffuse intracluster +light, and the presence of numerous background galaxies including some +that are highly distorted gravitational arcs. Given that the LSST +data will be accummulated over numerous epochs, there is significant +potential for the detection of transients along these lines-of-sight. +All of these complicating issues will be relevant to LSST commissioning data, +Wide Fast Deep survey data, and the Deep Drilling Fields, and all will +affect the basic processes of source detection and photometry. Beyond +photometry, further fundamental issues that require solutions include +ensuring that photometric redshift algorithms are +provided with spectral templates appropriate for +faint cluster members and prior information about the presence +of a galaxy cluster along the line-of-sight. +Science goals affected by these issues include weak-lensing measurements of the +mass-concentraion relation as a function of halo mass and redshift, +measuring the evolution of the galaxy luminosity function in clusters +and in particular the faint end slope, identifying star-forming galaxies +in clusters and their infall regions to probe the physics of quenching +of star formation, measuring the evolution of brightest cluster +galaxies, automated detection of strong-lensing clusters, and even +potential identification of strongly-lensed transients including +possible electromagnetic counterparts to gravitational wave sources. } ~\\ \activities{ -LSST will deliver the most information rich dataset ever in -relation to the masses and internal structures of clusters and their -infall regions. Moreover, the dataset can be enhanced significantly -via the addition of data at other wavelengths, including X-ray, -millimeter, and near-infrared. -~\\ -A tool is therefore envisaged that can take an input catalogue of -cluster centers that has been obtained from LSST or any other dataset -(e.g.~\emph{Planck}, \emph{eROSITA}), extract the -basic L2 LSST photometry of objects within a cone centered on the -cluster center, and compute the redshift probability distribution -$p(z)$ of each galaxy based on a -cluster-specific algorithm. When available, t -his algorithm will take account of the brightness and extent of X-ray -emission, over-density of galaxies as a function of magnitude and -color, any available spectroscopic redshifts, and the amplitude and extent of -any SZ decrement/increment. The algorithm will likely adopt a Bayesian -hierarchical modeling approach to forward model the problem, -and can be tested on existing datasets from surveys such as the -Local Cluster Substructure Survey (LoCuSS), XXL, and HSC data processed by -the DM Stack within LSST.\\ -~\\ -This work links with efforts on deblending/ICL, forward modeling -of cluster and groups, environmental measures, cluster detection, -complementary data, and work in the DESC Clusters Working Group via -the determination of $p(z)$ for background galaxies.} +LSST will deliver the most information rich dataset ever in relation to +the masses and internal structures of clusters and their infall regions. +Moreover, the dataset can be enhanced significantly via the addition of +data at other wavelengths, including X-ray, millimeter, and +near-infrared. To take full advantage of this opportunity, the +fundamental issues of source detection, photometry, and photometric +redshift inference along these crowded, challenging lines-of-sight must +be solved. Relevant activities include testing the Level 2 +software pipeline on both simulated LSST observations of clusters and +existing data including deep +observations of known clusters (e.g. from LoCuSS, Weighing the Giants, +CCCP, CFHT-LS, HSC, etc.). These tests will examine the ability of +the Level 2 pipeline to deblend correctly these crowded lines-of-sight, +and determine whether the Level 2 algorithm will require modifications +or a Level 3 algorithm for clusters will be needed. +Further activities include collating, reviewing, and selecting +appropriate cluster-specific galaxy spectral templates for deployment in +photometric redshift codes. +Another critical activity is to develop photometric +redshift algorithms that account for the brightness and +extent of X-ray emission, the overdensity of galaxies as a function of +magnitude and color, any available spectroscopic redshifts, and the +amplitude and extent of any SZ decrement/increment. +Such algorithms will +likely adopt a Bayesian hierarchical modeling approach to forward model +the problem, and can be tested on simulated data based on numerical +simulations and existing datasets (e.g. from XXL, XCS, HSC, LoCuSS, DES, +and others). +~\\~\\ +This work links with efforts on deblending and +intracluster light, forward +modeling of cluster and groups, environmental measures, cluster +detection, auxilliary data, and work in the DESC Clusters Working Group +via the determination of $p(z)$ for background galaxies.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item A new cluster-specific photometric redshift algorithm that can be -applied to a list of cluster detections based on LSST -or external data. +\item An algorithm that produces accurately deblended photometry of +cluster cores at least to redshift $z = 1$ with LSST data and to higher +redshifts in combination with near-IR data. +\item Cluster-specific galaxy spectral templates for use by photometric +redshift codes, emphasizing samples drawn from spectroscopic surveys of +high redshift clusters. +\item A new cluster-specific photometric redshift algorithm that can be +applied to a list of cluster detections based on LSST data, external +data, or combined LSST/external datasets. \end{enumerate} } \end{task} -\subsection{Forward Modeling of LSST Clusters and Groups} -\tasktitle{Forward Modeling of LSST Clusters and Groups} +\subsection{ Enabling Cluster Physics Through Forward Modeling of LSST +Clusters and Groups} +\tasktitle{Enabling Cluster Physics Through Forward Modeling of LSST +Clusters and Groups} \begin{task} \label{task:clss:cluster_fm} \motivation{ Most of the interesting cluster and group physics from LSST and its union with complementary surveys will be derived from studies that explore the full range of halo mass relevant to groups and clusters -$M_{200}\simeq10^{13}-10^{15}M_\odot$. This mass range extends -beyond that used by cluster cosmologists (e.g. colleagues in DESC), +$M_{200}\simeq10^{13}-10^{15}M_\odot$ and to redshifts $z\gtrsim1$. +This mass and redshift range extends +beyond that used by cluster cosmologists (e.g., colleagues in DESC), who typically restrict attention to objects with masses -$M_{200}>10^{14}M_\odot$. -However, the -requirement on controlling systematic biases for cluster/group physics -is roughly an order of -magnitude less stringent than for dark energy science. Arguably, $\sim10\%$ -control of systematic biases in weak-lensing measurements of low -redshift clusters ($\gtrsim2\times10^{14}M_\odot$) has already been -achieved \citep{okabe2013a,applegate2014a,hoekstra2015a,okabe2016a}. -This science task focuses on the challenge of maintaining that level of -control down to smaller masses and out to higher redshifts. +$M_{200}>10^{14}M_\odot$ at $z<1$. +Extending the range probed will be very challenging from the point of +view of systematic biases. However, the requirement on controlling +systematic biases for cluster/group physics is an order of magnitude +less stringent than the nominal 1\% requirement for dark energy science. +Arguably, $\sim10\%$ control of systematic biases in weak-lensing +measurements of low redshift clusters ($\gtrsim2\times10^{14}M_\odot$) +has already been achieved +\citep{okabe2013a,applegate2014a,hoekstra2015a,okabe2016a}, giving +considerable grounds for optimism. } ~\\ \activities{ -A growing number of studies are adopting an approach of forward -modeling the cluster population simultaneously with the cosmological -model to obtain constraints on scaling relations and cosmological -parameters. Here, the idea is to borrow this same approach, but adopt -a fixed cosmological model, broaden the mass range of systems -considered, and expand the forward modeling to include additional -relationships of interest. For example, one could simultaneously fit -density profile models to the shear profiles, the mass-concentration -relation, and the star-formation rates of clusters and groups. -Overall, this effort will provide a robust Bayesian inference code with which -to constrain the physics of galaxies and hot gas in groups and -clusters, tied directly to the halo mass function via weak-lensing. -Related activities include the selection of elements of the cluster population to include in the model, -and the development and testing of the code on simulated data. -Once developed, the code can be improved by extending the range of physics -explored by adding more physical relations, and by testing the code on existing -datasets from pointed surveys (e.g. LoCuSS, others) and wide area surveys (e.g. LoCuSS, DES, others). +Broadly, cluster-based constraints on dark energy will be +based on forward modeling the cluster population from a cosmological +model and a number of scaling relations between halo mass and observable +properties. The design of these algorithms and their selected +scaling relations will be predicated on deriving +the most reliable dark energy constraints, and not necessarily for +learning the +most cluster physics possible. For example, the +scaling relations will +be selected to have low scatter, and the internal +structure and halo concentration of clusters may be treated as nuisance +parameters despite their physical interest. +~\\~\\ +The main activity in this task will therefore be to develop a code to +forward model the combined LSST/multiwavelength dataset on a cluster +population at a level of detail that preserves the structure of +clusters and thus maximizes the available information about internal +cluster physics. +The model should connect cluster properties back to the halo mass function via the +weak-lensing constraints that will be available from the LSST data, assuming +a fixed cosmological model. +Requirements missing from cosmological modeling codes include (1) simultaneous fitting +of cluster scaling relations, density profile models to weak-shear +profiles, and the mass-concentration relation of groups and clusters, +and (2) simultaneous fitting of the weak-shear signal from clusters with +overtly astrophysical parameters of interest such as the star-formation +rate of clusters, and indicators of the merger history of clusters like +X-ray morphology. A public, multipurpose code would enable the +exploration of a broad range cluster science +interests with LSST and supporting data. Other important activities +will include testing the code on simulated light cone data, existing +datasets (e.g. XCS, SPT, XXL, LoCuSS, HSC, DES, and others), and LSST +commissioning data. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item A Bayesian inference code to simultaneously model cluster shear -profiles and scaling relations across the full range of halo mass of groups and clusters, -to $\sim10\%$ control on systematics. +\item A robust Bayesian forward modeling code to constrain +the physics of galaxies and hot gas in groups and clusters, tied +directly to the halo mass function via weak-lensing from LSST. +\item Detailed tests on simulated and existing datasets. +\item Early science from LSST commissioning data, dependending on the choice of +commissioning fields. \end{enumerate} } \end{task} - - - \end{tasklist} } From 05205e999c31d42c712099e19c272fb03cfcbe14 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 2 Aug 2017 13:18:27 -0700 Subject: [PATCH 55/64] Fixed Lacerna's affiliation. --- authorlist.tex | 53 +++++++++++++++++++++++++------------------------ main.pdf | Bin 307734 -> 307868 bytes 2 files changed, 27 insertions(+), 26 deletions(-) diff --git a/authorlist.tex b/authorlist.tex index 975993c..e321d86 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -32,24 +32,24 @@ Holwerda, Benne W.$^{25}$, Jarvis, Matt J.$^{4,26}$, Kasliwal, Vishal$^{27,28,29}$, -Lacerna, Ivan$^{14}$, -Loveday, Jon$^{30}$, -Marshall, Phil$^{31}$, +Lacerna, Ivan$^{30,14}$, +Loveday, Jon$^{31}$, +Marshall, Phil$^{32}$, Merlin, Emiliano$^{24}$, -Napolitano, Nicola R.$^{32}$, +Napolitano, Nicola R.$^{33}$, Puzia, Thomas H.$^{14}$, Robotham, Aaron$^{5}$, -Salim, Samir$^{33}$, -Sereno, Mauro$^{34}$, +Salim, Samir$^{34}$, +Sereno, Mauro$^{35}$, Snyder, Gregory F.$^{7}$, -Stott, John P.$^{35}$, -Tissera, Patricia B.$^{36}$, -Werner, Norbert$^{37,38,39}$, -Yoachim, Peter$^{40}$, -Borne, Kirk D.$^{41}$, +Stott, John P.$^{36}$, +Tissera, Patricia B.$^{37}$, +Werner, Norbert$^{38,39,40}$, +Yoachim, Peter$^{41}$, +Borne, Kirk D.$^{42}$, and Members of the LSST Galaxies Science Collaboration -\vspace*{4mm} +%\vspace*{2mm} {\justify\it\small $^{1}$Department of Astronomy and Astrophysics, University of California, Santa Cruz, Santa Cruz, CA 96054, USA, @@ -75,25 +75,26 @@ $^{20}$H.H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol, BS8 1TL, UK, $^{21}$School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK, $^{22}$Cardiff University, School of Physics and Astronomy, The Parade, Cardiff, CF22 3AA, UK, -$^{23}$Departamento de Astronomía, Universidad de Concepci{\'{o}}n,Casilla 160-C, Concepción, Chile, +$^{23}$Departamento de Astronom\'\i a, Universidad de Concepci{\'{o}}n,Casilla 160-C, Concepci{\'{o}}n, Chile, $^{24}$INAF - Osservatorio Astronomico di Roma, Via Frascati, 33, I-00078, Monte Porzio Catone (Roma), Italy, $^{25}$Department of Physics and Astronomy, 102 Natural Science Building, University of Louisville, Louisville KY 40292, USA, $^{26}$Department of Physics, University of the Western Cape, Bellville 7535, South Africa, $^{27}$Colfax International, 750 Palomar Avenue, Sunnyvale, CA 94085, USA, $^{28}$University of Pennsylvania, Department of Physics \& Astronomy, 209 S 33rd St, Philadelphia, PA 19104, USA, -$^{29}$Princeton University, Department of Astrophysical Sciences; 4 Ivy Ln, Princeton, NJ 08544, USA, -$^{30}$Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QH, UK, -$^{31}$Kavli Institute for Particle Astrophysics and Cosmology, P.O. Box 20450, MS29, Stanford, CA 94309, USA, -$^{32}$INAF -Osservatorio Astronomico di Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy, -$^{33}$Indiana University, Department of Astronomy, Bloomington, IN 47405, USA, -$^{34}$INAF - Osservatorio Astronomico di Bologna; Dipartimento di Fisica e Astronomia, Universit\`a di Bologna Alma-Mater, via Piero Gobetti 93/3, I-40129 Bologna, Italy, -$^{35}$Department of Physics, Lancaster University, Lancaster LA1 4YB, UK, -$^{36}$Astrophysics Group, Department of Physics - Campus La Casona, Universidad Andres Bello, Fernandez Concha 700, Las Condes, Santiago, Chile, -$^{37}$1 MTA-Eotvos University Hot Universe Research Group, Pazmany Peter Setany 1/A, Budapest, 1117, Hungary, -$^{38}$Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, Brno, 611 37, Czech Republic, -$^{39}$School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan, -$^{40}$University of Washington, Box 351580, U.W. Seattle, WA 98195-1580, USA, -$^{41}$Booz Allen Hamilton, 308 Sentinel Drive, Suite 100, Annapolis Junction, MD 20701, USA +$^{29}$Princeton University, Department of Astrophysical Sciences, 4 Ivy Lane, Princeton, NJ 08544, USA, +$^{30}$Instituto Milenio de Astrof\'\i sica, Av. Vicu{\~{n}}a Mackenna 4860, Macul, Santiago, Chile, +$^{31}$Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QH, UK, +$^{32}$Kavli Institute for Particle Astrophysics and Cosmology, P.O. Box 20450, MS29, Stanford, CA 94309, USA, +$^{33}$INAF -Osservatorio Astronomico di Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy, +$^{34}$Indiana University, Department of Astronomy, Bloomington, IN 47405, USA, +$^{35}$INAF - Osservatorio Astronomico di Bologna; Dipartimento di Fisica e Astronomia, Universit\`a di Bologna Alma-Mater, via Piero Gobetti 93/3, I-40129 Bologna, Italy, +$^{36}$Department of Physics, Lancaster University, Lancaster LA1 4YB, UK, +$^{37}$Astrophysics Group, Department of Physics - Campus La Casona, Universidad Andres Bello, Fernandez Concha 700, Las Condes, Santiago, Chile, +$^{38}$1 MTA-Eotvos University Hot Universe Research Group, Pazmany Peter Setany 1/A, Budapest, 1117, Hungary, +$^{39}$Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, Brno, 611 37, Czech Republic, +$^{40}$School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan, +$^{41}$University of Washington, Box 351580, U.W. 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zNJ>5Xc6`5er$*&vWbyjc)BAtMthY4$-q}!T_zABV_Qt*JTuIBAwKil@zpjKd-`=Yr zN6O@u-TpDO4=8 b+gOFB&5zmB^)$kaaAg%n2?--hW5)jhSq3e< diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index ad6fac5..c057775 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -60,7 +60,7 @@ \subsection{AGN Host Galaxy Properties from LSST Data} \motivation{ Morphological characterizations from parameterized models, such as multiple-component \cite{sersic1968a} profiles, or non-parametric measures like CAS and Gini-M20 -\citep{abraham1994a,conselice2000a,lotz2004a} can help identify mergining galaxies in the LSST data. +\citep{abraham1994a,conselice2000a,lotz2004a} can help identify merging galaxies in the LSST data. The ability of these techniques to characterize efficiently and accurately the morphology of AGN host galaxies identified via their variability remains unproven. } @@ -137,7 +137,7 @@ \subsection{AGN Variability Selection in LSST Data} Most AGN exhibit broad-band aperiodic, stochastic variability across the entire electromagnetic spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, providing a powerful probe of accretion physics. The main LSST Wide Fast Deep (WFD) survey will obtain $\sim10^8$ AGN light curves (i.e., flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. -The Deep Drilling Fields will provide AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will crucially depend on the interval between observations in individual filter bands. These concerns motivate a determinination of guidelines for an optimal survey strategy (from an AGN variability perspective) and a discovery +The Deep Drilling Fields will provide AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will crucially depend on the interval between observations in individual filter bands. These concerns motivate a determination of guidelines for an optimal survey strategy (from an AGN variability perspective) and a discovery of possible biases and uncertainties introduced into AGN variability science as a result of the chosen survey strategy.} ~\\ \activities{ diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex index 6d94344..e714350 100644 --- a/task_lists/aux/aux.tex +++ b/task_lists/aux/aux.tex @@ -10,7 +10,7 @@ \subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} \begin{task} \label{task:aux:spectroscopy} \motivation{ -Although great strides have been made in projects using photometric redshifts alone, some science is only possible with either spectroscopic redshifts and/or spectroscopic line measurements. In particular, spectroscopic redshifts are essential when distance accuracies of less than 1000 km/s are required; for example in identifying galaxy pairs and groups. Robust measurement of gas and stellar phase metalicities also require spectra with relatively high signal-to-noise and resolution. +Although great strides have been made in projects using photometric redshifts alone, some science is only possible with either spectroscopic redshifts and/or spectroscopic line measurements. In particular, spectroscopic redshifts are essential when distance accuracies of less than 1000 km/s are required; for example in identifying galaxy pairs and groups. Robust measurement of gas and stellar phase metallicities also require spectra with relatively high signal-to-noise and resolution. Finally, photometric redshifts still require spectroscopic redshifts for both calibration and accuracy assessment. As such, it is essential that we ensure the LSST community has access to the available high precision redshifts, spectroscopically-derived properties and calibrated spectra for all available galaxies and quasars within the LSST footprint. This necessarily entails bringing together data from disparate surveys (such as 2dFGRS, SDSS, 6dF, MGC, GAMA, VIPERS, VVDS), the homogenization of data products and quality control, as well as the ongoing ingestion of upcoming spectroscopic campaigns such as TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. This will require significant pre-LSST effort. } ~\\ @@ -62,7 +62,7 @@ \subsection{Panchromatic Imaging within the LSST Footprint} ~\\~\\ As galaxies emit radiation across the entire electromagnetic spectrum it is important to be able to trace this breadth of emission deriving from different astrophysical processes. This is particularly important in the LSST optical wavebands where anywhere from 0-90 per cent of the radiation might be attenuated by dust and re-radiated in the far-IR. The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman- and 4000\AA~breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. -Finally, X-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star-formation. Unification across the wavelength range requires federation of these very disparate datasets, and may be worth centralizing prior to LSST operations. +Finally, X-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star formation. Unification across the wavelength range requires federation of these very disparate datasets, and may be worth centralizing prior to LSST operations. Note a similar task has recently been achieved by the Galaxy And Mass Assembly team for a 200 square degree region \citep[see][and http://www/gama-survey.org/]{driver2016a} and can be extended to the full LSST footprint using similar techniques. } ~\\ @@ -109,10 +109,10 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} ~\\ For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), an accurate photometry measurement, and a disk inclination. The last two critical measurements will be provided by LSST imaging. -There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST Deep Drilling Fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments.\\ +There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST Deep Drilling Fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detection and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments.\\ ~\\ Two other surveys represent the progressively wider/shallower H\,{\sc{i}} survey tiers with the ASKAP telescope \citep{johnston2007a}: DINGO, a survey of the GAMA fields \citep[][Meyer+ {\em in prep}]{driver2009a,duffy2012a,meyer2015a} and WALLABY, the Southern Sky H\,{\sc{i}} survey \citep[][Koribalski+ {\em in prep}]{duffy2012a}. - A benefit of the MeerKAT and ASKAP radio surveys is that they are conducted commensally: radio continuum and 21 cm emission line (H\,{\sc{i}}) are observed at the same time. + A benefit of the MeerKAT and ASKAP radio surveys is that radio continuum and 21cm line (H\,{\sc{i}}) emission are observed at the same time. The survey strategy from wide and shallow to single deep field (WALLABY-DINGO-MIGHTEE-LADUMA) is designed to beat down cosmic variance effectively \citep[see e.g.,][]{maddox2016a}. } ~\\ diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 332325a..4ae031d 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -79,7 +79,7 @@ \subsection{Identifying and Characterizing Clusters} and high- redshift within the LSST footprint. Specifically, this work should characterize the selection function, completeness, and contamination rate for different cluster identification algorithms. Such -characerizations require realistic light-cone simulations spanning +characterizations require realistic light-cone simulations spanning extremely large volumes, so as to capture significant numbers ($\gg10,000$) of simulated galaxy clusters at high-redshift. Potential algorithms to be tested include adaptations of RedMaPPer @@ -101,7 +101,7 @@ \subsection{Identifying and Characterizing Clusters} \item New and improved cluster identification algorithms that can be applied to LSST commissioning and survey data, and combined LSST/NIR/X-ray data. -\item Compilation of auxillary data that will aide testing of algorithms +\item Compilation of auxiliary data that will aide testing of algorithms to identify and characterize clusters, such as near-infrared (e.g. VISTA, UKIDSS), X-ray (e.g.~XMM-Newton, eROSITA, etc.), SZ (Planck, SPT, ACT), and radio (SKA and its pathfinders, SUMSS) within the LSST @@ -239,7 +239,7 @@ \subsection{Enabling Cluster Science through Robust Photometry and Photometric R non-uniform background principally caused by the diffuse intracluster light, and the presence of numerous background galaxies including some that are highly distorted gravitational arcs. Given that the LSST -data will be accummulated over numerous epochs, there is significant +data will be accumulated over numerous epochs, there is significant potential for the detection of transients along these lines-of-sight. All of these complicating issues will be relevant to LSST commissioning data, Wide Fast Deep survey data, and the Deep Drilling Fields, and all will @@ -250,7 +250,7 @@ \subsection{Enabling Cluster Science through Robust Photometry and Photometric R faint cluster members and prior information about the presence of a galaxy cluster along the line-of-sight. Science goals affected by these issues include weak-lensing measurements of the -mass-concentraion relation as a function of halo mass and redshift, +mass-concentration relation as a function of halo mass and redshift, measuring the evolution of the galaxy luminosity function in clusters and in particular the faint end slope, identifying star-forming galaxies in clusters and their infall regions to probe the physics of quenching @@ -293,7 +293,7 @@ \subsection{Enabling Cluster Science through Robust Photometry and Photometric R This work links with efforts on deblending and intracluster light, forward modeling of cluster and groups, environmental measures, cluster -detection, auxilliary data, and work in the DESC Clusters Working Group +detection, auxiliary data, and work in the DESC Clusters Working Group via the determination of $p(z)$ for background galaxies.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: @@ -383,7 +383,7 @@ \subsection{ Enabling Cluster Physics Through Forward Modeling of LSST the physics of galaxies and hot gas in groups and clusters, tied directly to the halo mass function via weak-lensing from LSST. \item Detailed tests on simulated and existing datasets. -\item Early science from LSST commissioning data, dependending on the choice of +\item Early science from LSST commissioning data, depending on the choice of commissioning fields. \end{enumerate} } diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index fd6956c..3dfbd38 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -218,7 +218,7 @@ \subsection{Optimizing Galaxy Morphology Measurements} the Level 2 products should supply enough information to select reasonable subsets of galaxies.\\ ~\\ More importantly, while the traditional parameterizations of morphology described above will be useful, it is essential that new, more powerful methods of measuring galaxy morphology are developed and implemented, in order to leverage the exquisite volume and depth of LSST data. In this regard fast, -machine-learning techniques \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that can efficiently separate LSST galaxy populations into different morphological classes are particularly relevant and powerful. +machine-learning techniques \citep[e.g.,][Hausen \& Robertson, in prep]{hocking2015a} that can efficiently separate LSST galaxy populations into different morphological classes are particularly relevant and powerful. } ~\\ \activities{The preparation work will focus on defining morphological parameters and developing machine-learning algorithms to enable users to easily query galaxy morphologies from the LSST database. @@ -350,7 +350,7 @@ \subsection{Optimizing Galaxy Photometry} their brightness and clustering. These factors all affect photometry in systematic ways, potentially creating spurious correlations that can obscure or masquerade as astrophysical effects. For example, efforts to measure the effect of neighbors -on galaxy star-formation rates can be erroneous if the presence of a neighbor +on galaxy star formation rates can be erroneous if the presence of a neighbor affects the basic photometry. Measurements of galaxy magnification or measurements of intergalactic dust can be similarly affected by systematic photometric biases. It is thus important to hone the photometry techniques prior to the survey to @@ -418,7 +418,7 @@ \subsection{Optimizing Measurements of Stellar Population Parameters} \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item Development and refinement of techniques for constraining star-formation histories of large ensembles of galaxies. +\item Development and refinement of techniques for constraining star formation histories of large ensembles of galaxies. \item Model inputs to guide in developing these techniques. \item Refinement of the science requirements for ancillary multi-wavelength data to support LSST. \end{enumerate} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index d5e85f4..56d0417 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -20,7 +20,7 @@ \subsection{Low Surface Brightness Tidal Features} \begin{enumerate} \item Simulating realistic LSST images and LSB features (using e.g. new high-resolution hydrodynamical simulations in cosmological volumes, such as Horizon-AGN, EAGLE, Illustris and others). \item Identifying precursor datasets (e.g. the Hyper Suprime-Cam Survey or the Dark Energy Camera Legacy Survey (DECaLS)) that can be used as testbeds for developing LSB tools for use on LSST data. -\item Using such simulations to develop algorithms for auto-detection, measurement and characterisation of LSB features (e.g. using the properties of LSB tidal features to back-engineer the properties of the mergers which created them). +\item Using such simulations to develop algorithms for auto-detection, measurement and characterization of LSB features (e.g. using the properties of LSB tidal features to back-engineer the properties of the mergers which created them). \item Applying these algorithms to the precursor datasets to test their suitability. \item Ensuring that LSST Level 2 processing and observing strategies are aligned with the needs of LSB tidal-feature science. \end{enumerate} @@ -85,7 +85,7 @@ \subsection{Faint Outskirts of Galaxies} } ~\\ \activities{ -Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modelling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyse the outskirts. Dithering and rotation of individual imaging will need to be modelled before stacking multiple imaging. +Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modeling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyze the outskirts. Dithering and rotation of individual imaging will need to be modeled before stacking multiple imaging. \\ Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). } diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index 03ffcf3..abdedd5 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -68,7 +68,7 @@ \subsection{Multivariate Physical Properties of Galaxies from Photometric Redshi Measurements of key derived physical properties are critical for much work on galaxies and their evolution. The properties measurable from SEDs include star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity.\\ ~\\ Many recent science analyses have relied upon derived physical properties rather than fluxes and luminosities in the UV, optical and near-IR bands. This is largely a matter of convenience: utilizing tables of derived properties require no redshift (K) corrections or extra dust corrected, as those are effectively applied in the measurement process; they are also closer to the quantities best determined in simulations. However, derived quantities have the disadvantage of the potential for significant systematic errors in measurement, as well as non-uniformity in their definition (e.g., differences in adopted IMF can change stellar masses by $\sim 0.5$ dex). \\~\\ -Stellar mass has emerged as a parameter of choice for selecting galaxy samples and attempting to make apples-to-apples comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a measure of a galaxy’s star formation history. Dust attenuation and stellar metallicity can help to probe processes important for understanding galaxy evolution.\\ +Stellar mass has emerged as a parameter of choice for selecting galaxy samples and attempting to make apples-to-apples comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a measure of a galaxy's star formation history. Dust attenuation and stellar metallicity can help to probe processes important for understanding galaxy evolution.\\ ~\\ This task shares some goals with the Dark Energy Science Collaboration Photometric Redshifts working group, as laid out in their Science Roadmap \citep{LSSTDESC}, who are also interested in multidimensional probability density functions joint in redshift and stellar mass, star formation rate, and dust content of the galaxies. Coordination on this area with the DESC Photo-z working group will benefit both groups. @@ -124,7 +124,7 @@ \subsection{Simulations with Realistic Galaxy Colors and Physical Properties} The main activity for this task is to develop improved simulation metrics based upon observational studies of both low- and high-redshift galaxies. This will require expertise from the photo-$z$, high-redshift galaxies, AGN, and simulations working groups. In order to test whether mock galaxy populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions.\\ ~\\ If we then assume that the simulations are valid beyond the test intervals, we can use them as a testbed to develop improved algorithms for a wide variety of applications, e.~g.~selecting specific sub-populations of galaxies. -One key aspect of this work is that spectral energy distributions in simulations cannot be generated from discrete templates, but instead must span a continuous range of properties. If only a finite set of restframe SEDs are used in the simulation, the photo-$z$ problem would be unnaturally simplified and falsely strong photometric redshift predictions would result. Thus a method is required that simultaneously reproduces galaxy colors without resorting to a restricted set of SEDs. For example, this could be done by creating complete SEDs based on an extended set of principal components (e.g., extending the $kcorrect$ or EAZY basis set), though in general additional constraints are required with PCA-like techniques to ensure that unphysical spectra are not generated.\\ +One key aspect of this work is that spectral energy distributions in simulations cannot be generated from discrete templates, but instead must span a continuous range of properties. If only a finite set of rest-frame SEDs are used in the simulation, the photo-$z$ problem would be unnaturally simplified and falsely strong photometric redshift predictions would result. Thus a method is required that simultaneously reproduces galaxy colors without resorting to a restricted set of SEDs. For example, this could be done by creating complete SEDs based on an extended set of principal components (e.g., extending the $kcorrect$ or EAZY basis set), though in general additional constraints are required with PCA-like techniques to ensure that unphysical spectra are not generated.\\ ~\\ With sufficiently realistic simulations that reproduce the ensemble of galaxy star formation histories and the mapping between those histories and spectral energy distributions, we can use simulated catalogs to test techniques for identifying specific galaxy sub-populations. For some studies, we may wish to examine the relationship between galaxies in specific sub-populations and their large-scale structure environment. Thus, realistic density and clustering properties are also important in the simulation. There are a wide variety of techniques that may be used for environmental measures, operating on a variety of scales. As small-scale measurements can be noisy and/or washed out by photometric redshift errors, it may be more effective to measure the average overdensity/environment as a function of galaxy properties, rather than the reverse. } @@ -150,7 +150,7 @@ \subsection{Incorporating Galaxy Size and Surface Brightness into Photometric Re \label{task:photo_z:size_and_sb_priors} \motivation{ Photometric redshift algorithms most commonly have used galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information on a galaxy’s size, shape, overall surface brightness (SB), or detailed surface brightness (SB) profile can provide additional information that can aid in constraining the redshift and/or type of a galaxy, breaking potential degeneracies that using colors alone would miss. Gains can be particularly substantial at low redshift where LSST will at least partially resolve galaxies. Incorporating morphological information may help to improve joint predictions for galaxy properties and redshift as well, at the cost of imposing assumptions about links between morphology and color/SED that may not apply to all galaxies. -If sufficient training samples are available, priors for redshift and SED parameters given morphological parameters, $p(z, SED | P)$, can be constructed that can be incorporated into Bayesian analyses of photometric redshifts and potentially lead to improved constraints on the redshift PDF (i.e., $p(z | P, C )$ , where $P$ represents observed morphological parameters, $C$ represents observed flux/color measurements, and $SED$ represents one or more parameters representing the restframe SED of a galaxy). +If sufficient training samples are available, priors for redshift and SED parameters given morphological parameters, $p(z, SED | P)$, can be constructed that can be incorporated into Bayesian analyses of photometric redshifts and potentially lead to improved constraints on the redshift PDF (i.e., $p(z | P, C )$ , where $P$ represents observed morphological parameters, $C$ represents observed flux/color measurements, and $SED$ represents one or more parameters representing the rest-frame SED of a galaxy). } ~\\ \activities{ diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index 2b42299..0b3e428 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -57,7 +57,7 @@ \subsection{New Theoretical Models for the Galaxy Distribution} play a well-established role in modern galaxy surveys. For the first time, systematic uncertainties will limit the scientific potential of the new surveys, rather than sampling errors driven by the volume mapped. -A variety of viable, competing cosmological models already provide only subtly discernable +A variety of viable, competing cosmological models already provide only subtly discernible signals in survey data. Distinguishing between the models requires the best possible theoretical predictions to understand the measurements and their subsequent analysis, and to understand the uncertainties on the measurements. @@ -100,7 +100,7 @@ \subsection{Design of New Empirical Models for the Galaxy Distribution} Developing models of the galaxy-halo connection for LSST require two main stages. The first step tests current empirical models to judge the fidelity with which they reproduce the predictions of physical models based on simulations. The second step -uses physical models to devise new parameterizations for empirical models to +uses physical models to devise new parametrizations for empirical models to describe galaxy populations for which little or no data yet exists, providing enhanced empirical models relevant for upcoming surveys that will probe regimes that remain largely unmapped.} From 92fe2837792a433af59b639483c9a0d70c548079 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 2 Aug 2017 20:29:48 -0700 Subject: [PATCH 58/64] Fixed Newman's affiliation. --- authorlist.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/authorlist.tex b/authorlist.tex index e321d86..cbb29c4 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -63,7 +63,7 @@ $^{9}$Centre for Astrophysics Research, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, UK, $^{10}$Instituto de Astrof\'\i sica de Canarias, E-38200 La Laguna, Spain, $^{11}$Departamento de Astrof\'\i sica, Universidad de La Laguna, E-38206 La Laguna, Spain, -$^{12}$University of Pittsburgh and PITT PACC, 3941 O{'}Hara St., Pittsburgh, PA 15260, USA, +$^{12}$Department of Physics and Astronomy and PITT PACC, University of Pittsburgh, 3941 O{'}Hara St., Pittsburgh, PA 15260, USA, $^{13}$NOAO, 950 N. Cherry Ave, Tucson, AZ 85719, USA, $^{14}$ Instituto de Astrof\'\i sica, Pontificia Universidad, Cat{\'{o}}lica Chile, Vicu{\~{n}}a Mackenna 4860, Santiago, Chile, From b28239fb93f5eb9605bd9c9b86f978009a968bdf Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 3 Aug 2017 09:09:51 -0700 Subject: [PATCH 59/64] Small language edits to improve layout. 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z6shX@SIjfr%2D7TL1R2B)`XF&Ryuf9%&9w;VyHiKU(u!UxM-t;v?_xqLkYs!f?4_r zm|8aLmP{=TEZ>uy%Jt%+Glp~hlbHH#&mL3|Km&dQm!usq=^VY_I4=Gl<~;P{d?nWLzd3>5rmC|8k`z1jmh7g4I{T2;rEx zy>f^rFL>6^G0olaJVOTx2_fiRg&?9}hH<(S{|ij@kL6IZsbB$qxZgs19UaDSA3rsE zc`rvMTFM3n_2>5+`d$)*Wx;27fnVb`$TD$f(lvR0ZPB>Wn4uf?i8K&78%d)8I`h3= z^#(NOkQFOZxVkY0*V>6m_qCXpu5CL80~$r}J6T)Hw6n57WaRGSA9B!~Ut$OsRI2OX zGdVQ)q5Tgg(2URlrGjev_-NMV= za|e@Rz0p#VAYQGP*D*$(kY2)+lrZs?l_UgM-=txt|J%$t2tb^H9x6+`xkc`^VDtvG zhYLt%Zl@pvSf0V{#L9~oj-Q^_9aN0J>hafvtrX-Ju@Hn46qL&I>LJ@E zQ`36>vQ52UnEV4zfO$w}ZzCblTox9OqYvWg7O?ESmaD1{TF37ls+)07VF_1W@#HWx z2;)j)$5_>PC0;qhcy~BPAtH?f Date: Thu, 3 Aug 2017 09:15:20 -0700 Subject: [PATCH 60/64] Version date for arXiv posting updated. Closes issue #24 --- VersionDate.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VersionDate.tex b/VersionDate.tex index d64b751..a83678d 100644 --- a/VersionDate.tex +++ b/VersionDate.tex @@ -1,4 +1,4 @@ \begin{center} Version 1.0: -June 22, 2017 +August 4, 2017 \end{center} From 55941eb45bb0e08f26efa218362964be3fc820a0 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 3 Aug 2017 21:56:09 -0700 Subject: [PATCH 61/64] Fixing references Closes issue #29 --- references.bib | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/references.bib b/references.bib index 6380ae1..1b58a7b 100644 --- a/references.bib +++ b/references.bib @@ -1187,7 +1187,7 @@ @article{meyer2015a Date-Added = {2017-04-25 15:30:42 +0000}, Date-Modified = {2017-04-25 15:30:42 +0000}, Eprint = {1501.01082v1}, - Jornal = {ArXiv e-prints}, + Journal = {arXiv:1501.01082}, Month = {Jan}, Primaryclass = {astro-ph.GA}, Title = {Connecting the Baryons: Multiwavelength Data for SKA HI Surveys}, @@ -1493,9 +1493,10 @@ @ARTICLE{salim2016a @BOOK{sersic1968a, author = {{Sersic}, J.~L.}, - title = "{Atlas de galaxias australes}", + title = "{Atlas de galaxias australes.}", keywords = {GALAXIES, GROUPS OF GALAXIES, ATLASES}, booktitle = {Cordoba, Argentina: Observatorio Astronomico, 1968}, +publisher = {Cordoba, Argentina: Observatorio Astronomico}, year = 1968, adsurl = {http://adsabs.harvard.edu/abs/1968adga.book.....S}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} From 1ab13e87e070767d83798fe03458a55d27540c43 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 3 Aug 2017 23:06:31 -0700 Subject: [PATCH 62/64] Last minor revisions throughout. --- introduction/introduction.tex | 4 ++-- references.bib | 2 +- science_background/science_background.tex | 10 +++++----- task_lists/agn/agn.tex | 5 +++-- task_lists/aux/aux.tex | 16 ++++++++-------- task_lists/galaxies/galaxies.tex | 5 ++--- task_lists/lsb/lsb.tex | 2 +- task_lists/tmc/tmc.tex | 2 +- 8 files changed, 23 insertions(+), 23 deletions(-) diff --git a/introduction/introduction.tex b/introduction/introduction.tex index cf79356..d5ee9ec 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -11,7 +11,7 @@ bands every few nights. The observatory will operate for at least a decade, allowing stacked images to detect galaxies to redshifts well beyond unity. LSST and -its Deep-Wide-Fast and Deep Drilling Field surveys will meet +its Wide Fast Deep and Deep Drilling Fields surveys will meet the requirements of a broad range of science goals in astronomy, astrophysics and cosmology \citep{ivezic2008a}. The LSST ranked first among large ground-based initiatives in the @@ -45,7 +45,7 @@ connects individual research projects together into a broader enterprise to enable dark energy science with LSST. -Following the lead of DESC, several other LSST community organizations +Following the lead of DESC several other LSST community organizations, including the AGN, Milky Way and Local Volume, and Solar System Science Collaborations, started to develop Roadmaps to outline critical preparatory tasks in diff --git a/references.bib b/references.bib index 1b58a7b..3d3c9c4 100644 --- a/references.bib +++ b/references.bib @@ -27,7 +27,7 @@ @ARTICLE{LSSTDESC adsnote = {Provided by the SAO/NASA Astrophysics Data System} } @BOOK{nrc2010a, - author = "National Research Council", + author = "{National Research Council}", title = "New Worlds, New Horizons in Astronomy and Astrophysics", isbn = "978-0-309-15799-5", doi = "10.17226/12951", diff --git a/science_background/science_background.tex b/science_background/science_background.tex index dbe131f..b8b9403 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -166,7 +166,7 @@ \section{Star Formation and Stellar Populations in Galaxies} origin of the relation remains an active line of inquiry \citep[e.g.][]{lofthouse2017a}, guided by recently improved data from Hubble Space Telescope over the -$\sim0.2$ deg$^{-2}$ Cosmic Assembly Near-Infrared +$\sim0.2$ deg$^{2}$ Cosmic Assembly Near-Infrared Deep Extragalactic Survey \citep{grogin2011a,koekemoer2011a}. While LSST will be comparably limited in redshift @@ -364,7 +364,7 @@ \section{Probing the Extremes of Galaxy Formation} galaxies tracks the accretion history of the most massive supermassive black holes. If stellar mass builds proportionally to black hole mass in quasars, -then very rare luminous star forming galaxies at +then very rare luminous star-forming galaxies at early times may immediately proceed the formation of bright quasars. LSST has all the requisite survey properties (area, multiband imaging, and @@ -375,8 +375,8 @@ \section{Probing the Extremes of Galaxy Formation} high-redshift galaxy luminosity function. Independent determinations of the distribution of galaxy luminosities at $z\sim6$ show substantial -variations at the bright end. The origin of -the discrepancies between various groups remains +variations. The origin of +the discrepancies between various determinations remains unclear, but the substantial cosmic variance expected for the limited volumes probed and the intrinsic rarity of the bright objects may conspire to @@ -457,7 +457,7 @@ \section{Science Book} \item Demographics of Galaxy Populations \begin{itemize} \item Passively evolving galaxies -\item High-redshift star forming galaxies +\item High-redshift star-forming galaxies \item Dwarf galaxies \item Mergers and interactions \end{itemize} diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index c057775..bf9912a 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -33,7 +33,7 @@ \subsection{AGN Selection from LSST Data} The use of LSST as a single way to identify AGN and characterize their diversity of AGN requires the development of selection criteria that can leverage the color, morphology, and variability information available from LSST imaging alone. -A number of AGN surveys with input from multiple wavelength observation and spectra already +A number of AGN surveys with input from multiple wavelength observations and spectra already exist, and precursor work must utilize these surveys to determine whether AGN that prove difficult to identify via optical color selection will reveal themselves through the additional parameters of morphology, variability, and/or the @@ -112,7 +112,8 @@ \subsection{AGN Feedback in Clusters} SDSS has enabled this multi-wavelength analysis for a few hundred clusters at $z<0.3$, but LSST cluster datasets will reach deeper to redshifts $z>1$. Such studies hold implications for cosmological studies by helping to distinguish between -X-ray gas properties strongly influenced by AGN or simply the +X-ray gas properties strongly influenced by AGN or that arise only in response +to the cluster gravitational potential. } ~\\ diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex index e714350..758b860 100644 --- a/task_lists/aux/aux.tex +++ b/task_lists/aux/aux.tex @@ -1,6 +1,6 @@ \section{Auxiliary Data}\label{sec:tasks:aux} {\justify -While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing, future, and proposed external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, x-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation for and during LSST operations it is therefore prudent to ensure appropriate access, usability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. +While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing, future, and proposed external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, X-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation for and during LSST operations it is therefore prudent to ensure appropriate access, usability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. @@ -46,9 +46,9 @@ \subsection{Panchromatic Imaging within the LSST Footprint} \begin{task} \label{task:aux:panchromatic} \motivation{ -LSST will only cover a small portion of the electromagnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available x-ray, UV, IR, and radio data. +LSST will only cover a small portion of the electromagnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available X-ray, UV, IR, and radio data. While archives of these data exist independently, there is a dire need to establish a Universe database which federates these data in a coherent manner. One of the major concerns of such a database is the accurate multi-wavelength source identification and de-convolution in disparate data with wildly differing resolutions. For example, two closely separated sources in the LSST data may appear as a single source in lower resolution data. As such, significant errors will be made when simply table matching these photometric catalogues. -The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFIT/TPHOT; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to x-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse x-ray halos, discrete x-ray sources and extended radio lobes). +The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFIT/TPHOT; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to X-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse X-ray halos, discrete X-ray sources and extended radio lobes). } ~\\ \activities{ @@ -61,7 +61,7 @@ \subsection{Panchromatic Imaging within the LSST Footprint} \end{enumerate} ~\\~\\ As galaxies emit radiation across the entire electromagnetic spectrum it is important to be able to trace this breadth of emission deriving from different astrophysical processes. This is particularly important in the LSST optical wavebands where anywhere from 0-90 per cent of the radiation might be attenuated by dust and re-radiated in the far-IR. -The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman- and 4000\AA~breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. +The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman and 4000\AA~breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. Finally, X-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star formation. Unification across the wavelength range requires federation of these very disparate datasets, and may be worth centralizing prior to LSST operations. Note a similar task has recently been achieved by the Galaxy And Mass Assembly team for a 200 square degree region \citep[see][and http://www/gama-survey.org/]{driver2016a} and can be extended to the full LSST footprint using similar techniques. } @@ -97,14 +97,14 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} ~\\~\\ A few major drawbacks for these studies into the evolution of the T-F are (a) the kinematic information comes from H$\alpha$ optical data (sometimes redshifted into the infra-red, -which does not trace the full rotation curve, -(b) adaptive optics for these observations filters out the lower surface brightness features such as the rotating +which does not trace the full rotation curve), +(b) adaptive optics for these observations filter out the lower surface brightness features such as the rotating disk \citep[see for a review ][]{glazebrook2013a}, and (c) these measurements are made for intrinsically bright samples of galaxies. However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}.\\ ~\\ -The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b}, -detailed kinematics \citep{trachternach2008a}, extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. +The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b} and +detailed kinematics \citep{trachternach2008a} extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}.\\ ~\\ For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 3dfbd38..e83f8b1 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -175,7 +175,7 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} input galaxies do not display realistic morphologies. At least some simulations with realistic morphologies are needed, especially for the Deep Drilling Fields. Inputs should come from hydrodynamical simulations, -{\it Hubble} images, and images from precursor surveys such as CFHTLS, DES and Hyper Suprime-Cam. +{\it Hubble} images, and images from precursor surveys such as CFHTLS, DES, and Hyper Suprime-Cam. The Science Collaborations should help provide and vet inputs. \\ ~\\ More challenging activities involve developing techniques and algorithms to improve the @@ -382,9 +382,8 @@ \subsection{Optimizing Galaxy Photometry} \begin{enumerate} \item Development of metrics for various science cases to help evaluate the Level 2 photometry. \item Realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies). +\item Deliverables over the longer term include developing optimal techniques for forced photometry using priors from space-based missions. \end{enumerate} -Deliverables over the longer term include developing optimal techniques for forced photometry -using priors from space-based missions. } \end{task} diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index 56d0417..55c48a0 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -19,7 +19,7 @@ \subsection{Low Surface Brightness Tidal Features} Several activities are of critical importance and need to be completed before LSST commissioning and the survey proper: \begin{enumerate} \item Simulating realistic LSST images and LSB features (using e.g. new high-resolution hydrodynamical simulations in cosmological volumes, such as Horizon-AGN, EAGLE, Illustris and others). -\item Identifying precursor datasets (e.g. the Hyper Suprime-Cam Survey or the Dark Energy Camera Legacy Survey (DECaLS)) that can be used as testbeds for developing LSB tools for use on LSST data. +\item Identifying precursor datasets (e.g. the Hyper Suprime-Cam Survey or the Dark Energy Camera Legacy Survey) that can be used as testbeds for developing LSB tools for use on LSST data. \item Using such simulations to develop algorithms for auto-detection, measurement and characterization of LSB features (e.g. using the properties of LSB tidal features to back-engineer the properties of the mergers which created them). \item Applying these algorithms to the precursor datasets to test their suitability. \item Ensuring that LSST Level 2 processing and observing strategies are aligned with the needs of LSB tidal-feature science. diff --git a/task_lists/tmc/tmc.tex b/task_lists/tmc/tmc.tex index 0b3e428..04029c2 100644 --- a/task_lists/tmc/tmc.tex +++ b/task_lists/tmc/tmc.tex @@ -127,7 +127,7 @@ \subsection{Estimating Uncertainties for Large-Scale Structure Statistics} ~\\ \activities{ Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, such as those based on perturbation theory. -Coordinate with Dark Energy Science Collaboration Working Groups, as these covariance matrices can also inform Cosmological parameter constraints.} +Coordinate with Dark Energy Science Collaboration Working Groups, as these covariance matrices can also inform cosmological parameter constraints.} ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ From e9f7f524d0eaf275314a73f1e39c316d62a7dca6 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Thu, 3 Aug 2017 23:18:41 -0700 Subject: [PATCH 63/64] Creating an arxiv version. For submission to the arxiv. --- arxiv/VersionDate.tex | 4 + arxiv/abstract.tex | 15 + arxiv/agn.tex | 219 +++++ arxiv/apj.bst | 1628 +++++++++++++++++++++++++++++++ arxiv/authorlist.tex | 105 ++ arxiv/aux.tex | 141 +++ arxiv/clss.tex | 392 ++++++++ arxiv/ddf.tex | 113 +++ arxiv/galaxies.tex | 428 +++++++++ arxiv/high_z.tex | 102 ++ arxiv/introduction.tex | 76 ++ arxiv/journal_macros.tex | 105 ++ arxiv/lsb.tex | 176 ++++ arxiv/main.tex | 83 ++ arxiv/photo_z.tex | 173 ++++ arxiv/references.bib | 1754 ++++++++++++++++++++++++++++++++++ arxiv/science_background.tex | 491 ++++++++++ arxiv/structure.tex | 63 ++ arxiv/task_lists.tex | 23 + arxiv/tmc.tex | 140 +++ task_lists/clss/clss.tex | 14 +- 21 files changed, 6238 insertions(+), 7 deletions(-) create mode 100644 arxiv/VersionDate.tex create mode 100644 arxiv/abstract.tex create mode 100644 arxiv/agn.tex create mode 100644 arxiv/apj.bst create mode 100644 arxiv/authorlist.tex create mode 100644 arxiv/aux.tex create mode 100644 arxiv/clss.tex create mode 100644 arxiv/ddf.tex create mode 100644 arxiv/galaxies.tex create mode 100644 arxiv/high_z.tex create mode 100644 arxiv/introduction.tex create mode 100644 arxiv/journal_macros.tex create mode 100644 arxiv/lsb.tex create mode 100644 arxiv/main.tex create mode 100644 arxiv/photo_z.tex create mode 100644 arxiv/references.bib create mode 100644 arxiv/science_background.tex create mode 100644 arxiv/structure.tex create mode 100644 arxiv/task_lists.tex create mode 100644 arxiv/tmc.tex diff --git a/arxiv/VersionDate.tex b/arxiv/VersionDate.tex new file mode 100644 index 0000000..a83678d --- /dev/null +++ b/arxiv/VersionDate.tex @@ -0,0 +1,4 @@ +\begin{center} +Version 1.0: +August 4, 2017 +\end{center} diff --git a/arxiv/abstract.tex b/arxiv/abstract.tex new file mode 100644 index 0000000..5708d14 --- /dev/null +++ b/arxiv/abstract.tex @@ -0,0 +1,15 @@ + + +\vspace*{30mm} +\begin{center} +{\bf Abstract} +\end{center} +\vspace*{5mm} + +{\justify +The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of +galaxies, dark matter, and black holes over cosmic time. The +LSST Galaxies Science Collaboration (LSST GSC) has identified a host of preparatory research tasks required +to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. +This {\it Galaxies Science Roadmap} provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The {\it Galaxies Science Roadmap} will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era. +} diff --git a/arxiv/agn.tex b/arxiv/agn.tex new file mode 100644 index 0000000..bf9912a --- /dev/null +++ b/arxiv/agn.tex @@ -0,0 +1,219 @@ +\section{Active Galactic Nuclei}\label{sec:tasks:agn:intro} {\justify + + +Active Galactic Nuclei (AGN) phenomena enable an understanding of +the growth of supermassive black holes (BHs), aspects of galaxy evolution, the high-redshift universe, +and other physical activity including accretion physics, jets, and magnetic fields. +While AGN represent a distinct topic within the LSST Science Collaborations, the LSST +dataset will reveal some aspects of AGN science via their role as an +evolutionary stage of galaxies in addition to their ability to probe accretion physics around BHs. +The tasks listed here present preparatory science efforts connected with AGN study as a special +phase in galaxy evolution. + + +\begin{tasklist}{AGN} +\subsection{AGN Selection from LSST Data} +\tasktitle{AGN Selection from LSST Data} +\begin{task} +\label{task:agn:selection} +\motivation{ +LSST multiband photometry may select Active Galactic Nuclei using a variety of different methods. At optical and near infrared wavelengths, the distinctive colors of AGN +at particular redshifts enables their photometric selection \citep[e.g.,][]{richards2006a}. +The LSST data will therefore augment methods that rely on X-ray or radio activity, or the +identification of emission lines in spectroscopic data. +LSST will also open up, in a more practical way, the identification of AGN based on their variability. +These LSST photometric, multiwavelength, and variability-selected samples may probe +unique aspects of AGN phenomena. +A better understanding of the AGN role in galaxy evolution requires +an understanding of how and why these selection methods include or exclude particular sources +or phases of AGN-galaxy co-evolution. +} +~\\ +\activities{ +The use of LSST as a single way to identify AGN and characterize their diversity of AGN +requires the development of selection criteria that can leverage the color, morphology, +and variability information available from LSST imaging alone. +A number of AGN surveys with input from multiple wavelength observations and spectra already +exist, and precursor work must utilize these surveys to determine +whether AGN that prove difficult to identify via optical color selection will reveal +themselves through the additional parameters of morphology, variability, and/or the +near-infrared data that LSST will provide. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Creation of a cross-matched catalog of known AGN selected and verified using different methods. +\item Understanding of AGN variability sensitivity given the nominal LSST cadence. +\item Development of algorithms that probe how color selection accounts for AGN variability. +\end{enumerate} +} +\end{task} +%\end{tasklist} + + +%\begin{tasklist}{T} +\subsection{AGN Host Galaxy Properties from LSST Data} +\tasktitle{AGN Host Galaxy Properties from LSST Data} +\begin{task} +\label{task:agn:host_galaxies} +\motivation{ +Morphological characterizations from parameterized models, such as multiple-component +\cite{sersic1968a} profiles, or non-parametric measures like CAS and Gini-M20 +\citep{abraham1994a,conselice2000a,lotz2004a} can help identify merging galaxies in the LSST data. +The ability of these techniques to characterize efficiently and accurately the +morphology of AGN host galaxies identified via their variability remains unproven. +} +~\\ +\activities{ +Simulated or model AGN host galaxies can characterize whether the +LSST Level 2 data will enable the measurement of morphological features associated with +AGN, as a function of host galaxy properties, AGN luminosity, and variability. +For each model galaxy, varying the central AGN luminosity will reveal the impact of +central source brightness on the recovery of morphological properties. +Existing data sets, such as Pan-STARRS, may help inform LSST about the range of +variability frequency and amplitude, and how these AGN properties may affect the +recovery of morphological properties in AGN host galaxies. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Characterization of the accuracy and precision afforded by the LSST dataset for the +recovery of basic morphology properties as a function of AGN brightness and wavelength. +\item Understanding of the effects of AGN brightness and variability on host-galaxy classification diagrams. +\item Development of morphological parameters beyond star/galaxy separation and an understanding of the efficacy of LSST Level 2 data products for morphological selection of AGN. +\item Development of color selection criteria that accounts for morphology. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +\subsection{AGN Feedback in Clusters} +\tasktitle{AGN Feedback in Clusters} +\begin{task} +\label{task:agn:feedback_in_clusters} +\motivation{ +Brightest Cluster/Group Galaxies (hereafter BCGs) represent the most massive galaxies in the local +universe, residing at or near the centers of galaxy clusters and groups. +BCGs contain the largest known supermassive BHs that can influence the host galaxy properties, +cluster gas, and other cluster members via the mechanical energy produced by their $>100$kpc +scale jets (``AGN feedback''). +The relative proximity of low-redshift galaxy clusters enable detailed studies of +stars, gas, and AGN jets that may reveal the ramifications of AGN feedback. +LSST will provide a large sample of moderate- to high-redshift clusters +in which we can measure AGN feedback statistically. By combining X-ray, radio, and optical observations we can assess the average influence of BCG AGN on the hot intracluster medium (ICM) for different sub-populations \citep[e.g.,][]{stott2012a}. +} +~\\ +\activities{ +By assembling a multi-wavelength dataset (optical, X-ray, and radio), the BCG mass, cluster mass, ICM temperature, and mechanical power injected into the ICM by supermassive BHs can be constrained. +The interplay between the BCG, its black hole, and the cluster gas can then be studied, +providing an assessment of the balance of energies involved and a direct comparison with theoretical models of AGN feedback. +SDSS has enabled this multi-wavelength analysis for a few hundred clusters at $z<0.3$, +but LSST cluster datasets will reach deeper to redshifts $z>1$. +Such studies hold implications for cosmological studies by helping to distinguish between +X-ray gas properties strongly influenced by AGN or that arise only in response +to the +cluster gravitational potential. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Investigation and quantification of the ability of the LSST pipeline to select BCGs using precursor datasets such as the HSC survey. +\item Compilation of existing and forthcoming radio and X-ray data available for AGN feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS, etc.). +\item Assessment of theoretical predictions expected for the multi-wavelength properties of +AGN host galaxies in clusters or groups (e.g., cosmological simulations such as EAGLE or more detailed single cluster studies). +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\subsection{AGN Variability Selection in LSST Data} +\tasktitle{AGN Variability Selection in LSST Data} +\begin{task} +\label{task:agn:variability} +\motivation{ +Most AGN exhibit broad-band aperiodic, stochastic variability across the entire electromagnetic +spectrum on timescales ranging from minutes to years. Continuum variability arises in the accretion disk of the AGN, providing a powerful probe of accretion physics. +The main LSST Wide Fast Deep (WFD) survey will obtain $\sim10^8$ AGN light curves (i.e., flux as a function of time) with $\sim1000$ observations ($\sim200$ per filter band) over 10 years. +The Deep Drilling Fields will provide AGN lightcurves with much denser sampling for a small subset of the objects in the WFD survey. The science content of the lightcurves will critically depend on the exact sampling strategy used to obtain the light curves. For example, the observational uncertainty in determining the color variability of AGN will crucially depend on the interval between observations in individual filter bands. These concerns motivate a determination of guidelines for an optimal survey strategy (from an AGN variability perspective) and a discovery +of possible biases and uncertainties introduced into AGN variability science as a result of the chosen survey strategy.} +~\\ +\activities{ +Study existing AGN variability datasets (SDSS Stripe 82, OGLE, PanSTARRS, CRTS, PTF + iPTF, Kepler, \& K2) to constrain a comprehensive set of AGN variability models. Generate and study simulations using parameters selected from these models using observational constraints, and determine the appropriateness of simulations for carrying out various types of AGN variability science including power spectrum models, quasi-periodic oscillation searches, and binary AGN models.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Observational constraints on AGN variability models. +\item Metrics for quantifying the efficacy of different survey strategies for AGN variability science. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\subsection{AGN Photometric Redshifts from LSST Data} +\tasktitle{AGN Photometric Redshifts from LSST Data} +\begin{task} +\label{task:agn:photoz} +\motivation{ +Given the large number of AGN that LSST will discover, +many AGN will not receive follow-up with spectroscopic observations. +Photometric redshifts can provide relatively accurate redshifts for large numbers of galaxies, +but accurate photometric redshifts for AGN host galaxies remain challenging. +} +~\\ +\activities{ +Initial efforts include a comprehensive review of the state of the art in AGN host galaxy photo-$z$ +determinations and an analysis of AGN vs. non-AGN galaxy photo-$z$ performance. +A comparison of model and/or observed AGN host SEDs with a matched set of +non-host galaxies at a variety of redshifts will help engineer color selection criteria for identifying AGN hosts, and whether variability can break photo-$z$ degeneracies. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Development of AGN host color selection criteria, and an identification of objects for which color selection might prove ambiguous or degenerate. +\item Analysis of multiwavelength, morphological, or variability information that might break photo-$z$ degeneracies. This task complements work described in Section \ref{task:photo_z:color_simulations} +(Photometric Redshifts) and should be coordinated with those efforts. +\end{enumerate} +} +\end{task} +%\end{tasklist} + +%\begin{tasklist}{T} +\subsection{AGN Merger Signatures from LSST Data} +\tasktitle{AGN Merger Signatures from LSST Data} +\begin{task} +\label{task:agn:mergers} +\motivation{ +Understanding the role AGN play in galaxy evolution requires identifying AGN phenomena at all stages and in all types of galaxies. +AGN host galaxies often show disturbed morphology, suggesting that the galaxy merger process may trigger AGN activity. +While the ``trainwrecks'' may prove easy to identify in the high-quality LSST data, the +identification of galaxies in other merger stages, such as ``pre-merger'' harassment, may be particularly hard to recognize. +Preliminary work needs to be done to understand how to identify mergers from the LSST data products and whether galaxy deblending and segmentation methods and procedures are adequate. +} +~\\ +\activities{ +Create simulated or identify real images that contain known galaxy mergers, including +systems with and without visible AGN. +Run the LSST software stack on these images, and +engineer metrics that quantify +the accurate detection of galaxy mergers with and without AGN. +Activities for detecting some of these low surface brightness (LSB) features will parallel work described in Section \ref{task:gal:lsb} +(Galaxy Evolution) and should be coordinated with those efforts. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Characterization and optimization of the ability of the LSST Level 2 data to enable the detection of galaxy mergers that host AGN. +\item Identification of catalog parameters or merging galaxy images with properties that will prove challenging to recognize (semi-)automatically in the LSST dataset. +\end{enumerate} +} +\end{task} +\end{tasklist} +} diff --git a/arxiv/apj.bst b/arxiv/apj.bst new file mode 100644 index 0000000..8d3ac16 --- /dev/null +++ b/arxiv/apj.bst @@ -0,0 +1,1628 @@ +%% $Log: apj.bst,v $ +%% Revision 1.4 2002/06/18 16:37:48 alberto +%% Add comma after first author in two-author reference +%% Fix courtesy of Tim Robishaw +%% +%% Revision 1.3 2000/04/20 22:17:50 jbaker +%% Fixed INBOOK bug, now works essentially like BOOK. +%% +%% Revision 1.2 1998/08/30 22:35:45 jbaker +%% Added RCS keywords. +%% +%% 1998/08/12 J Baker +%% Tweaked by hand to get correct results for ApJ. Added functions from +%% astrobib. + + +%% +%% This is file `apj.bst', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% merlin.mbs (with options: `,ay,nat,nm-rev,nmdash,dt-beg,yr-per,note-yr,atit-u,jtit-x,jttl-rm,thtit-a,vnum-x,volp-com,jpg-1,pp-last,btit-rm,add-pub,pub-par,pre-edn,edby,edbyx,blk-com,fin-bare,ppx,ed,abr,ord,jabr,amper,em-x') +%% ---------------------------------------- +%% *** Bibliographic Style for ApJ *** +%% + %------------------------------------------------------------------- + % The original source file contains the following version information: + % \ProvidesFile{merlin.mbs}[1998/02/25 3.85a (PWD)] + % + % NOTICE: + % This file may be used for non-profit purposes. + % It may not be distributed in exchange for money, + % other than distribution costs. + % + % The author provides it `as is' and does not guarantee it in any way. + % + % Copyright (C) 1994-98 Patrick W. Daly + %------------------------------------------------------------------- + % For use with BibTeX version 0.99a or later + %------------------------------------------------------------------- + % This bibliography style file is intended for texts in ENGLISH + % This is an author-year citation style bibliography. As such, it is + % non-standard LaTeX, and requires a special package file to function properly. + % Such a package is natbib.sty by Patrick W. Daly + % The form of the \bibitem entries is + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Smith]{key}... + % The essential feature is that the label (the part in brackets) consists + % of the author names, as they should appear in the citation, with the year + % in parentheses following. There must be no space before the opening + % parenthesis! + % With natbib v5.3, a full list of authors may also follow the year. + % In natbib.sty, it is possible to define the type of enclosures that is + % really wanted (brackets or parentheses), but in either case, there must + % be parentheses in the label. + % The \cite command functions as follows: + % \citet{key} ==>> Jones et al. (1990) + % \citet*{key} ==>> Jones, Baker, and Smith (1990) + % \citep{key} ==>> (Jones et al., 1990) + % \citep*{key} ==>> (Jones, Baker, and Smith, 1990) + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.][]{key} ==>> (e.g. Jones et al., 1990) + % \citep[e.g.][p. 32]{key} ==>> (e.g. Jones et al., p. 32) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Smith + % \citeyear{key} ==>> 1990 + %--------------------------------------------------------------------- + +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ duplicate$ empty$ + 'pop$ + 'write$ + if$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {add.blank} +{ " " * before.all 'output.state := +} + +FUNCTION {date.block} +{ + skip$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ skip$ } + +FUNCTION {capitalize} +{ "u" change.case$ "t" change.case$ } + +FUNCTION {space.word} +{ " " swap$ * " " * } + + % Here are the language-specific definitions for explicit words. + % Each function has a name bbl.xxx where xxx is the English word. + % The language selected here is ENGLISH +FUNCTION {bbl.and} +{ "and"} + +FUNCTION {bbl.editors} +{ "eds." } + +FUNCTION {bbl.editor} +{ "ed." } + +FUNCTION {bbl.edby} +{ "edited by" } + +FUNCTION {bbl.edition} +{ "edn." } + +FUNCTION {bbl.volume} +{ "Vol." } + +FUNCTION {bbl.of} +{ "of" } + +FUNCTION {bbl.number} +{ "no." } + +FUNCTION {bbl.nr} +{ "no." } + +FUNCTION {bbl.in} +{ "in" } + +FUNCTION {bbl.pages} +{ "" } + +FUNCTION {bbl.page} +{ "" } + +FUNCTION {bbl.chapter} +{ "Ch." } +%{ "chap." } + +FUNCTION {bbl.techrep} +{ "Tech. Rep." } + +FUNCTION {bbl.mthesis} +{ "Master's thesis" } + +FUNCTION {bbl.phdthesis} +{ "PhD thesis" } + +FUNCTION {bbl.first} +{ "1st" } + +FUNCTION {bbl.second} +{ "2nd" } + +FUNCTION {bbl.third} +{ "3rd" } + +FUNCTION {bbl.fourth} +{ "4th" } + +FUNCTION {bbl.fifth} +{ "5th" } + +FUNCTION {bbl.st} +{ "st" } + +FUNCTION {bbl.nd} +{ "nd" } + +FUNCTION {bbl.rd} +{ "rd" } + +FUNCTION {bbl.th} +{ "th" } + +MACRO {jan} {"Jan."} + +MACRO {feb} {"Feb."} + +MACRO {mar} {"Mar."} + +MACRO {apr} {"Apr."} + +MACRO {may} {"May"} + +MACRO {jun} {"Jun."} + +MACRO {jul} {"Jul."} + +MACRO {aug} {"Aug."} + +MACRO {sep} {"Sep."} + +MACRO {oct} {"Oct."} + +MACRO {nov} {"Nov."} + +MACRO {dec} {"Dec."} + +FUNCTION {eng.ord} +{ duplicate$ "1" swap$ * + #-2 #1 substring$ "1" = + { bbl.th * } + { duplicate$ #-1 #1 substring$ + duplicate$ "1" = + { pop$ bbl.st * } + { duplicate$ "2" = + { pop$ bbl.nd * } + { "3" = + { bbl.rd * } + { bbl.th * } + if$ + } + if$ + } + if$ + } + if$ +} + +MACRO {acmcs} {"ACM Comput. Surv."} + +MACRO {acta} {"Acta Inf."} + +MACRO {cacm} {"Commun. ACM"} + +MACRO {ibmjrd} {"IBM J. Res. Dev."} + +MACRO {ibmsj} {"IBM Syst.~J."} + +MACRO {ieeese} {"IEEE Trans. Softw. Eng."} + +MACRO {ieeetc} {"IEEE Trans. Comput."} + +MACRO {ieeetcad} + {"IEEE Trans. Comput.-Aided Design Integrated Circuits"} + +MACRO {ipl} {"Inf. Process. Lett."} + +MACRO {jacm} {"J.~ACM"} + +MACRO {jcss} {"J.~Comput. Syst. Sci."} + +MACRO {scp} {"Sci. Comput. Programming"} + +MACRO {sicomp} {"SIAM J. Comput."} + +MACRO {tocs} {"ACM Trans. Comput. Syst."} + +MACRO {tods} {"ACM Trans. Database Syst."} + +MACRO {tog} {"ACM Trans. Gr."} + +MACRO {toms} {"ACM Trans. Math. Softw."} + +MACRO {toois} {"ACM Trans. Office Inf. Syst."} + +MACRO {toplas} {"ACM Trans. Prog. Lang. Syst."} + +MACRO {tcs} {"Theoretical Comput. Sci."} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + + numnames 'namesleft := + { namesleft #0 > } + { + s nameptr "{vv~}{ll}{, jj}{, f.}" format.name$ 't := + nameptr #1 > + { + #8 numnames < + { #0 'namesleft := } + 'skip$ + if$ + namesleft #1 > + { ", " * t * } + { + numnames #1 > +%% AA 6/18/2002 +%% This fix courtesy of Tim Robishaw : +%% Original version left comma out after initials of first author +%% for two-author papers!! +%% numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + %t "others" = + #8 numnames < + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.names.ed} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{f.~}{vv~}{ll}{, jj}" + format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", " * bbl.editors * } + { ", " * bbl.editor * } + if$ + } + if$ +} + +FUNCTION {format.in.editors} +{ editor empty$ + { "" } + { editor format.names.ed + } + if$ +} + +FUNCTION {format.note} +{ note empty$ + { "" } + { note #1 #1 substring$ + duplicate$ "{" = + 'skip$ + { output.state mid.sentence = + { "l" } + { "u" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title + } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " {et~al.}" * + } + { " \& " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.key.full} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.key.full} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {editor.key.full} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.full + { type$ "proceedings" = + 'editor.key.full + 'author.key.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[{" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "}]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {word.in} +{ bbl.in + " " * } + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * "; set to ????" * warning$ + pop$ "????" } + 'skip$ + if$ + extra.label * + before.all 'output.state := + after.sentence 'output.state := +} + +FUNCTION {format.btitle} +{ title +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { bbl.volume volume tie.or.space.connect + series empty$ + 'skip$ + { bbl.of space.word * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { bbl.number } + { bbl.number capitalize } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { bbl.in space.word * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {is.num} +{ chr.to.int$ + duplicate$ "0" chr.to.int$ < not + swap$ "9" chr.to.int$ > not and +} + +FUNCTION {extract.num} +{ duplicate$ 't := + "" 's := + { t empty$ not } + { t #1 #1 substring$ + t #2 global.max$ substring$ 't := + duplicate$ is.num + { s swap$ * 's := } + { pop$ "" 't := } + if$ + } + while$ + s empty$ + 'skip$ + { pop$ s } + if$ +} + +FUNCTION {convert.edition} +{ edition extract.num "l" change.case$ 's := + s "first" = s "1" = or + { bbl.first 't := } + { s "second" = s "2" = or + { bbl.second 't := } + { s "third" = s "3" = or + { bbl.third 't := } + { s "fourth" = s "4" = or + { bbl.fourth 't := } + { s "fifth" = s "5" = or + { bbl.fifth 't := } + { s #1 #1 substring$ is.num + { s eng.ord 't := } + { edition 't := } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + } + if$ + t +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { convert.edition "l" change.case$ " " * bbl.edition * } + { convert.edition "t" change.case$ " " * bbl.edition * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check +% { bbl.pages pages n.dashify tie.or.space.connect } +% { bbl.page pages tie.or.space.connect } + { pages n.dashify } + { pages } + if$ + } + if$ +} + +FUNCTION {first.page} +{ 't := + "" + { t empty$ not t #1 #1 substring$ "-" = not and } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + while$ +} + +FUNCTION {format.journal.pages} +{ pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { + ", " * + pages first.page * + } + if$ + } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + { "" } + { type empty$ + { bbl.chapter } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { word.in booktitle emphasize * } + { word.in booktitle emphasize * + ", " * + editor num.names$ #1 > + { bbl.editors } + { bbl.editor } + if$ + * " " * + format.in.editors * + } + if$ + } + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { bbl.techrep } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + word.in + } + { bbl.volume volume tie.or.space.connect + bbl.of space.word * + } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} + +FUNCTION {format.publisher} +{ publisher empty$ + { "empty publisher in " cite$ * warning$ } + 'skip$ + if$ + "" + address empty$ publisher empty$ and + 'skip$ + { + add.blank "(" * + address empty$ + 'skip$ + { address * } + if$ + publisher empty$ + 'skip$ + { address empty$ + 'skip$ + { ": " * } + if$ + publisher * + } + if$ + ")" * + } + if$ + output +} + +STRINGS {oldname} + +FUNCTION {name.or.dash} +{ 's := + oldname empty$ + { s 'oldname := s } + { s oldname = + { "---" } + { s 'oldname := s } + if$ + } + if$ +} + +%%%%%%%% Functions added from astrobib + +FUNCTION {format.edn.btitle} % Title should be on stack. +{ duplicate$ empty$ edition empty$ or + 'skip$ + { ", " * format.edition * } + if$ +} + +FUNCTION {format.ed.booktitle} % The title should be on the stack. +{ duplicate$ empty$ + { "no book title in " cite$ * warning$ "" pop$ } + { editor empty$ + author empty$ or % Empty author means editor already given. + 'format.edn.btitle + { format.edn.btitle ", " * bbl.editor * " " * format.in.editors * } + if$ + } + if$ +} + +FUNCTION {format.full.book.spec} % The title should be on the stack. +{ series empty$ + { format.ed.booktitle + volume empty$ + { number empty$ + 'skip$ + { " there's a number but no series in " cite$ * warning$ + " No." number tie.or.space.connect * } + if$ + } + { ", Vol." volume tie.or.space.connect * + number empty$ + 'skip$ + {"Both volume and number fields in " * cite$ * warning$ } + if$ + } + if$ + } + { volume empty$ + { format.ed.booktitle ", " * series * + number empty$ + 'skip$ + { " No." number tie.or.space.connect * } + if$ + } + { series ", Vol." volume tie.or.space.connect * + ", " * swap$ format.ed.booktitle * + number empty$ + 'skip$ + {"Both volume and number fields in " * cite$ * warning$ } + if$ + } + if$ + } + if$ +} + +%%%%%%% End of functions from astrobib + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + crossref missing$ + { journal + "journal" output.check + format.vol.num.pages output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + format.journal.pages + format.note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + name.or.dash + } + { format.authors output.nonnull + name.or.dash + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% crossref missing$ +% { format.bvolume output +% format.number.series output +% format.edition output + format.publisher +% } +% { +% format.book.crossref output.nonnull +% } +% if$ + format.pages output + format.note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title "title" output.check + howpublished output + address output + format.note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + name.or.dash + } + { format.authors output.nonnull + name.or.dash + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% crossref missing$ +% { +% format.bvolume output +% format.chapter.pages "chapter and pages" output.check +% format.number.series output +% format.edition output + format.publisher +% } +% { +% format.chapter.pages "chapter and pages" output.check +% format.book.crossref output.nonnull +% } +% if$ + format.pages "pages" output.check + format.note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + bbl.in " " * booktitle format.full.book.spec * output +% crossref missing$ +% { format.in.ed.booktitle "booktitle" output.check +% format.bvolume output +% format.number.series output +% format.edition output +% format.chapter.pages output + format.publisher +% } +% { format.incoll.inproc.crossref output.nonnull +% format.chapter.pages output +% } +% if$ + format.pages "pages" output.check + format.note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output % added + format.date "year" output.check + date.block + bbl.in " " * booktitle format.full.book.spec * output +% crossref missing$ +% { format.in.ed.booktitle "booktitle" output.check +% format.bvolume output +% format.number.series output + publisher empty$ + { organization output + address output + } + { organization output + format.publisher + } + if$ +% } +% { format.incoll.inproc.crossref output.nonnull +% } +% if$ + format.pages output + format.note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.btitle "title" output.check + format.edition output + organization output + address output + format.note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + bbl.mthesis format.thesis.type output.nonnull + school "school" output.check + address output + format.note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title output + howpublished output + format.note output + fin.entry +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + bbl.phdthesis format.thesis.type output.nonnull + school "school" output.check + address output + format.note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output + organization format.key output } + { format.editors output } + if$ +% format.editors output +% editor format.key output + name.or.dash + format.date "year" output.check + date.block + title format.full.book.spec output +% format.btitle "title" output.check +% format.bvolume output +% format.number.series output + publisher empty$ not % No need for warning if no pub. + { format.publisher } + { editor empty$ % For empty editor, organization was already given. + 'skip$ + { organization output } + if$ + address output + } + if$ +% address output +% organization output +% publisher output + format.pages output + format.note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block + format.title "title" output.check + format.tr.number output.nonnull + institution "institution" output.check + address output + format.note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + name.or.dash + format.date "year" output.check + date.block +% format.title "title" output.check + format.note "note" output.check + fin.entry +} + +FUNCTION {default.type} { misc } + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ + " {et~al.}" * + } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { + " {et~al.}" * + } + { " \& " * s #2 "{vv~}{ll}" format.name$ + * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.label} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.label + 'author.key.label + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + { pop$ "????" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv{ } }{ll{ }}{ f{ }}{ jj{ }}" + format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { t sortify * } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.sort} +{ editor empty$ + { key empty$ + { "to sort, need editor or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.sort + 'author.sort + if$ + } + if$ + #1 entry.max$ substring$ + 'sort.label := + sort.label + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { last.label next.extra } + +INTEGERS { last.extra.num number.label } + +FUNCTION {initialize.extra.label.stuff} +{ #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.extra.label.stuff} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} +%% End of customized bst file +%% +%% End of file `apj.bst'. diff --git a/arxiv/authorlist.tex b/arxiv/authorlist.tex new file mode 100644 index 0000000..cbb29c4 --- /dev/null +++ b/arxiv/authorlist.tex @@ -0,0 +1,105 @@ +Robertson, Brant E.$^{1}$, +Banerji, Manda$^{2}$, +Cooper, Michael C.$^{3}$, +Davies, Roger$^{4}$, +Driver, Simon P.$^{5}$, +Ferguson, Annette M. N.$^{6}$, +Ferguson, Henry C.$^{7}$, +Gawiser, Eric$^{8}$, +Kaviraj, Sugata$^{9}$, +Knapen, Johan H.$^{10,11}$, +Lintott, Chris$^{4}$, +Lotz, Jennifer$^{7}$, +Newman, Jeffrey A.$^{12}$, +Norman, Dara J.$^{13}$, +Padilla, Nelson$^{14}$, +Schmidt, Samuel J.$^{15}$, +Smith, Graham P.,$^{16}$, +Tyson, J. Anthony$^{15}$, +Verma, Aprajita$^{4}$, +Zehavi, Idit$^{17}$, +Armus, Lee$^{18}$, +Avestruz, Camille$^{19}$, +Barrientos, L. Felipe$^{14}$, +Bowler, Rebecca A. A.$^{4}$, +Bremer, Malcolm N.$^{20}$, +Conselice, Christopher J.$^{21}$, +Davies, Jonathan$^{22}$, +Demarco, Ricardo$^{23}$, +Dickinson, Mark E.$^{13}$, +Galaz, Gaspar$^{14}$, +Grazian, Andrea$^{24}$, +Holwerda, Benne W.$^{25}$, +Jarvis, Matt J.$^{4,26}$, +Kasliwal, Vishal$^{27,28,29}$, +Lacerna, Ivan$^{30,14}$, +Loveday, Jon$^{31}$, +Marshall, Phil$^{32}$, +Merlin, Emiliano$^{24}$, +Napolitano, Nicola R.$^{33}$, +Puzia, Thomas H.$^{14}$, +Robotham, Aaron$^{5}$, +Salim, Samir$^{34}$, +Sereno, Mauro$^{35}$, +Snyder, Gregory F.$^{7}$, +Stott, John P.$^{36}$, +Tissera, Patricia B.$^{37}$, +Werner, Norbert$^{38,39,40}$, +Yoachim, Peter$^{41}$, +Borne, Kirk D.$^{42}$, +and Members of the LSST Galaxies Science Collaboration + +%\vspace*{2mm} + +{\justify\it\small +$^{1}$Department of Astronomy and Astrophysics, University of California, Santa Cruz, Santa Cruz, CA 96054, USA, +$^{2}$Institute of Astronomy, Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB30HA, UK, +$^{3}$Department of Physics and Astronomy, University of California, Irvine, 4129 Frederick Reines Hall, Irvine, CA 92697, USA, +$^{4}$Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Rd., Oxford, OX1 3RH, UK, +$^{5}$International Centre for Radio Astronomy Research (ICRAR), University of Western Australia, Perth, Australia, WA 6009, Australia, +$^{6}$Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, UK, +$^{7}$Space Telescope Science Institute, 3700 San Martin Drive, Baltimore MD 21218, USA, +$^{8}$Rutgers University, 136 Frelinghuysen Rd., Piscataway, NJ 08854-8019, USA, +$^{9}$Centre for Astrophysics Research, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, UK, +$^{10}$Instituto de Astrof\'\i sica de Canarias, E-38200 La Laguna, Spain, +$^{11}$Departamento de Astrof\'\i sica, Universidad de La Laguna, E-38206 La Laguna, Spain, +$^{12}$Department of Physics and Astronomy and PITT PACC, University of Pittsburgh, 3941 O{'}Hara St., Pittsburgh, PA 15260, USA, +$^{13}$NOAO, 950 N. Cherry Ave, Tucson, AZ 85719, USA, +$^{14}$ Instituto de Astrof\'\i sica, Pontificia Universidad, +Cat{\'{o}}lica Chile, Vicu{\~{n}}a Mackenna 4860, Santiago, Chile, +$^{15}$Department of Physics, University of California, Davis, One Shields Ave, Davis, CA, 95616, USA, +$^{16}$School of Physics and Astronomy, University of Birmingham, Edgbaston, B15 2TT, UK, +$^{17}$Department of Astronomy, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA, +$^{18}$IPAC/Caltech, 1200 E. California Blvd. MS314-6, Pasadena, CA 91125, USA, +$^{19}$Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Ave., Chicago, IL 60637, USA, +$^{20}$H.H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol, BS8 1TL, UK, +$^{21}$School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK, +$^{22}$Cardiff University, School of Physics and Astronomy, The Parade, Cardiff, CF22 3AA, UK, +$^{23}$Departamento de Astronom\'\i a, Universidad de Concepci{\'{o}}n,Casilla 160-C, Concepci{\'{o}}n, Chile, +$^{24}$INAF - Osservatorio Astronomico di Roma, Via Frascati, 33, I-00078, Monte Porzio Catone (Roma), Italy, +$^{25}$Department of Physics and Astronomy, 102 Natural Science Building, University of Louisville, Louisville KY 40292, USA, +$^{26}$Department of Physics, University of the Western Cape, Bellville 7535, South Africa, +$^{27}$Colfax International, 750 Palomar Avenue, Sunnyvale, CA 94085, USA, +$^{28}$University of Pennsylvania, Department of Physics \& Astronomy, 209 S 33rd St, Philadelphia, PA 19104, USA, +$^{29}$Princeton University, Department of Astrophysical Sciences, 4 Ivy Lane, Princeton, NJ 08544, USA, +$^{30}$Instituto Milenio de Astrof\'\i sica, Av. Vicu{\~{n}}a Mackenna 4860, Macul, Santiago, Chile, +$^{31}$Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QH, UK, +$^{32}$Kavli Institute for Particle Astrophysics and Cosmology, P.O. Box 20450, MS29, Stanford, CA 94309, USA, +$^{33}$INAF -Osservatorio Astronomico di Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy, +$^{34}$Indiana University, Department of Astronomy, Bloomington, IN 47405, USA, +$^{35}$INAF - Osservatorio Astronomico di Bologna; Dipartimento di Fisica e Astronomia, Universit\`a di Bologna Alma-Mater, via Piero Gobetti 93/3, I-40129 Bologna, Italy, +$^{36}$Department of Physics, Lancaster University, Lancaster LA1 4YB, UK, +$^{37}$Astrophysics Group, Department of Physics - Campus La Casona, Universidad Andres Bello, Fernandez Concha 700, Las Condes, Santiago, Chile, +$^{38}$1 MTA-Eotvos University Hot Universe Research Group, Pazmany Peter Setany 1/A, Budapest, 1117, Hungary, +$^{39}$Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, Brno, 611 37, Czech Republic, +$^{40}$School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan, +$^{41}$University of Washington, Box 351580, U.W. Seattle, WA 98195-1580, USA, +$^{42}$Booz Allen Hamilton, 308 Sentinel Drive, Suite 100, Annapolis Junction, MD 20701, USA + + + + + + + +} diff --git a/arxiv/aux.tex b/arxiv/aux.tex new file mode 100644 index 0000000..758b860 --- /dev/null +++ b/arxiv/aux.tex @@ -0,0 +1,141 @@ +\section{Auxiliary Data}\label{sec:tasks:aux} +{\justify +While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing, future, and proposed external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, X-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation for and during LSST operations it is therefore prudent to ensure appropriate access, usability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. + + + +\begin{tasklist}{AUX} +\subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} +\tasktitle{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} +\begin{task} +\label{task:aux:spectroscopy} +\motivation{ +Although great strides have been made in projects using photometric redshifts alone, some science is only possible with either spectroscopic redshifts and/or spectroscopic line measurements. In particular, spectroscopic redshifts are essential when distance accuracies of less than 1000 km/s are required; for example in identifying galaxy pairs and groups. Robust measurement of gas and stellar phase metallicities also require spectra with relatively high signal-to-noise and resolution. +Finally, photometric redshifts still require spectroscopic redshifts for both calibration and accuracy assessment. As such, it is essential that we ensure the LSST community has access to the available high precision redshifts, spectroscopically-derived properties and calibrated spectra for all available galaxies and quasars within the LSST footprint. This necessarily entails bringing together data from disparate surveys (such as 2dFGRS, SDSS, 6dF, MGC, GAMA, VIPERS, VVDS), the homogenization of data products and quality control, as well as the ongoing ingestion of upcoming spectroscopic campaigns such as TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. This will require significant pre-LSST effort. +} +~\\ +\activities{ +Several activities are necessary to compile this spectroscopic database: +\begin{enumerate} +\item Establishment of a database structure capable of accommodating and serving both spectra and derived data products including fast SQL database queries. +\item Ingestion of existing key public datasets including, for example: 2dFGRS, SDSS, 2QZ, 2SLAQ, 6dF, MGC, GAMA, ESP, VVDS, VIPERS. +\item A process for establishing quality control and homogenization of datasets including assignment of revised quality flags. +\item A pathway for ingesting future datasets as they become available and potentially in advance via MOU arrangements, e.g., TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid, etc. +\end{enumerate} +Approximately 6 million spectroscopic redshifts are known, with the majority of these already in the public domain, along with associated flux and wavelength calibrated spectra. In addition, derived parameters also exist for many of these spectra including, but not limited too, redshifts, equivalent widths, velocity dispersions, line asymmetries etc. Many of these measurements have been made using bespoke software specific to each originating survey (e.g., SDSS v 2dFGRS), creating an inhomogeneous network of data, measurements and quality control flags within the LSST footprint. +In addition, in the next decade a number of new surveys will expand these measurements from millions to tens of millions of spectra through facilities and programs such as LAMOST, 4MOST, DESI as well as coarse spectroscopic information via GRISM data from Euclid and eventually WFIRST, leading to a wealth of spectroscopic data which will be invaluable to LSST. +The community has two specific problems, i) collating this data and ii) ensuring quality control and standardization. Due to differing observing and analysis techniques not all spectroscopic measurements will be equal, and will depend on the resolution, signal-to-noise and precise software applied. +Within reason some effort should be made to both collate and standardize the data with some provision of a uniform quality control process. At the bare minimum this should result in a database which contains the flux and wavelength calibrated spectra, links or copies of original derived products, and crucially, measurements using a uniform set of software analysis tools (e.g., to produce consistent redshift and equivalent width measurements) with some coherent cross-survey quality control flags. +While this task sounds intimidating, this is exactly what has been achieved within the 200 square degrees of the Galaxy And Mass Assembly survey \citep{driver2011a,driver2016a,liske2015a} and an expansion of this process to the full LSST footprint is not unreasonable or impossible. However, this process needs to commence imminently if the database is to be in place for both LSST and the next generation of spectroscopic surveys. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item A useable and searchable database of spectra with associated derived products. +\item Derived products using standardized analysis codes to measure redshifts and equivalent widths, etc. +\item A strategy for ingesting additional datasets as they become available. +\end{enumerate} +} +\end{task} + + + +\subsection{Panchromatic Imaging within the LSST Footprint} +\tasktitle{Panchromatic Imaging within the LSST Footprint} +\begin{task} +\label{task:aux:panchromatic} +\motivation{ +LSST will only cover a small portion of the electromagnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available X-ray, UV, IR, and radio data. +While archives of these data exist independently, there is a dire need to establish a Universe database which federates these data in a coherent manner. One of the major concerns of such a database is the accurate multi-wavelength source identification and de-convolution in disparate data with wildly differing resolutions. For example, two closely separated sources in the LSST data may appear as a single source in lower resolution data. As such, significant errors will be made when simply table matching these photometric catalogues. +The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFIT/TPHOT; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to X-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse X-ray halos, discrete X-ray sources and extended radio lobes). +} +~\\ +\activities{ +Several activities are required: +\begin{enumerate} +\item Database to host imaging data from diverse sources, including astrometric alignment. +\item Software to define aperture in a specified (LSST) band. +\item Software to measure flux across panchromatic data taking into account original aperture definition, facility resolution, signal-to-noise limitations, and any physical priors. +\item Tools to serve imaging and photometric data either for individual or sets of objects. +\end{enumerate} +~\\~\\ +As galaxies emit radiation across the entire electromagnetic spectrum it is important to be able to trace this breadth of emission deriving from different astrophysical processes. This is particularly important in the LSST optical wavebands where anywhere from 0-90 per cent of the radiation might be attenuated by dust and re-radiated in the far-IR. +The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman and 4000\AA~breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. +Finally, X-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star formation. Unification across the wavelength range requires federation of these very disparate datasets, and may be worth centralizing prior to LSST operations. +Note a similar task has recently been achieved by the Galaxy And Mass Assembly team for a 200 square degree region \citep[see][and http://www/gama-survey.org/]{driver2016a} and can be extended to the full LSST footprint using similar techniques. +} +~\\ +\deliverables{%Deliverables over the next few years from the activities described above include: +~ +\begin{enumerate} +\item A database capable of serving image cutouts at any location over the LSST footprint and any wavelength (see http://cutout.icrar.org/psi.php for a similar database over the GAMA regions). This database should include +\begin{itemize} +\item X-ray maps from eROSITA +\item UV from GALEX +\item Optical from SkyMapper, DES, and Euclid. +\item Near-IR from VISTA and Euclid. +\item Mid-IR from WISE. +\item Far-IR from IRAS, Herschel, and potential missions like Spica. +\item Radio continuum and HI from ASKAP (EMU,WALLABY,DINGO), MeerKAT (LADUMA, MIGHTEE, MeerKLASS), and eventually the SKA. +\end{itemize} +\item Derived panchromatic photometry (on the fly or pre-processed). +\end{enumerate} +} +\end{task} + +\subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} +\tasktitle{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} +\begin{task} +\label{task:HI} +\motivation{ +% +How do galaxies evolve kinematically? The relation between stellar luminosity and rotation for disk galaxies is well known in the local Universe \citep[i.e., the Tully-Fisher or T-F relation, see][]{tully1977a,verheijen2001a} and +suspected to evolve as gas and stars form a disk within the dark matter gravitational potential. H\,{\sc{i}} extends throughout the stellar disk and well beyond, its kinematics tracing the galaxy's dark matter potential. +The potential evolution of the T-F relation, including possible evolution in the normalization, slope, or both, is an area of active research +\cite[][]{weiner2006a,tiley2016a}. +~\\~\\ +A few major drawbacks for these studies into the evolution of the T-F are +(a) the kinematic information comes from H$\alpha$ optical data (sometimes redshifted into the infra-red, +which does not trace the full rotation curve), +(b) adaptive optics for these observations filter out the lower surface brightness features such as the rotating +disk \citep[see for a review ][]{glazebrook2013a}, and +(c) these measurements are made for intrinsically bright samples of galaxies. +However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}.\\ +~\\ +The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b} and +detailed kinematics \citep{trachternach2008a} extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. +The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}.\\ +~\\ +For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), +an accurate photometry measurement, and a disk inclination. The last two critical measurements will be provided by LSST imaging. +There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST Deep Drilling Fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detection and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments.\\ +~\\ +Two other surveys represent the progressively wider/shallower H\,{\sc{i}} survey tiers with the ASKAP telescope \citep{johnston2007a}: DINGO, a survey of the GAMA fields \citep[][Meyer+ {\em in prep}]{driver2009a,duffy2012a,meyer2015a} and WALLABY, the Southern Sky H\,{\sc{i}} survey \citep[][Koribalski+ {\em in prep}]{duffy2012a}. + A benefit of the MeerKAT and ASKAP radio surveys is that radio continuum and 21cm line (H\,{\sc{i}}) emission are observed at the same time. +The survey strategy from wide and shallow to single deep field (WALLABY-DINGO-MIGHTEE-LADUMA) is designed to beat down cosmic variance effectively \citep[see e.g.,][]{maddox2016a}. +} +~\\ +\activities{ +Several activities are necessary to compile kinematic evolution using a combination of H\,{\sc{i}} kinematics and LSST imaging: +\begin{enumerate} +\item Accurate photometry of extended objects in all LSST Deep Drilling Fields. +\item accurate morphology of all galaxies with HI detections (to infer inclination). +\item Spectroscopic redshifts of all galaxies {\em not} detected in H\,{\sc{i}} for stacking purposes. +\end{enumerate} +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Robust and accurate inclination estimates from morphological fits/models. +\item Accurate galaxy photometry from LSST Deep Drilling Field stacks. +\item Stacking code for H\,{\sc{i}} spectra. +\end{enumerate} +} +\end{task} + + + +\end{tasklist} +} diff --git a/arxiv/clss.tex b/arxiv/clss.tex new file mode 100644 index 0000000..7f06b1c --- /dev/null +++ b/arxiv/clss.tex @@ -0,0 +1,392 @@ +\section{Clusters and Large-Scale Structure}\label{sec:tasks:clss} +{\justify +The cosmological process of galaxy formation inextricably links +together environment and large-scale structure with the detailed +properties of galaxy populations. The extent of this connection +ranges from the scales of superclusters down to small groups. The +following preparatory science tasks focus on this critical connection +between galaxy formation, clusters, and large-scale structure (LSS). + +\begin{tasklist}{CLSS} +\subsection{Cluster and Large-Scale Structure Sample Emulator} +\tasktitle{Cluster and Large-Scale Structure Sample Emulator} +\begin{task} +\label{task:clss:emulator} +\motivation{ +To prepare for galaxy group/cluster and LSS science with LSST, +the samples of cluster/group galaxies detected in a given range of +redshift, brightness, and color need to be estimated. +Group and +cluster populations must be identified in given ranges of redshift, richness, mass, +and other physical parameters. +} +~\\ +\activities{ +LSST has advanced simulations of its 10-year Wide Fast Deep survey +available from the Operations Simulator. The output databases can be +analyzed to determine the expected time-dependent depth of LSST +detection images at each sky location. These depths can be converted +into predicted numbers of galaxies as a function of redshift and +brightness \citep[e.g.,][]{awan2016a}.\\ +~\\ +To predict galaxy sample sizes as a function of physical parameters, +the ``raw'' predicted galaxy numbers can be +interfaced with semi-analytical models painted on large N-body +simulations. This approach can extend the +predictions for cluster/LSS samples +to include the observed properties of color, size, morphology, +and the physical properties of halo mass, stellar mass, and star formation +rate. The combination of these models will produce an LSST Cluster/LSS +Sample Emulator for understanding the detailed science return of +LSST for cluster and group science.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Creation of a public LSST Extragalactic Sample Emulator with a +simple user interface, allowing for the estimation of sample sizes +detected by LSST as a function of redshift and +physical parameters (e.g.~galaxy magnitudes, colors, size, morphology, +cluster richness, mass, temperature, etc.). +\end{enumerate} +} +\end{task} + + +\subsection{Identifying and Characterizing Clusters} +\tasktitle{Identifying and Characterizing Clusters} +\begin{task} +\label{task:clss:clusters} +\motivation{ LSST photometry will make it possible to search for and +study the galaxy populations of distant clusters and proto-clusters over +cosmological volumes. These clusters are testbeds for theories of +hierarchical structure formation, intergalactic medium heating, metal +enrichment, and galaxy evolution. However, standard approaches for +identifying clusters, such as the red sequence method, will be hampered +by the limited wavelength coverage of LSST. For example, at $z \gtrsim +1.5$, near-IR photometry is required to identify systems with +Balmer/$4000$\AA\ breaks. +To maximize cluster science with LSST, new +techniques for cluster identification and the incorporate complementary +data from projects such as \emph{Euclid} or \emph{eROSITA} must be devised. +Exploration of optimal filter methods +\citep[e.g.,][]{bellagamba2017a} +could improve cluster identification in LSST data. +} +~\\ +\activities{ Using existing imaging datasets and simulations, algorithms +need to be developed and optimized to identify clusters at intermediate- +and high- redshift within the LSST footprint. Specifically, this work +should characterize the selection function, completeness, and +contamination rate for different cluster identification algorithms. Such +characterizations require realistic light-cone simulations spanning +extremely large volumes, so as to capture significant numbers +($\gg10,000$) of simulated galaxy clusters at high-redshift. Potential +algorithms to be tested include adaptations of RedMaPPer +\citep{rykoff2014a}, methods that search for galaxy +overdensities over a range of scales \citep[e.g.,][]{chiang2014a,wang2016a}, +and +methods designed to select clusters from joint optical/NIR/X-ray +datasets. In parallel, a comprehensive census of the available +multiwavelength data (specifically IR and X-ray imaging) is needed to +enable the new algorithms to be tested on real observational data, +including multiwavelength datasets co-located with LSST Commissioning +observations. It will also be necessary to develop algorithms to +homogenize the external datasets with LSST data at the pixel level, and +enable them to be served to the community.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item New and improved cluster identification algorithms that can be +applied to LSST commissioning and survey data, and combined +LSST/NIR/X-ray data. +\item Compilation of auxiliary data that will aide testing of algorithms +to identify and characterize clusters, such as near-infrared (e.g. +VISTA, UKIDSS), X-ray (e.g.~XMM-Newton, eROSITA, etc.), SZ (Planck, SPT, +ACT), and radio (SKA and its pathfinders, SUMSS) within the LSST +footprint. +\item Algorithms to match optimally and homogenize multiwavelength +data with LSST commissioning and survey data. +\end{enumerate} +} +\end{task} + +\subsection{Developing and Optimizing Measurements of Galaxy Environment} +\tasktitle{Developing and Optimizing Measurements of Galaxy Environment} +\begin{task} +\label{task:clss:environment} +\motivation{ +Over the past decade, many studies have +shown that environment plays a important role in shaping galaxy +properties. For example, satellite galaxies in the local Universe +exhibit lower star formation rates, more bulge-dominated morphologies, +as well as older and more metal-rich stellar populations when compared +to isolated (or ``field'') systems of equivalent stellar mass +\citep{baldry2006a,cooper2010a,pasquali2010a}. +Unlike spectroscopic surveys, LSST will lack the precise line-of-sight +velocity measurements to robustly identify satellite galaxies in +lower-mass groups, where the expected photo-$z$ precision will be much +coarser than the corresponding +the velocity dispersion of typical host halos. +Instead, LSST will likely be better suited to measure environment by +tracing the local galaxy density and identifying filaments. However, +LSST is unlike any previous photometric survey and may require new +approaches to measuring environment. +The challenge remains to find measures of local galaxy density +with the greatest sensitivity to the true underlying density field (or +to host halo mass, etc.), so as to enable analyses of environment's +role in galaxy evolution with LSST. +} +~\\ +\activities{ +Using mock galaxy catalogs created via +semi-analytic techniques, tracers of local +galaxy density (i.e.~``environment'') measured on mock LSST +photometric samples will be compared to the underlying real-space density of galaxies +or host halo mass. In addition to testing existing density +measures, such as $N^{\rm th}$-nearest-neighbor distance and counts in +a fixed aperture, new measures will be explored that may be better +suited to LSST. For each measure, the impact of +increasing survey depth and photo-$z$ precision over the course of the +survey will be examined.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item With an improved understanding of the +strengths and weaknesses of different environment measures as applied +to LSST, this effort will yield code to measure local galaxy density +(likely in multiple ways) within the LSST dataset. +\item Creation of methods to generate galaxy environmental measures as Level 3 data products for use by the entire project. +\end{enumerate} +} +\end{task} + +\subsection{Enabling and Optimizing Measurements of Galaxy Clustering} +\tasktitle{Enabling and Optimizing Measurements of Galaxy Clustering} +\begin{task} +\label{task:clss:clustering} +\motivation{ +Contemporary galaxy surveys have +transformed the study of large-scale structure, enabling high +precision measurements of clustering statistics. The correlation +function provides a fundamental way to characterize the galaxy +distribution. The dependence of clustering on galaxy properties and +the evolution of clustering provide fundamental constraints on +theories of galaxy formation and evolution. Interpreting these +measurements provides crucial insight into the relation between +galaxies and dark matter halos. Understanding how galaxies relate to +the underlying dark matter is essential for optimally utilizing +the large-scale distribution of galaxies as a cosmological probe. +} +~\\ +\activities{ +Support work to define and characterize +the upcoming galaxy samples from LSST to enable clustering +measurements. Several distinct sets of information need to +be made available or be calculable from pipeline data. Such +requirements include a detailed understanding of any selection effects +impacting the observed galaxies, the angular and radial completeness +of the samples, and the detailed geometry of the survey (typically +provided in terms of random catalogs that cover the full survey area). +One aspect +to address is how best to handle the large data sets involved +(e.g.~the LSST ``gold'' galaxy sample will include about $4$~billion +galaxies over $18$,$000$~square degrees). Another issue is the development +of a +methodology to incorporate optimally the LSST photo-$z$ estimates with +the angular data to obtain ``2.5-dimensions'' for pristine clustering +measurements.\\ +~\\ +Further efforts will concern the development, testing, and optimization of +algorithms for measuring galaxy clustering using LSST data. +These algorithms will be tested on realistic LSST mock catalogs, which +will also later serve as a tool for obtaining error estimates on the +measurements. +This endeavor overlaps with DESC-LSS working group efforts, and +requires cooperation of the DESC-PhotoZ working group and the Galaxies +Theory and Mock Catalogs working group.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Guidance for LSST galaxy pipelines to include all the necessary +information for measurements of the correlation function and related +statistics to take place once LSST data is available. This deliverable +requires the engineering of ancillary products such as masks and maps of +completeness as a function of galaxy properties. +\item Development and refinement of techniques for measuring galaxy clustering of +large LSST galaxy samples. Together, these techniques will enable the +full potential of LSST data for combined studies of large-scale structure and +galaxy formation to be realized. +\end{enumerate} +} +\end{task} + + +\subsection{Enabling Cluster Science through Robust Photometry and Photometric Redshifts} +\tasktitle{Enabling Cluster Science through Robust Photometry and Photometric Redshifts} +\begin{task} +\label{task:clss:los} +\motivation{ +Lines-of-sight through the cores of galaxy clusters and +groups (hereafter "clusters") rank among the most challenging +observations in which to identify robustly distinct extragalactic +objects and to infer a reliable photometric redshift distribution + $p(z)$ from the available data. +Challenges that must be overcome include crowding of galaxies, a highly +non-uniform background principally caused by the diffuse intracluster +light, and the presence of numerous background galaxies including some +that are highly distorted gravitational arcs. Given that the LSST +data will be accumulated over numerous epochs, there is significant +potential for the detection of transients along these lines-of-sight. +All of these complicating issues will be relevant to LSST commissioning data, +Wide Fast Deep survey data, and the Deep Drilling Fields, and all will +affect the basic processes of source detection and photometry. Beyond +photometry, further fundamental issues that require solutions include +ensuring that photometric redshift algorithms are +provided with spectral templates appropriate for +faint cluster members and prior information about the presence +of a galaxy cluster along the line-of-sight. +Science goals affected by these issues include weak-lensing measurements of the +mass-concentration relation as a function of halo mass and redshift, +measuring the evolution of the galaxy luminosity function in clusters +and in particular the faint end slope, identifying star-forming galaxies +in clusters and their infall regions to probe the physics of quenching +of star formation, measuring the evolution of brightest cluster +galaxies, automated detection of strong-lensing clusters, and even +potential identification of strongly-lensed transients including +possible electromagnetic counterparts to gravitational wave sources. +} +~\\ +\activities{ +LSST will deliver the most information rich dataset ever in relation to +the masses and internal structures of clusters and their infall regions. +Moreover, the dataset can be enhanced significantly via the addition of +data at other wavelengths, including X-ray, millimeter, and +near-infrared. To take full advantage of this opportunity, the +fundamental issues of source detection, photometry, and photometric +redshift inference along these crowded, challenging lines-of-sight must +be solved. Relevant activities include testing the Level 2 +software pipeline on both simulated LSST observations of clusters and +existing data including deep +observations of known clusters (e.g. from LoCuSS, Weighing the Giants, +CCCP, CFHT-LS, HSC, etc.). These tests will examine the ability of +the Level 2 pipeline to deblend correctly these crowded lines-of-sight, +and determine whether the Level 2 algorithm will require modifications +or a Level 3 algorithm for clusters will be needed. +Further activities include collating, reviewing, and selecting +appropriate cluster-specific galaxy spectral templates for deployment in +photometric redshift codes. +Another critical activity is to develop photometric +redshift algorithms that account for the brightness and +extent of X-ray emission, the overdensity of galaxies as a function of +magnitude and color, any available spectroscopic redshifts, and the +amplitude and extent of any SZ decrement/increment. +Such algorithms will +likely adopt a Bayesian hierarchical modeling approach to forward model +the problem, and can be tested on simulated data based on numerical +simulations and existing datasets (e.g. from XXL, XCS, HSC, LoCuSS, DES, +and others). +~\\~\\ +This work links with efforts on deblending and +intracluster light, forward +modeling of cluster and groups, environmental measures, cluster +detection, auxiliary data, and work in the DESC Clusters Working Group +via the determination of $p(z)$ for background galaxies.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item An algorithm that produces accurately deblended photometry of +cluster cores at least to redshift $z = 1$ with LSST data and to higher +redshifts in combination with near-IR data. +\item Cluster-specific galaxy spectral templates for use by photometric +redshift codes, emphasizing samples drawn from spectroscopic surveys of +high-redshift clusters. +\item A new cluster-specific photometric redshift algorithm that can be +applied to a list of cluster detections based on LSST data, external +data, or combined LSST/external datasets. +\end{enumerate} +} +\end{task} + + + +\subsection{Enabling Cluster Physics Through Forward Modeling of LSST +Clusters and Groups} +\tasktitle{Enabling Cluster Physics Through Forward Modeling of LSST +Clusters and Groups} +\begin{task} +\label{task:clss:cluster_fm} +\motivation{ +Most of the interesting cluster and group physics from LSST and its +union with complementary surveys will be derived from studies that +explore the full range of halo mass relevant to groups and clusters +$M_{200}\simeq10^{13}-10^{15}M_\odot$ and to redshifts $z\gtrsim1$. +This mass and redshift range extends +beyond that used by cluster cosmologists (e.g., colleagues in DESC), +who typically restrict attention to objects with masses +$M_{200}>10^{14}M_\odot$ at $z<1$. +Extending the range probed will be very challenging from the point of +view of systematic biases. However, the requirement on controlling +systematic biases for cluster/group physics is an order of magnitude +less stringent than the nominal 1\% requirement for dark energy science. +Arguably, $\sim10\%$ control of systematic biases in weak-lensing +measurements of low redshift clusters ($\gtrsim2\times10^{14}M_\odot$) +has already been achieved +\citep{okabe2013a,applegate2014a,hoekstra2015a,okabe2016a}, giving +considerable grounds for optimism. +} +~\\ +\activities{ +Broadly, cluster-based constraints on dark energy will be +based on forward modeling the cluster population from a cosmological +model and a number of scaling relations between halo mass and observable +properties. The design of these algorithms and their selected +scaling relations will be predicated on deriving +the most reliable dark energy constraints, and not necessarily for +learning the +most cluster physics possible. For example, the +scaling relations will +be selected to have low scatter, and the internal +structure and halo concentration of clusters may be treated as nuisance +parameters despite their physical interest. +~\\~\\ +The main activity in this task will therefore be to develop a code to +forward model the combined LSST/multiwavelength dataset on a cluster +population at a level of detail that preserves the structure of +clusters and thus maximizes the available information about internal +cluster physics. +The model should connect cluster properties back to the halo mass function via the +weak-lensing constraints that will be available from the LSST data, assuming +a fixed cosmological model. +Requirements missing from cosmological modeling codes include (1) simultaneous fitting +of cluster scaling relations, density profile models to weak-shear +profiles, and the mass-concentration relation of groups and clusters, +and (2) simultaneous fitting of the weak-shear signal from clusters with +overtly astrophysical parameters of interest such as the star-formation +rate of clusters, and indicators of the merger history of clusters like +X-ray morphology. A public, multipurpose code would enable the +exploration of a broad range cluster science +interests with LSST and supporting data. Other important activities +will include testing the code on simulated light cone data, existing +datasets (e.g. XCS, SPT, XXL, LoCuSS, HSC, DES, and others), and LSST +commissioning data. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item A robust Bayesian forward modeling code to constrain +the physics of galaxies and hot gas in groups and clusters, tied +directly to the halo mass function via weak-lensing from LSST. +\item Detailed tests on simulated and existing datasets. +\item Early science from LSST commissioning data, depending on the choice of +commissioning fields. +\end{enumerate} +} +\end{task} +\end{tasklist} +} diff --git a/arxiv/ddf.tex b/arxiv/ddf.tex new file mode 100644 index 0000000..c34f021 --- /dev/null +++ b/arxiv/ddf.tex @@ -0,0 +1,113 @@ +\section{Deep Drilling Fields}\label{sec:tasks:ddf} + +{\justify +The LSST Deep Drilling Fields (DDF) will have a higher cadence and deeper observations than the Wide Fast Deep (WFD) survey. +Many of the details of the observing strategy have yet to be finalized, but four DDFs have been selected. +Whether to include any others will be part of a complex trade involving other special projects that depart from the WFD survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy all remain under study at the current time. +The tasks outlined in this section will help optimize the LSST DDF +observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy evolution science. +The specific task of calculating photometric redshifts in the LSST DDFs is addressed separately in Section \ref{task:photo_z:ddf}. + +\begin{tasklist}{DDF} + +\subsection{Coordinating Ancillary Observations} +\tasktitle{Coordinating Ancillary Observations} +\begin{task} +\label{task:ddf:ancillary_obs} +\motivation{ +Galaxy evolution science performed using LSST DDF data crucially requires supporting observations from other facilities. +While the LSST data uniquely provides deep and accurate photometry, good image quality, and time-series sampling, the amount of information in six bands of relatively broad optical imaging +remains quite limited. Estimates of photometric redshifts and stellar-population parameters (e.g., mass and star-formation rate) greatly improve with the addition of longer-wavelength data. +Combining these quantities with information on dust and gas from far-IR, millimeter, and radio observations allows one to build and test models that track the flow of gas in and out of galaxies. +Deep and dense spectroscopy provides precise redshifts, calibrates photometric redshifts, and measures important physical properties of galaxies. +Properly supported by this additional data, the LSST DDFs will become the most valuable areas of the sky for galaxy evolution science. +The central regions of the four fields already selected already enjoy multiwavelength coverage; +the main challenge is filling out the much larger area subtended by the LSST field of view. +} +~\\ +\activities{ +A major challenge in supporting the LSST DDFs is the huge investment of telescope time. +Providing supporting multiwavelength data sets requires +coordination across facilities and collaborations to make the most efficient use of telescope time. Current coordination occurs somewhat haphazardly, but there has not to date been a dedicated effort to organize potential stakeholders involved in developing a coherent plan. The LSST Science Collaborations can and should take the lead. +The SERVS program to observe the already-designated DDFs with Spitzer provides a good example of where coordination can prove fruitful \citep{mauduit2012a}, but substantial +further work remains. Activities include organizing workshops to discuss LSST DDF coordination, +and proposals for major surveys or even new instrumentation to provide supporting data. +If the proposals are successful, then they must be successfully executed with an eye toward integrating +with the future LSST data. These collective efforts will require additional work to enable DDF support through policies and strategic planning at major observatories. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Workshops on LSST DDF supporting observations. +\item Annually updated roadmap of supporting observations (conceived, planned, or executed). +\item Public Release of data from supporting observations. +\item Level 3 software to enable use of LSST data with supporting data. +\end{enumerate} +} +\end{task} + +\subsection{Observing Strategy and Cadence} +\tasktitle{Observing Strategy and Cadence} +\begin{task} +\label{task:ddf:cadence} +\motivation{ +The LSST DDF observing strategy will need to serve diverse needs. For galaxy evolution science, the time series aspect of the observation may prove less important than the depth, image quality, and mix of filters. +Non-LSST factors like the availability of supporting data from other facilities, or the timing of the availability of such data will influence the observing strategy optimization. +For example, for many science goals completing the observations of one DDF to the final 10-year depth in the first year could prove very beneficial. +Justifying this investment will require work, including the selection of a suitable DDF +and the identification of synergies with other LSST science areas (e.g., DESC, AGN, transients). +} +~\\ +\activities{ +The LSST observing strategy is optimized using the Operations Simulator (OpSim). The Project works with the community to develop both baseline observing strategies and figures of merit for comparing different strategies. The figures of merit are implemented programmatically via the Metrics Analysis Framework (MAF) so that they can be easily applied to any candidate LSST cadence. The LSST project has called on the Science Collaborations to develop these metrics to codify their science priorities. The major activity here is involvement in the optimization of the DDF strategy through participation in Cadence workshops, training on the MAF and OpSim, developing metrics and coding them in MAF, and proposing and helping to evaluate DDF cadences.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Figures of Merit via MAF for use by OpSim in evaluating DDF strategies. +\item Proposed observing strategies for DDFs with corresponding scientific rationale. +\item Proposing and/or helping to assess selection of additional DDFs. +\end{enumerate} +} +\end{task} + +\subsection{Data Processing} +\tasktitle{Data Processing} +\begin{task} +\label{task:ddf:data_processing} +\motivation{ +Getting the most out of the DDFs may require data processing beyond that required for the +LSST WFD Survey. A variety of issues will need consideration in trying to optimize the science output, +including different strategies for making co-adds, masking bright stars and ghosts, determining sky levels, treating scattered light, detecting and characterizing faint or low surface brightness features, deblending overlapping objects, or estimating photometric redshifts. Reprocessing the DDF data while utilizing +supporting observations may prove feasible. +While there exists a clear advantage to issue one ``official'' LSST-released catalog at Level 2, +defining such a catalog to support a very broad range of science remains challenging. +Generating high-quality Level 3 catalogs to advance extragalactic research that include external +data will require time and effort from the LSST Science Collaborations. +} +~\\ +\activities{ +Identify the most important DDF-specific science drivers and any processing requirements distinct from the WFD survey. Coordinate with the Project and Science Collaborations to provide a coherent set of specifications and priorities for data processing.\\ +~\\ +Develop the machinery to test and validate the data-processing on the DDFs (via pure simulations and artificial-source injection). This activity may stress the inputs to the LSST image simulator, requiring more realistic inputs for low-mass galaxies, galaxy morphologies, and low surface brightness features. Use of the supporting data sets in Level 2 or 3 processing requires careful thought. For example, +pixel-level information from either Euclid or WFIRST +may improve source identification and photometry. +However, these ancillary data sets will not be available for all the DDFs and does not currently +reflect the baseline observing plan for any of the projects, and the timing of the various projects and associated data rights create their own set of challenges. The Science Collaborations need to work with the various projects to identify a clear path forward.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Science drivers and input into to the development of Level 2 processing for the DDFs. +\item Specifications for galaxy evolution-oriented Level 3 DDF processing. +\item Specifications for data processing using supporting data from other facilities. +\item Data simulations tailored to the DDFs. +\item Level 3 data processing code, or augmentations to the LSST Level 2 pipeline, to fully leverage the depth of the DDFs. +\end{enumerate} +} +\end{task} + +\end{tasklist} + +} diff --git a/arxiv/galaxies.tex b/arxiv/galaxies.tex new file mode 100644 index 0000000..e83f8b1 --- /dev/null +++ b/arxiv/galaxies.tex @@ -0,0 +1,428 @@ +% LSST Extragalactic Roadmap +% Chapter: task_lists +% Section: galaxies + +\section{Galaxy Evolution Task Lists}\label{sec:tasks:gal:intro} +{\justify +The LSST Project optimized the observatory and data management design +to execute successfully and efficiently the core LSST science mission. +For measurements +of dark energy, that optimization generally means treating galaxies as ``tracer particles'' -- + using statistical measures of ellipticity and position to provide statistical +constraints on large-scale structure and cosmic geometry. While many of the +DESC tasks relate directly to studying galaxy evolution, they remain +incomplete. In particular, studies of galaxy evolution require more attention to +optimizing multi-wavelength supporting data, obtaining different kinds of spectroscopy, +performing different +kinds of simulations and other theoretical support, and a greater attention to +the detection +and characterization of low surface brightness features or unusual morphologies. + +The task list presented here highlights the preparatory research needed +before LSST first light. +Tasks of primary importance and particular urgency include those that might influence the detailed survey +design or the algorithms used in the LSST Software Stack to construct catalogs. +Other critical tasks remain reasonably independent of the +LSST survey design and data pipeline optimization, but will help ensure good support for +LSST galaxy studies. + +\begin{tasklist}{G} + +\subsection{Techniques for Finding Low Surface Brightness Features or Galaxies} +\tasktitle{Techniques for Finding Low Surface Brightness Features or Galaxies} +% Tidal streams +% Intracluster diffuse light +\begin{task} +\label{task:gal:lsb} +\motivation{ +Important scientific benefits of the LSST dataset +relative to prior large-area surveys include its ability to detect +low surface brightness (LSB) features associated with galaxies. +This ability includes the identification of tidal streams and +other features associated with past and ongoing mergers, intra-cluster and +intra-group light, and relatively nearby, extended LSB galaxies. +Prior to LSST, typical studies of the LSB universe focused +on relatively small samples, often selected by criteria that prove difficult to quantify +or reproduce in theoretical models. Measurements of the LSB features themselves +can challenge pipelines and subsequent analysis, +and often require both hand-tuning and interactive scientific judgment. This manual +attention serves to help quantify accurately what we observe, but such +interacting tuning of the measurements does not scale to the LSST dataset and +can prove difficult to apply to theoretical models. +For LSST, we must automate the detection and characterization of LSB features, +at least to the point where we can select samples +for further study via database queries and quantify the completeness or +other statistical properties of +those retrieved samples. +} +~\\ +\activities{ +Several crucial activities include: (1) simulating realistic LSB features, (2) +using the simulations to optimize detection and measurement, (3) informing LSST +Level 2 processing and observing strategies about the needs of LSB science, +and (4) developing a strategy for finding and measuring LSB features through +some combination of Level 2 measurements, database queries, and Level 3 processing.\\ +~\\ +The insertion of realistic LSB features into LSST simulated images will provide +``data challenges'' to test methods for their extraction and measurement, allowing +for the exploration of different techniques or algorithms for performing LSB +feature detection and characterization. +Because the LSB objects sparsely populate the sky, +making realistic LSST sky images will probably prove inefficient. +More targeted simulations with a higher density of LSB object will better +enable the efficient exploration of LSB feature detection and analysis. +Simulated observations must realistically treat scattered light, particularly +scattering from bright stars that may or may not fall in the actual field of +view of the telescope. Scattering from bright stars will likely contribute the +primary source of contamination when searching for extended LSB features. +Ideally, the LSST scattered-light model, +tuned by repeated observations, will perform sufficiently well and enable the removal +or flagging of these contaminants at Level 2. +Defining the associated performance metrics for +based on analysis of simulation represents an important activity that needs early work to +help inform LSST development. Including Galactic cirrus in the simulations is important +for very large-scale LSB features. Including a cirrus model as part of the LSST background +estimation is worth considering, but the science benefit gained from the +additional effort remains unclear.\\ +~\\ +Because the LSST source extraction is primarily +optimized for finding faint, barely-resolved galaxies, +simultaneously finding large LSB structures and cataloging them as +one entity in the LSST database may pose challenges. +For very large structures, analysis of the LSST ``sky background'' +map might constitute the most productive approach. +We need to work with the LSST Project +to make sure the Software Stack stores the background map in a useful form, and that background +measurements from repeated observations can be combined to separate the fluctuating +foreground and scattered light from the astrophysically interesting signal owing to extended +LSB structures. +Then, we need strategies for measuring these background maps, characterizing +structures, and developing value-added catalogs to supplement the Level 2 database.\\ +~\\ +For smaller structures, the database likely will contain pieces +of the structure, either as portions of a hierarchical +family of deblended objects or as separate catalog entries. Therefore, we need to +develop strategies for querying the database to find such structures and either extract +the appropriate data for customized processing, or develop ways to put back together +the separate entries in the database. A possible value-added catalog, for example, from +the Galaxies Science Collaboration might include an extra set of fields for the database to indicate +which separate objects likely probably originate from the same physical entity. These additional fields would +remain sparsely populated in the first year or two of LSST, but by the end of the survey +the relational connections between deblended objects may prove a +useful resource for a wide variety of investigations. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Creations of realistic inputs of LSB galaxies or LSB features for the LSST image simulations. +\item Development of algorithms for finding and measuring LSB features. +\item Input to the Project on scattered-light mitigation and modeling strategies. +\item Input to the Project on photometric and morphological parameters to measure/store at Level 2. +\item Identification of query strategies and sample queries for finding LSB structures. +\item Engineering of a baseline concept for a value-added database of LSB structures. +\end{enumerate} +} +\end{task} + +\subsection{Techniques for Identifying and Deblending Overlapping Galaxies} +\tasktitle{Techniques for Identifying and Deblending Overlapping Galaxies} +\begin{task} +\label{task:gal:deblending} +\motivation{ +Level 2 data products will provide the starting point +for galaxy evolution science with LSST. In the LSST nomenclature, objects +represent astrophysical entities (stars, galaxies, quasars, etc.), while +sources represent their single-epoch observations. +The LSST Software Stack will generate the master list of objects in Level 2 +by associating +and deblending the list of single-epoch source detections and the +lists of sources detected on co-adds. The exact strategies for +performing this task still remain under active development by the LSST Project, and +engagement with the science community will prove essential. While each +data release will provide unique object IDs, if the first few +generations of catalogs limit the science performed through data base +queries the consequences may impede early LSST science.\\ +~\\ +For galaxies science, the issue of deblending holds critical importance. +For example, searches for high-redshift galaxies via color selection +or photometric redshifts involve model or template spectra that make +the prior assumption that each analyzed object does not consist of a +blend of two objects at two different redshifts. +Therefore, to get a reliable estimate of the evolution of classes of galaxies +over redshift we need to (a) create reasonably clean initial catalogs +and (b) model the effects of blending on the sample selection +and derivation of redshift and other parameters. These issues critically +affect not just galaxy evolution science, but also lensing and large-scale +structure studies. Another example involves the measurement +of galaxy morphologies, where the effects of blending and confusion +may dominate measurement uncertainties.\\ +~\\ +For the Level 2 catalogs, the planned approach involves using the +Software Stack to deblend sources hierarchically and then +maintain this hierarchy in the catalog. +Scientifically important decisions still remain about whether +and how to use color information in the deblending, and how to divide +the flux between overlapping components. Even if the Project performs +the development work, engagement with the community can generate important +tests and figures of merit to optimize the science return. +} +~\\ +\activities{ +Preparations for LSST in this area involve working both with simulations +and real data. The current LSST image simulations already utilize realistic source densities, +redshift distributions, sizes, and color distributions. However, the +input galaxies do not display realistic morphologies. At least some simulations +with realistic morphologies are needed, especially for the Deep Drilling Fields. +Inputs should come from hydrodynamical simulations, +{\it Hubble} images, and images from precursor surveys such as CFHTLS, DES, and Hyper Suprime-Cam. +The Science Collaborations should help provide and vet inputs. \\ +~\\ +More challenging activities involve developing techniques and algorithms to improve the +deblending. When two galaxies at different redshifts overlap, using observations +from all the LSST filters and perhaps even EUCLID and WFIRST might +help to disentangle them. Some attempts over the past few years have +incorporated color gradient information into the deblending algorithm, but this approach needs +much more attention for developing and testing algorithms, and for +deciding on figures-of-merit for their performance. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Production of realistic galaxy image inputs to the LSST ImSim team. +\item Development of tests and figures of merit to quantify the effects on several science objectives; +\item Assessment of the current baseline plan for Level 2 deblending and for parameter estimation for blended objects. +\item Development of prototype implementations of deblending algorithms that take advantage of the LSST color information. +\end{enumerate} +} +\end{task} + +\subsection{Optimizing Galaxy Morphology Measurements} +\tasktitle{Optimizing Galaxy Morphology Measurements} +% techniques for identifying mergers +% Bayesian techniques for inference from large data sets +% Merging human classification and machine learning +\begin{task} +\label{task:gal:morphology} +\motivation{ +Morphology encodes key signatures of the formation histories of galaxies, and measurements of galaxy morphology +provide an important tool for constraining models of galaxy evolution. +While simple measures of galaxy ellipticity and position +angles may be sufficient for the dark energy science goals, more sophisticated measurements of morphology are needed for galaxy-evolution science. While the ``multifit'' approach of fitting simple parametric models to galaxy profiles is useful to zeroth order, this approach may be insufficient for the detailed morphological information +required for much of the galaxy science that is planned using LSST.\\ +~\\ +For well-resolved galaxies the baseline requirement is to have separate measures of bulge and disk, spiral arm structure, measures of concentration, asymmetry, and clumpiness. These +properties ought to be measured as part of the Level 2 processing, to enable database queries to extract subclasses of galaxies. Both parametric and non-parametric measures are desirable. While Level 3 processing methods will be +developed to further optimize galaxy measurements, +the Level 2 products should supply enough information to select reasonable subsets of galaxies.\\ +~\\ +More importantly, while the traditional parameterizations of morphology described above will be useful, it is essential that new, more powerful methods of measuring galaxy morphology are developed and implemented, in order to leverage the exquisite volume and depth of LSST data. In this regard fast, +machine-learning techniques \citep[e.g.,][Hausen \& Robertson, in prep]{hocking2015a} that can efficiently separate LSST galaxy populations into different morphological classes are particularly relevant and powerful. +} +~\\ +\activities{The preparation work will focus on defining morphological parameters and developing machine-learning algorithms to enable users to easily query galaxy morphologies from the LSST database. +Two aspects of LSST data make this a significant research project: the fact that LSST provides multi-band data with a high degree of uniformity, and the fact that the individual observations will have varying point-spread functions. The former offers the opportunity to use much more information than has been generally possible. The latter means that it will take some effort to optimize and calibrate the traditional non-parametric measures of morphology (e.g. the CAS, GINI and M20 parameters), develop new LSST-optimized parameters, and tune machine-learning algorithms to operate on this type of data. +\\ +Given the very large data set expected from LSST, which will change on short timescales in terms of depth, morphological parameters (e.g. CAS) will likely need to be calibrated on realistic data from hydrodynamical simulations in cosmological volumes, possibly augmented by training sets classified by humans. Similarly, machine-learning algorithms will have to be developed and implemented using a mixture of realistic simulations and precursor datasets, such as the Hyper Suprime-Cam Survey. A series of ``classification challenges'' prior to the LSST survey could help to refine these techniques. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Realistic galaxy image inputs from hydrodynamical simulations and precursor datasets for classification tests. +\item Human classification of image subsets for calibration of morphological parameters. +\item Machine-learning algorithms that will provide fast morphological classification of LSST datasets, developed using and implemented on precursor datasets such as the Hyper Suprime-Cam Survey or the Dark Energy Survey. +\end{enumerate} +} +\end{task} + + +\subsection{Galaxy Structural Parameters} +\tasktitle{Galaxy Structural Parameters} + +\begin{task} +\label{task:gal:struc_param} +\motivation{ +The image quality provided by the LSST camera (0.2"/pixel) and the wide field coverage (9.6deg$^2$) over 18,000 deg$^2$ in optical and NIR bands promise to provide unique data for studying the evolution of the internal galaxy structure. +The full depth of the Wide Fast Deep survey (r $\sim$27.5 coadded) +will allow for the identification dwarf galaxies at $z\sim0.5$, and up to $M_*+2$ galaxies in clusters and field at $z\sim1.5$, and reach deep enough to study the structural parameters (size, Sersic index, ellipticity etc.) of $M_*$ galaxies at $z\sim1.2$ (for seeing$<0.5$"). The LSST data will allow for size, Sersic index, and bulge-to-disk ratio for over a billion galaxies to be correlated with mass, color, and other intrinsic properties at different epochs and thereby clarify the mechanisms that drive the galaxy assembly and transformation. +} +~\\ +\activities{Preparatory work will consist of testing parametric methods for seeing-convolved 2D fitting of the galaxy light distribution on precursor surveys (e.g., HSC or KiDS) and on simulated LSST images, with the aim of providing viable tools for automatic image masking, catalogue extraction, source classification, and 2D galaxy fitting +in Level 3 datasets. +This task will involve optimizing tool performance to guarantee meet time metrics (e.g., processing 100 million LSST galaxies in all bands on a single week). The surface brightness profile of galaxies in different bands will finally generate a catalog of all relevant structural parameters via Level 3 products. +} +~\\ +\deliverables{%From the activities described above we expect to provide the following deliverables: +~ +\begin{enumerate} +\item Benchmarks for existing and newly developed tools for galaxy surface photometry. +\item Automatic masks for star halos, spikes, and reflections, and related procedures for Level 3 analyses. +\item Tools to catalog structural parameters in different bands. +\item Machine learning algorithms for the identification of faint substructures in model subtracted images (e.g. streams, merging, rings, strong lensing arcs, etc.). +\end{enumerate} +} +\end{task} + +\bigskip +\subsection{Optimizing Galaxy Mass Profile Measurements} +\tasktitle{Optimizing Galaxy Mass Profile Measurements} +% foreground lens galaxy sample selection +% completeness +% shear simulations +% galaxy-mass correlation function +% sample cuts: type, environment, color, redshift +% correlations of mass profile with optical properties +\begin{task} +\label{task:gal:mass} +\motivation{Galaxies form and evolve dynamically via the gravitational influence +of the underlying dark matter structure. This non-baryonic dark mass is intimately +involved in the evolution of the baryonic component that ultimately generates the +stellar component visible in the optical. LSST can uniquely probe both of these +tracers for hundreds of millions of galaxies over a range of look-back time. +This sample provides an opportunity to probe the detailed relation between baryonic and dark +matter structure +evolution. Such studies have been attempted before in a limited way using LSST +precursor surveys. Using 300,000 lens galaxies in the Deep Lens Survey, \citep{choi2012a} +studied the mass profile of galaxies in three luminosity bins out to several Mpc. Using +a similar number of lens galaxies in the COSMOS ACS data, \citet{leauthaud2012a} derived +constraints on the evolution of the stellar-to-dark matter connection in the context of halo models. +LSST will provide a billion lens galaxies with accurate photometric redshifts, revolutionizing +this measurement. +} +~\\ +\activities{ +An important issue to address is how far down the galaxy mass function can one detect +the mass profile in selected large samples of galaxies. One must start +with a model of the mass distribution in galaxies, which will +involve use of existing galaxy formation simulations and resulting analytic models. +Foreground lens galaxy sample selection must be explored, +weak lens shear simulations of LSST observing over +a large area (1000 deg$^2$) containing a large sample of lens galaxies performed, +stacked simulations of +the galaxy-mass correlation function out to significant radii for mass environment tests (3-10 Mpc) +computed, +sample cuts on morphological surface brightness type vs. redshift engineered, and an assessment of +signal-to-noise (SNR) for +dwarf galaxy samples and sample completeness determined. +The LSST main survey will +have hundreds of thousands of dwarf galaxies in a range of redshift $z = 0.2 - 0.6$ which act as lenses. +The shear SNR is high -- a simulation of just 20 LSST visits to a single $z=0.5$ galaxy +with total $10^{11} M_\odot$ virial mass yields a shear SNR$\approx10$ out to several Mpc in projected radius. +Stacking a million dwarf galaxies should thus yield high precision mass profiles, even when cut on +parameters such as mass environment, surface brightness type, stellar mass, and redshift. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities +%described above include the following: +~ +\begin{enumerate} +\item A selection for a set of template galaxies for use as lenses in ray-trace simulation, +using a set of simulated models of galaxies at various stages in development. +\item Galaxy - mass shear simulations over at least 1000 square degrees, using the +latest LSST OpSim run and full end-to-end weak lens ray tracing, including PSF +and detector effects, and incorporating a representative set of galaxies over a range of masses. +\item Computation of galaxy-mass correlation functions using these stacked LSST shear +simulations, for sets of populations of galaxies over a wide mass range. +\item Assessment SNR vs galaxy mass, and the ability to correlate mass profile with +optical surface brightness and type over a range of redshift. +\end{enumerate} +} +\end{task} + +\subsection{Optimizing Galaxy Photometry} +\tasktitle{Optimizing Galaxy Photometry} +% background subtraction +% optimal co-adds +% best flux estimator +% image quality metrics +% forced photometry with separate central point source (important for AGN) +% Using high-resolution priors where available +\begin{task} +\label{task:gal:photometry} +\motivation{ +Systematic uncertainties will dominate over random uncertainties for many +research questions addressed with LSST. The most basic measurement +of a galaxy is its flux in each band, but flux is a remarkably subtle measurement +for a variety of reasons as galaxies do not have well-defined edges, their shapes +vary, they have close neighbors, they cluster together, and lensing affects both +their brightness and clustering. These factors all affect photometry in systematic +ways, potentially creating spurious correlations that can obscure or masquerade as +astrophysical effects. For example, efforts to measure the effect of neighbors +on galaxy star formation rates can be erroneous if the presence of a neighbor +affects the basic photometry. Measurements of galaxy magnification or measurements +of intergalactic dust can be similarly affected by systematic photometric biases. +It is thus important to hone the photometry techniques prior to the survey to +minimize and characterize the biases. Furthermore, there are science topics that +require not just photometry for the entire galaxy, but well-characterized photometry +for sub-components, such as a central point-source or a central bulge. +} +~\\ +\activities{ +The core photometry algorithms will end up being applied in Level 2 processing, +so it is important that photometry be vetted for a large number of potential +science projects before finalizing the software. Issues include the following. +(1) Background estimation, which, for example, can greatly affect the photometry +for galaxies in clusters or dwarfs around giant galaxies. (2) Quantifying the +biases of different flux estimators vs. (for example) distances to and fluxes +of their neighbors. (3) Defining optimal strategies to deal with the varying +image quality. (4) Defining a strategy for forced photometry of a central point +source. For time-varying point-sources, the image subtractions will give a +precise center, but will only measure the AC component of the flux. Additional +measurements will be needed to give the static component. (5) Making use +of high-resolution priors from either Euclid or WFIRST, when available. +Because photometry is so central to much of LSST science, there will need to +be close collaboration between the LSST Project and the community. +} +~\\ +\deliverables{ +%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Development of metrics for various science cases to help evaluate the Level 2 photometry. +\item Realistic inputs for difficult photometry cases (e.g. close neighbors, clusters of galaxies, AGN in galaxies of various morphologies). +\item Deliverables over the longer term include developing optimal techniques for forced photometry using priors from space-based missions. +\end{enumerate} +} +\end{task} + +\subsection{Optimizing Measurements of Stellar Population Parameters} +\tasktitle{Optimizing Measurements of Stellar Population Parameters} +% Strategies for dealing with strong covariance of parameter estmates +\begin{task} +\label{task:gal:stellarpops} +\motivation{ +The colors of galaxies carry information about their star formation histories, +each interval of redshift being a snapshot of star formation up until that time. +Unfortunately, estimates of star formation rates and histories +for a single galaxy based on only the LSST bands will be highly uncertain, +owing largely to degeneracies between age, dust extinction, and metallicity. +Strategies for overcoming the degeneracies include hierarchical modeling -- using +ensembles of galaxies to constrain the hyper-parameters that govern +the star formation histories of sets of galaxies rather than individuals, +and using ancillary data from other wavelengths. +} +~\\ +\activities{ +Activities in this area include developing scalable techniques for +hierarchical Bayesian inference on very large data sets. These can be +tested on semi-analytical or hydrodynamical models, where the answer is known +even if they do not correctly represent galaxy evolution. The models should +also be analyzed to find simple analytical expressions for star formation +histories, chemical evolution, and the evolution and behavior of dust to +make the Bayesian inference practical. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Development and refinement of techniques for constraining star formation histories of large ensembles of galaxies. +\item Model inputs to guide in developing these techniques. +\item Refinement of the science requirements for ancillary multi-wavelength data to support LSST. +\end{enumerate} +} +\end{task} + +\end{tasklist} +} diff --git a/arxiv/high_z.tex b/arxiv/high_z.tex new file mode 100644 index 0000000..328aee2 --- /dev/null +++ b/arxiv/high_z.tex @@ -0,0 +1,102 @@ +\section{High-Redshift Galaxies}\label{sec:tasks:high_z} + +{\justify +Observations of distant galaxies provide critical information +about the efficiency of the galaxy formation process, the end +of the reionization era, the early enrichment of the intergalactic +medium, and the initial conditions for the formation of modern +galaxies at later times. Through its wide area and sensitivity +in $zy$, LSST will probe galaxies out to $z\sim7$ and +yet further in conjunction with future wide-area infrared surveys. +The following science tasks address outstanding preparatory work +for maximizing high-redshift science with LSST. + +\begin{tasklist}{HZ} + +\subsection{Optimizing Galaxy Photometry for High-Redshift Sources} +\tasktitle{Optimizing Galaxy Photometry for High-Redshift Sources} +\begin{task} +\label{task:high_z:photometry} +\motivation{ +The identification and study of high-redshift galaxies with LSST hinges on reliable, accurate and optimal measurements of the galaxy flux in all LSST passbands. +Galaxies at redshifts above $z\sim7$ will only be detected in the LSST $y$-band and will be non-detections or ``drop-outs'' in the other LSST filters. +Galaxies at redshifts $z>8$ will not be detected at all in the LSST filters, +but combining LSST with infrared surveys such as Euclid and WFIRST would enable the identification +of this population. +Robust flux measurements or limits for the undetected high-redshift galaxies in the blue LSST filters will prove particularly important, as this information enables efficient +high-redshift galaxy selection. +The highest redshift searches will LSST will necessarily require combining with space-based +infrared surveys like Euclid and WFIRST. +Since Euclid and WFIRST will provide data with very different spatial resolutions and point spread functions (PSFs) compared to LSST, algorithms also need to be devised to provide homogeneous flux measurements for sources across the different surveys. +It remains unclear whether the current LSST Level 2 data will meet all the requirements for identifying and characterizing high-redshift galaxy populations, +motivating an investigation before the start of LSST operations. +} +~\\ +\activities{ +First, the potential need for Level 3 data products beyond the baseline LSST Level 2 catalog +requires clarification. Photometric catalogues produced using the reddest LSST (e.g. $z$- or $y$-band) images as the detection image will prove critical for high-redshift science as high-redshift galaxies will not be detected in the bluer bands. Similarly, negative fluxes for undetected galaxies together with their corresponding errorbars provide useful input into spectral energy distribution (SED) fitting codes for high-redshift galaxy selection. Coordinating with the LSST Project to ensure +the application of forced photometry in Level 2 in a manner appropriate for high-redshift galaxy +selection may be sufficient, or Level 3 data products may be required.\\ +~\\ +Second, the determination of a suitable approach to combining LSST data with infrared data from Euclid/WFIRST for high-redshift galaxy selection will be required, including optimal measures of an optical-IR color for sources from these combined datasets. +Sources resolved in Euclid or WFIRST data could be blended in LSST, and may therefore +require deblending using the higher resolution IR data as a prior before reliable flux and +color measurements can be made. The engineering of this combined analysis likely will require +Level 3 efforts, and tests using existing datasets (e.g., Dark Energy Survey and Hubble +Space Telescope data) may already commence.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Clarification of LSST Level 2 data suitability for high-redshift science, and an identification of any Level 3 needs. +\item Development of Level 3 tools to produce optimal combined photometry from ground and space-based surveys, and the testing of these tools on existing datasets. +\end{enumerate} +} +\end{task} + +\subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} +\tasktitle{High-Redshift Galaxies and Interlopers in LSST Simulations} +\begin{task} +\label{task:high_z:interlopers} +\motivation{ +Before the start of LSST operations, the testing of selection methods for high-redshift +galaxies on high-fidelity simulations will provide essential validation of the utility of +LSST data for studying distant galaxy populations. +Given its wide-field coverage, LSST will uniquely uncover large samples of the most luminous and potentially massive high-redshift galaxies at the Epoch of Reionization \citep{robertson2007a}. +The most significant obstacle to selecting clean samples of such sources from the photometric data +is the presence of significant populations of interlopers, such as +cool brown dwarfs in our own Milky Way and low-redshift, dusty and/or red galaxies. +These objects can mimic the colors of high-redshift sources and therefore +prove difficult to distinguish. +This issue is particularly a problem for the highest redshift objects detected by LSST, which, unless data at redder wavelengths is available (such as near-infrared imaging from VISTA/Euclid/WFIRST, and/or mid-infrared imaging from Spitzer/WISE) will be only detected in one or two red-optical filters. +Using the LSST simulations, one wants to devise the most effective way of separating these different populations by utilizing both photometric and morphological information for the sources. +Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA, +one expects LSST images to spatially resolve at least some of the most luminous $z > 6$ galaxies \citep{willott2013a, bowler2017a}. +For fainter high-redshift galaxies however, a morphological distinction between faint ultra-cool brown dwarfs may not be possible, and further information such as near-infrared colors or proper motions will be required for identification. +} +~\\ +\activities{ +Liaise with the LSST Project simulations working group to ensure that high-redshift galaxies have been incorporated into the simulations with a representative set of physical properties (e.g., star formation histories, UV-slopes, emission line equivalent widths, dust extinction, and +metallicity). Ensure that high-redshift galaxies have the correct number density and size distribution in the simulations, allowing for investigations to characterize +how effectively morphology can separate high-redshift galaxies from low-redshift interlopers. +The high-redshift quasar population should also be included, as these have comparable number densities to the brightest galaxies at these redshifts and are typically indistinguishable with broad-band photometry only. +Incorporate interloper populations into the simulations with the correct number densities and colors, including cool Milky Way stars +(e.g., M, L and T-brown dwarfs) as well as populations of very red, massive, +and/or dusty galaxies at lower redshifts of $z\sim2$. +Determine the degree to which LSST selection of high-redshift galaxies effectively requires +color information from infrared filters provided by external surveys +(i.e., Euclid or WFIRST). + } + ~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Incorporation of high-$z$ galaxies and quasars into LSST simulations with a realistic and representative set of properties. +\item Incorporation pf cool Milky Way brown dwarfs into LSST simulations. +\item Predictions of the likely number density of brown dwarfs over the different DDFs. +\item Extension of simulations to other datasets beyond LSST (e.g., Euclid and WFIRST filters). +\end{enumerate} +} +\end{task} +\end{tasklist} +} diff --git a/arxiv/introduction.tex b/arxiv/introduction.tex new file mode 100644 index 0000000..d5ee9ec --- /dev/null +++ b/arxiv/introduction.tex @@ -0,0 +1,76 @@ +% LSST Extragalactic Roadmap +% Chapter: Introduction +% First draft by + +\chapter[Introduction]{Introduction} +\label{ch:intro} + +{\justify +The Large Synoptic Survey Telescope (LSST) is a wide-field, ground-based +observatory designed to image a substantial fraction of the sky in six optical +bands every few nights. +The observatory will operate for at least a decade, allowing +stacked images to detect galaxies to redshifts well beyond unity. LSST and +its Wide Fast Deep and Deep Drilling Fields surveys will meet +the requirements of a broad range of science goals in astronomy, astrophysics and cosmology +\citep{ivezic2008a}. +The LSST ranked first among large ground-based initiatives in the +2010 National Academy of Sciences decadal survey in astronomy and astrophysics \citep{nrc2010a}, +and will begin survey operations early in the next decade. +This document, the {\it LSST Galaxies Science Roadmap}, outlines critical preparatory research efforts needed +to leverage fully the power of LSST for extragalactic science. + +In 2008, eleven separate quasi-independent science collaborations were formed to +focus on a broad range of topics in astronomy and cosmology that the LSST could +address. Members of these collaborations have proven instrumental in helping to +develop the science case for LSST (encapsulated in the LSST Science Book; +\citealt{LSSTSciBook}), +refine the concepts for the survey and for the data processing, and educate +other scientists and the public about the promise of this unique observatory. + +The Dark Energy Science Collaboration (DESC) has taken the +next logical step beyond the Science Book. They identified they most critical +challenges the community will need to overcome +to realize the potential of LSST for +measuring the nature and effects of dark energy. The +DESC looked at five complementary +techniques for tackling dark energy, and outlined high-priority tasks for their +Science Collaboration during construction. The DESC designated sixteen +new and existing working +groups to coordinate the work. The DESC documented these efforts +in a 133-page white paper \citep{LSSTDESC}. The DESC white +paper provides a guide for investigators looking for ways to contribute to the +overall DESC preparatory science effort, +indicates clearly the importance of the advance work, and +connects individual research projects together into a broader +enterprise to enable dark energy science with LSST. + +Following the lead of DESC several other LSST community organizations, +including the AGN, Milky Way and Local Volume, and Solar System Science +Collaborations, +started to develop Roadmaps to outline critical preparatory tasks in +their science domains. +This document, led by members of the LSST Galaxies Science Collaboration, +acts as a Roadmap for extragalactic science covering +galaxy formation and evolution writ large, the influence of dark matter structure +formation on the properties of galaxy populations, and the impact of supermassive +black holes on their host galaxies. +This Roadmap identifies the major high-level +science themes of these investigations, outlines how complementary techniques +will contribute, and identifies areas where advance work will prove essential. For this +preparatory work, the {\it LSST Galaxies Science Roadmap} emphasizes areas that are not adequately +covered in the DESC Roadmap. + +Chapter \ref{ch:science_background} gives a brief summary of the LSST galaxies science background. +Many of the themes and projects are already set out in the LSST Science Book, +which provides more details for many of the science investigations. +Chapter \ref{ch:task_lists} presents preparatory science tasks for +extragalactic science with LSST, organized by science topic. +Cross-references between complementary tasks in different science topics are +noted throughout the document. +The science task list content assumes that the work plan of the DESC will be executed +and that the resulting software and other data products resulting from the DESC +efforts will be made available to the other science collaborations. +} +\let\cleardoublepage\clearpage + diff --git a/arxiv/journal_macros.tex b/arxiv/journal_macros.tex new file mode 100644 index 0000000..73faeb0 --- /dev/null +++ b/arxiv/journal_macros.tex @@ -0,0 +1,105 @@ +% +% These Macros are taken from the AAS TeX macro package version 5.2 +% and are compatible with the macros in the A&A document class +% version 7.0 +% Include this file in your LaTeX source only if you are not using +% the AAS TeX macro package or the A&A document class and need to +% resolve the macro definitions in the TeX/BibTeX entries returned by +% the ADS abstract service. +% +% If you plan not to use this file to resolve the journal macros +% rather than the whole AAS TeX macro package, you should save the +% file as ``aas_macros.sty'' and then include it in your LaTeX paper +% by using a construct such as: +% \documentstyle[11pt,aas_macros]{article} +% +% For more information on the AASTeX and A&A packages, please see: +% http://journals.aas.org/authors/aastex.html +% ftp://ftp.edpsciences.org/pub/aa/readme.html +% For more information about ADS abstract server, please see: +% http://adsabs.harvard.edu/ads_abstracts.html +% + +% Abbreviations for journals. The object here is to provide authors +% with convenient shorthands for the most "popular" (often-cited) +% journals; the author can use these markup tags without being concerned +% about the exact form of the journal abbreviation, or its formatting. +% It is up to the keeper of the macros to make sure the macros expand +% to the proper text. If macro package writers agree to all use the +% same TeX command name, authors only have to remember one thing, and +% the style file will take care of editorial preferences. This also +% applies when a single journal decides to revamp its abbreviating +% scheme, as happened with the ApJ (Abt 1991). + +\def\refj@jnl#1{{\rm#1}} + +\def\aj{\refj@jnl{AJ}} % Astronomical Journal +\def\actaa{\refj@jnl{Acta Astron.}} % Acta Astronomica +\def\araa{\refj@jnl{ARA\&A}} % Annual Review of Astron and Astrophys +\def\apj{\refj@jnl{ApJ}} % Astrophysical Journal +\def\apjl{\refj@jnl{ApJ}} % Astrophysical Journal, Letters +\def\apjs{\refj@jnl{ApJS}} % Astrophysical Journal, Supplement +\def\ao{\refj@jnl{Appl.~Opt.}} % Applied Optics +\def\apss{\refj@jnl{Ap\&SS}} % Astrophysics and Space Science +\def\aap{\refj@jnl{A\&A}} % Astronomy and Astrophysics +\def\aapr{\refj@jnl{A\&A~Rev.}} % Astronomy and Astrophysics Reviews +\def\aaps{\refj@jnl{A\&AS}} % Astronomy and Astrophysics, Supplement +\def\azh{\refj@jnl{AZh}} % Astronomicheskii Zhurnal +\def\baas{\refj@jnl{BAAS}} % Bulletin of the AAS +\def\bac{\refj@jnl{Bull. astr. Inst. Czechosl.}} + % Bulletin of the Astronomical Institutes of Czechoslovakia +\def\caa{\refj@jnl{Chinese Astron. Astrophys.}} + % Chinese Astronomy and Astrophysics +\def\cjaa{\refj@jnl{Chinese J. Astron. Astrophys.}} + % Chinese Journal of Astronomy and Astrophysics +\def\icarus{\refj@jnl{Icarus}} % Icarus +\def\jcap{\refj@jnl{J. Cosmology Astropart. Phys.}} + % Journal of Cosmology and Astroparticle Physics +\def\jrasc{\refj@jnl{JRASC}} % Journal of the RAS of Canada +\def\memras{\refj@jnl{MmRAS}} % Memoirs of the RAS +\def\mnras{\refj@jnl{MNRAS}} % Monthly Notices of the RAS +\def\na{\refj@jnl{New A}} % New Astronomy +\def\nar{\refj@jnl{New A Rev.}} % New Astronomy Review +\def\pra{\refj@jnl{Phys.~Rev.~A}} % Physical Review A: General Physics +\def\prb{\refj@jnl{Phys.~Rev.~B}} % Physical Review B: Solid State +\def\prc{\refj@jnl{Phys.~Rev.~C}} % Physical Review C +\def\prd{\refj@jnl{Phys.~Rev.~D}} % Physical Review D +\def\pre{\refj@jnl{Phys.~Rev.~E}} % Physical Review E +\def\prl{\refj@jnl{Phys.~Rev.~Lett.}} % Physical Review Letters +\def\pasa{\refj@jnl{PASA}} % Publications of the Astron. Soc. of Australia +\def\pasp{\refj@jnl{PASP}} % Publications of the ASP +\def\pasj{\refj@jnl{PASJ}} % Publications of the ASJ +\def\rmxaa{\refj@jnl{Rev. Mexicana Astron. Astrofis.}}% + % Revista Mexicana de Astronomia y Astrofisica +\def\qjras{\refj@jnl{QJRAS}} % Quarterly Journal of the RAS +\def\skytel{\refj@jnl{S\&T}} % Sky and Telescope +\def\solphys{\refj@jnl{Sol.~Phys.}} % Solar Physics +\def\sovast{\refj@jnl{Soviet~Ast.}} % Soviet Astronomy +\def\ssr{\refj@jnl{Space~Sci.~Rev.}} % Space Science Reviews +\def\zap{\refj@jnl{ZAp}} % Zeitschrift fuer Astrophysik +\def\nat{\refj@jnl{Nature}} % Nature +\def\iaucirc{\refj@jnl{IAU~Circ.}} % IAU Cirulars +\def\aplett{\refj@jnl{Astrophys.~Lett.}} % Astrophysics Letters +\def\apspr{\refj@jnl{Astrophys.~Space~Phys.~Res.}} + % Astrophysics Space Physics Research +\def\bain{\refj@jnl{Bull.~Astron.~Inst.~Netherlands}} + % Bulletin Astronomical Institute of the Netherlands +\def\fcp{\refj@jnl{Fund.~Cosmic~Phys.}} % Fundamental Cosmic Physics +\def\gca{\refj@jnl{Geochim.~Cosmochim.~Acta}} % Geochimica Cosmochimica Acta +\def\grl{\refj@jnl{Geophys.~Res.~Lett.}} % Geophysics Research Letters +\def\jcp{\refj@jnl{J.~Chem.~Phys.}} % Journal of Chemical Physics +\def\jgr{\refj@jnl{J.~Geophys.~Res.}} % Journal of Geophysics Research +\def\jqsrt{\refj@jnl{J.~Quant.~Spec.~Radiat.~Transf.}} + % Journal of Quantitiative Spectroscopy and Radiative Transfer +\def\memsai{\refj@jnl{Mem.~Soc.~Astron.~Italiana}} + % Mem. Societa Astronomica Italiana +\def\nphysa{\refj@jnl{Nucl.~Phys.~A}} % Nuclear Physics A +\def\physrep{\refj@jnl{Phys.~Rep.}} % Physics Reports +\def\physscr{\refj@jnl{Phys.~Scr}} % Physica Scripta +\def\planss{\refj@jnl{Planet.~Space~Sci.}} % Planetary Space Science +\def\procspie{\refj@jnl{Proc.~SPIE}} % Proceedings of the SPIE + +\let\astap=\aap +\let\apjlett=\apjl +\let\apjsupp=\apjs +\let\applopt=\ao diff --git a/arxiv/lsb.tex b/arxiv/lsb.tex new file mode 100644 index 0000000..55c48a0 --- /dev/null +++ b/arxiv/lsb.tex @@ -0,0 +1,176 @@ +\section{Low Surface Brightness Science}\label{sec:tasks:lsb} +{\justify +The exquisite data quality of LSST will open up a brand new regime in +low surface brightness (LSB) science, over unprecedentedly large areas of the sky. LSST's unique deep-wide capabilities will enable us to uncover new evidence for and measures of the cosmic merger rate (via tidal features that result from galaxy interactions), reveal the signatures of hierarchical structure formation in extragalactic stellar halos, and probe the LSB outskirts around local galaxies. The following science tasks provide an enumeration of the critical preparatory research tasks required for fully leveraging the LSST dataset for LSB science. + +\begin{tasklist}{LSB} +\subsection{Low Surface Brightness Tidal Features} +\tasktitle{Low Surface Brightness Tidal Features} +\begin{task} +\label{task:lsb:tidal_features} +\motivation{ +A key advantage of LSST over previous large area surveys (e.g. the SDSS) is its ability to detect LSB tidal features around galaxies, which encode their assembly history \citep[e.g.][]{kaviraj2014b}. The LSST survey (which has a larger footprint than the SDSS) will be two magnitudes deeper than the SDSS almost immediately after start of operations, and five magnitudes deeper at the end of the survey. With this unparalleled deep-wide capability, LSST will revolutionize LSB tidal feature science, enabling, for the first time, the empirically reconstruction of the assembly histories of galaxies over at least two-thirds of cosmic time. +These histories provide the most stringent observational test yet of the hierarchical paradigm and elucidate the role of mergers (down to mass ratios of at least 1:50) in driving star formation, black-hole growth, and morphological transformation over a significant fraction of cosmic time.\\ +~\\ +Prior to LSST, typical studies of the LSB universe have focused on small galaxy samples (e.g. in the SDSS Stripe 82), often selected using criteria that are difficult to quantify (e.g. visual inspection, that can be somewhat subjective) or reproduce in theoretical models. Furthermore, previously used techniques for the identification and characterization of features, such as visual inspection, cannot be easily applied to the unprecedented volume of data expected from the next generation of telescopes like LSST. Given the depth and volume of data expected from LSST, it is critical that we automate the detection, measurement and characterization of LSB tidal features, at least to the point where samples for further study can be selected via database queries, and where the completeness of samples returned from such queries can be quantified. +} +~\\ +\activities{ +Several activities are of critical importance and need to be completed before LSST commissioning and the survey proper: +\begin{enumerate} +\item Simulating realistic LSST images and LSB features (using e.g. new high-resolution hydrodynamical simulations in cosmological volumes, such as Horizon-AGN, EAGLE, Illustris and others). +\item Identifying precursor datasets (e.g. the Hyper Suprime-Cam Survey or the Dark Energy Camera Legacy Survey) that can be used as testbeds for developing LSB tools for use on LSST data. +\item Using such simulations to develop algorithms for auto-detection, measurement and characterization of LSB features (e.g. using the properties of LSB tidal features to back-engineer the properties of the mergers which created them). +\item Applying these algorithms to the precursor datasets to test their suitability. +\item Ensuring that LSST Level 2 processing and observing strategies are aligned with the needs of LSB tidal-feature science. +\end{enumerate} +} +~\\ +\deliverables{%Deliverables over the next several years (especially in the run up to commissioning) from the activities described above include the following: +~ +\begin{enumerate} +\item Realistic mock LSST images from cosmological simulations (including re-simulations of individual objects where necessary) with spatial resolutions of $\sim1$ kpc or better. +\item Algorithms for finding galaxies with LSB tidal features, measuring the properties of these features and characterizing them i.e. using the properties of LSB tidal features to reconstruct the properties of the mergers which created them (e.g. mass ratios, time elapsed since the merger, etc.). +\item A baseline concept for a value-added LSST database of LSB tidal features. +\end{enumerate} +} +\end{task} + + +\subsection{Low Surface Brightness Galaxies} +\tasktitle{Low Surface Brightness Galaxies} +\begin{task} +\label{task:lsb:galaxies} +\motivation{ +The objective of this task is to investigate objects that have surface brightnesses much less than the background night sky and are typical of the Milky Way galaxy within which we live. Many authors have previously shown how difficult it is to identify LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to our own spiral galaxy.\\ +~\\ +The LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via neutral hydrogen surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies will still be quite easy to detect in LSST images.\\ +~\\ +At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting surface brightness limit of the LSST combined with the large field-of-view make this facility unique for probing the existence of large LSBs similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This issue is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception.\\ +~\\ +To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5~\mathrm{mag}~\mathrm{arcsec}^{-2}$ and that from a space telescope typically an order of magnitude fainter $\approx25.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28~\mathrm{mag}~\mathrm{arcsec}^{-2}$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32~\mathrm{mag}~\mathrm{arcsec}^{-2}$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into luminous stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the universe using LSST to at least a surface brightness level of $30~\mathrm{mag}~\mathrm{arcsec}^{-2}$. +} +~\\ +\activities{The key activities for this task include the production of simulated data e.g. from new hydrodynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. Once produced, analysis of simulated images is needed to ensure that LSB galaxies can be accurately detected. This analysis will require the development of new object detection software specifically designed for the detection of LSB galaxies, in particular objects with large size, near or melted with brighter galaxies, and highly irregular and distorted objects. Precursor data sets that can be used to test our methods +will need to be identified. Data generated using numerical simulations can be used to examine the types of galaxies produced that have sufficient angular momentum to become LSB disks. These disks can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. +New methods of detecting LSB objects will be engineered, including pixel clustering methods and the labeling of pixels with certain properties, i.e., surface brightness level, SED shape, and proximity to other similar pixels. We will train our methods on other currently available data sets (KIDS, CFHT etc). These analyses will further +require the production of realistic simulated LSST images of nearby dwarf galaxies (from high resolution hydrodynamical simulations like New Horizon which has resolutions of tens of parsecs), the +identification of nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools, +and the development and testing of the database search queries for finding candidates of several shapes and sizes. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Realistic mock LSST images of LSB galaxies from simulations. +\item Detection and selection algorithms for LSB galaxies from observational datasets. +\item A new Level 3 LSB galaxy detection package. +\end{enumerate} +} +\end{task} + + + +\subsection{Faint Outskirts of Galaxies} +\tasktitle{Faint Outskirts of Galaxies} +\begin{task} +\label{task:lsb:faint_outskirts} +\motivation{ +The outskirts of nearby galaxies, loosely defined as the regions below $ +25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in neutral +hydrogen, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, VST, Subaru, GTC). The main science driver for studying the outskirts of galaxies is understanding the assembly, formation, and evolution of galaxies. These studies can be performed +through imaging and subsequent parameterization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar halos. From numerical modeling, it is known that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo are tightly related to the accretion and merging history, as illustrated by the imaging of structures in the stars in the outskirts of M31 and other local group galaxies.\\ +~\\ +Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000s of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, need to be understood before stacking. The systematics will affect some measurements more than others -- for instance, linear features such as tidal streams will be less affected by overall PSF. +} +~\\ +\activities{ +Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modeling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyze the outskirts. Dithering and rotation of individual imaging will need to be modeled before stacking multiple imaging. +\\ +Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Information on the stability and spatial constancy of the LSST PSF. +\item Improved control over systematics for LSB science, and other fields including weak lensing. +\end{enumerate} +} +\end{task} + + +\subsection{Sky Estimation} +\tasktitle{Sky Estimation} +\begin{task} +\label{task:lsb:task_label} +\motivation{ +LSST is likely to reveal new aspects of galaxies as low surface brightness objects. A relatively unexplored area is ultra-low surface brightness morphology and tails over a wide range of angular scales at levels of 31-32 mag/sq.~arcsec. Accurate sky estimation is key. +Current algorithms, including SDSS Photo, SExtractor, GalFit, and PyMorph, experience challenges when +attempting unbiased sky estimation with deep data. +The problem is typically encountered on scales large compared with the PSF where the counts from the object become indistinguishable from the ``sky'' counts. For example, fits of Sersic profiles [after PSF convolution] suffer from bias at large Sersic index due to sky mis-estimation (usually over-subtraction of sky due to systematic non-detection of fainter objects). +~\\~\\ +The discovery space is large: LSB features can exist on scales of arcseconds to many arcminutes -- spanning the majority of faint galaxies at redshift $z\sim 1$ to more nearby LSB galaxies. In the past it has been assumed that galaxies at all redshifts fit the profiles of low-z galaxies, and that the surface brightness level beyond $\sim$10 half light radii represents the sky background, as opposed to some extended LSB halo. In the era of LSST, we can afford to let the data speak for themselves. +~\\~\\ +The correct sky estimation on any angular scale is actually an ill-posed problem. The proper sky for barely resolved galaxies at high-redshift is in principle quite different from the correct sky level for large angular scale LSB features. Indeed, the flux from barely resolved galaxies sits on top of the fainter larger angular scale flux associated with arcminute scale LSB extragalactic features, which in turn sits on top of the starlight reflected by Galactic cirrus, night sky surface brightness caused by atmosphere emission and scattered light from bright objects in the camera and the atmosphere. Thus for LSST, there will be a separate sky estimate appropriate for each of the different morphological classes of LSB objects. To make the problem tractable, a multi-component sky model must be built. +} +~\\ +\activities{ +The research program starts with the current best methods, improving sky estimates on all angular scales via new algorithms, and then validation via simulations. The sky model in principle can be built using knowledge of the LSST system, locations of bright objects, the observational data, and statistical summaries of faint galaxy counts from HST. The first step is to detect all objects above a position-variable local sky estimate, masking them, and then growing the masks. The remaining pixels contain undetected galaxies, giving an over-estimate of the sky level around compact objects if left uncorrected. Statistical faint galaxy counts can help in making these corrections. When corrected, the Poisson noise from the remaining sky may be fit with a Gaussian. Even then, 3-$\sigma$ clipping and/or one-sided fitting may be required. This entire process is recursive on every angular scale where there are important sky components. +~\\~\\ +LSST data management are planning novel algorithms of this general sort, and close coordination will be necessary and beneficial. The Dark Energy Science Collaboration (DESC) Science Roadmap \citep{LSSTDESC} +includes plans for realistic image-based simulations of the LSST sky. In coordination with DESC, the inclusion of faint, large-scale LSB objects in future Data Challenge catalogs and images would benefit all groups involved in testing algorithms and characterizing LSB objects. Improvements we make may be ingested by LSST DM as a Level 3 contribution. LSB ghosts due to reflected bright star light in the camera should also be included. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item In coordination with the Dark Energy Science Collaboration, generate realistic image simulations. Faint, large-scale LSB objects should be included in Data Challenge image based simulations. The level of realism in the simulations can be extended to what is physically possible, rather than limited to conventional morphological models. +\item Recursive sky model building algorithms applied to these simulations, with statistical galaxy count corrections. +\item Development of metrics for successful detection and characterization of each extragalactic component. +\item Tests of degeneracies among models, and sensitivity to priors. Validation on simulations, on various types of objects. +\item Tests on LSST precursor deep survey data, for performance estimates. +\item Tests on deep LSST commissioning data. +\end{enumerate} +} +\end{task} + + +\subsection{Intracluster Light} +\tasktitle{Intracluster Light} +\begin{task} +\label{task:lsb:icl} +\motivation{ +Intra-cluster Light (ICL) is a low surface brightness stellar component that permeates galaxy clusters. ICL is predicted to be formed mainly of stars stripped from cluster galaxies via interactions with other members, which then become bound to the total cluster potential. The ICL is also likely to contain stars that formed in the gaseous knots torn from in-falling galaxies as they are ram-pressure stripped by the hot intra-cluster medium. Therefore, it is important to study the ICL as it has kept a record of the assembly history of the cluster. Assuming LSST and its data products are sensitive to large LSB structures (see Activities and Deliverables) then it will be possible to perform the first comprehensive survey of ICL in galaxy clusters and groups within a uniform dataset.\\ +~\\ +Some outstanding scientific questions, which LSST could solve are as follows: +\begin{itemize} +\item When does the ICL (to a given SB limit) first emerge i.e. at what redshift and/or halo mass? +\item Does the ICL contain significant substructure? +\item What is its surface brightness profile and does it have a color dependence, which would indicate age/metallicity gradients? +\item Where does the ICL begin and the large diffuse cD halo of the Brightest Cluster Galaxy (BCG) end and do they have the same origin? +\end{itemize} +} +~\\ +\activities{ +The preparatory work for the ICL component of the LSB case involves investigating LSST-specific issues for large LSB features and the known properties of the ICL itself. +The LSST specific issues fall into three categories: telescope; observation strategy; and pipeline. The faint, large radii wings of the PSF and any low-level scattered light or reflections from the telescope optics or structure will produce LSB signals, which could easily mimic the ICL. The dither pattern of the observations, if smaller than the typical extent of a cluster, could mean that the ICL is treated as a variation in the background during the reduction and/or image combination process, rather than as a real object. This leads onto the pipeline itself which, regardless of the dither pattern, could remove the ICL if an aggressive background subtraction is used on either single frames or when combining images. It is therefore crucial to liaise with the LSST Project's strategy, telescope, instrument and data reduction teams.\\ +~\\ +The ICL specific issues are mainly the feasibility of observing the ICL given its known properties, which can be simulated from existing data. Using deep observations of the ICL in low redshift clusters one can model whether it is expected to see ICL at higher redshifts (up to $z=1$) given dimming, stellar population evolution, and the surface brightness limits of LSST. This consideration is crucial for determining possible evolution in ICL properties. For +studies of low mass groups or high-redshift systems, it may be required to stack populations to obtain a detection of the ICL. +An assessment of whether a genuine stacked ICL detection could be achieved by a comprehensive masking of galaxy cluster members is important, as is a determination of whether faint galaxies just below the detection threshold end up combining to give a false or boosted ICL signal. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item An investigation of telescope specific issues that affect the measurement of large LSB features: PSF wings; scattered light. +\item An investigation of observation specific issues that affect the measurement of large LSB features: dither pattern strategy. +\item An investigation of image pipeline specific issues that affect the measurement of large LSB features: background removal; image combining. +\item A feasibility analysis: given the depth/surface brightness limit of the LSST imaging, to what limits can we hope to recover ICL in clusters and to what redshifts? Can this be simulated or extrapolated from deep imaging of low-z clusters? +\item An investigation of the feasibility of stacking clusters to obtain faint ICL - this is difficult and will require very strong masking of even the faintest observable cluster members. +\end{enumerate} +} +\end{task} +\end{tasklist} +} diff --git a/arxiv/main.tex b/arxiv/main.tex new file mode 100644 index 0000000..130fee3 --- /dev/null +++ b/arxiv/main.tex @@ -0,0 +1,83 @@ +%--------------------------------------------------------------------------------------- +%--------------------------------------------------------------------------------------- +% PACKAGES AND OTHER DOCUMENT CONFIGURATIONS +%---------------------------------------------------------------------------------------- + +\documentclass[11pt,fleqn,oneside,openany]{book} +\input{structure} +\usepackage{booktabs} +\usepackage{pdflscape} +\usepackage{float} +\usepackage[colorlinks=true, allcolors=blue]{hyperref} +\usepackage[document]{ragged2e} +\begin{document} +\input{journal_macros} + + +%---------------------------------------------------------------------------------------- +% TITLE PAGE +%---------------------------------------------------------------------------------------- +\thispagestyle{empty} +{\Huge Large Synoptic Survey Telescope} +\linebreak +\linebreak +{\Huge Galaxies Science Roadmap} +\linebreak +\linebreak +{\centering +\input{authorlist} +} +\vfill + +%---------------------------------------------------------------------------------------- +% COPYRIGHT PAGE +%---------------------------------------------------------------------------------------- +\newpage +\thispagestyle{empty} + +\noindent +{\justify +The {\it Large Synoptic Survey Telescope Galaxies Science Roadmap} represents the collective efforts of more than one hundred scientists to define the critical research activities to prepare our field to maximize +the science return of the LSST dataset. We want to thank the LSST Corporation for their +support in developing this Roadmap and for supporting LSST-related science more broadly. +We also wish to thank the LSST Galaxies Science Collaboration members for their efforts +over the years in developing the case for extragalactic science with LSST. +} +\vspace{1in} + +Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}) and the LSST Galaxies Science Collaboration ({\tt lsst-galaxies@lsstcorp.org}). +\vspace{1in} +\input{VersionDate} + + +%---------------------------------------------------------------------------------------- +% Abstract +%---------------------------------------------------------------------------------------- + +\include{abstract} + +%---------------------------------------------------------------------------------------- +% Table of Contents +%---------------------------------------------------------------------------------------- + +\tableofcontents % Print the table of contents + + +%---------------------------------------------------------------------------------------- +% Chapters +%---------------------------------------------------------------------------------------- + +\input{introduction} +\input{science_background} +\input{task_lists} + +%--------------------------------------------------------------------------------------- +% References +%--------------------------------------------------------------------------------------- +\bibliography{references} + + +%---END--- +\end{document} + + diff --git a/arxiv/photo_z.tex b/arxiv/photo_z.tex new file mode 100644 index 0000000..abdedd5 --- /dev/null +++ b/arxiv/photo_z.tex @@ -0,0 +1,173 @@ +\section{Photometric Redshifts}\label{sec:tasks:photo_z} +{\justify +For a photometric survey like LSST, our abilities to accurately measure distances to huge samples of galaxies, constrain the stellar masses, ages, and metallicities of objects as a function of time, measure the spatial clustering of galaxy populations, and identify unusual objects at various cosmic epochs will all rely heavily on +photometric redshift measurements. +The following important preparatory science tasks address both the systematic uncertainties on photometric redshifts associated with the LSST observatory and with the requisite +stellar population synthesis models. + +A major effort within the LSST Dark Energy Science Collaboration (DESC) is focused on the development of photometric redshift algorithms for LSST, including the incorporation of joint probability distributions between redshift and astrophysical parameters of interest for the study of galaxy evolution. Efforts within the Galaxies collaboration should be able to leverage work happening in DESC and build upon it to ensure that photometric redshifts optimized for galaxy science are available. +The related question of determining photometric redshifts for Active Galactic Nuclei is discussed in Section \ref{task:agn:photoz}. + +\begin{tasklist}{PZ} +\subsection{Impact of Filter Variations on Galaxy Photometric Redshift Precision} +\tasktitle{Impact of Filter Variations on Galaxy Photometric Redshift Precision}\label{pzfiltervar} +\begin{task} +\label{task:photo_z:filter_variations} +\motivation{ +For accurate photometric redshifts, well-calibrated photometry is essential. Variations in the telescope system, particularly the broad-band $ugrizy$ filters, will need to be very well understood to meet the stringent LSST calibration goals. Photometry will be impacted by multiple factors that may vary as a function of position and/or time. The position of the galaxy in the focal plane will change the effective throughput both due to the angle of the light passing through the filter, and potential variations in the filter transmission itself due to coating irregularities across the physical filter. Preliminary tests show that the filter variation may have a relatively small impact, but further tests are necessary to ensure that these variations will not dominate the photometric error budget.\\ +~\\ +In addition, the effective passbands of the LSST filters will depend significantly upon atmospheric conditions and airmass, particularly in $y$-band. The spatially correlated nature of these effects can induce scale-dependent systematics that could be particularly insidious for measurements of large-scale environment and clustering. The nominal plan from LSST Data Management is to correct for variations across the focal plane or between, incorporating approximate models for galaxy SEDs (which may be based upon photometric redshift estimates). Such corrections may be imperfect and leave residuals, particularly for specific populations with unusual SEDs.~\\ +~\\ +Tests of the amplitude of these residuals and their impact on photo-$z$'s, especially for particular object classes of interest, will be important for determining to what degree DM data products can be used directly for galaxies work. +If the variations can be calibrated well, they could potentially be used to further improve, rather than degrade, photo-$z$ performance. +The variations in filter response can offer up a small amount of extra information on the object SED given the slight variation in effective filter wavelength, particularly for objects with strong narrow features (i.e., emission lines). +Tests of how much information is gained can inform whether or not the extra computational effort required for computing photo-$z$'s that incorporate the effective passband from every individual LSST observation of an object will be superior to estimates incorporating DM measurements corrected to the six fiducial filters of the survey. All topics discussed above are also being examined by the LSST Dark Energy Science Collaboration Photometric Calibration working group, and there are several related tasks described in the DESC Science Roadmap document \citep{LSSTDESC}. +Communication and coordination with the Photometric Calibration group will be very important to maximize the impact of work on these areas of shared interest. +} +~\\ +\activities{ +Tests of the SED-dependent residuals in photometric redshifts induced by photometric calibration systematics at the expected level.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Quantification of the amplitude of photometric uncertainties in the LSST filters due to variation in filter throughputs and atmospheric transmission. +\item Identification of SED classes where residuals in DM calibration of effective passbands will be prominent. +\end{enumerate} +} +\end{task} + +\subsection{Photometric Redshifts in the LSST Deep Drilling Fields} +\tasktitle{Photometric Redshifts in the LSST Deep Drilling Fields} +\begin{task} +\label{task:photo_z:ddf} +\motivation{ +The LSST Deep Drilling Fields present different challenges than the main survey, including increasing rates of confusion between sources, but they also provide the ability to use subsets of the data to construct higher resolution images due to the large number of repeat observations. These properties allow investigations of galaxies of brightness which are close to the noise floor in the main survey. Having an accurate error model is essential for optimal photo-z performance; the larger number of repeat observations in the Deep Drilling Fields enables empirical checks on the magnitude and flux uncertainties generated by the LSST pipeline, through both higher signal-to-noise stacks and using subsets of the data to model the uncertainties. As LSST imaging data will not be available for several more years, such studies of subset stacks to examine seeing and error properties would have to use pre-existing data sets, e.~g.~Hyper Suprime-Cam data, when testing such algorithms and putting needed infrastructure in place so that it can be used once LSST data are flowing.\\~\\ +In addition to providing useful information about main-survey photometric redshift quality, the Deep Drilling Fields will pose particular challenges for photometric redshift determination, as spectroscopy for complete samples down to the DDF depth for photo-$z$ training and calibration will be completely infeasible, and the DDF area may limit high-precision calibration by cross-correlation techniques. +} +~\\ +\activities{ +Tests of confusion limits in deeper coadds than available in the main survey, as well as improvements enabled by ''best seeing" subsamples on precursor data sets. Tests of the flux error model using subsets and higher signal-to-noise coadds. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Studies of confusion and deblending in deep stacks and ``best seeing" conditions using precursor data sets. +\item Estimates of gains in studying faint galaxy populations at higher signal-to-noise than available in the main survey. +\item A check on LSST flux error models using both higher signal-to-noise coadds and subsets of the data to main survey depth using precursor data sets. +\end{enumerate} +} +\end{task} + +\subsection{Multivariate Physical Properties of Galaxies from Photometric Redshifts} +\tasktitle{Multivariate Physical Properties of Galaxies from Photometric Redshifts} +\begin{task} +\label{task:photo_z:physical_properties} +\motivation{ +Measurements of key derived physical properties are critical for much work on galaxies and their evolution. The properties measurable from SEDs include star formation rate (SFR), stellar mass ($M_\star$), specific SFR (sSFR), dust attenuation, and stellar metallicity.\\ +~\\ +Many recent science analyses have relied upon derived physical properties rather than fluxes and luminosities in the UV, optical and near-IR bands. This is largely a matter of convenience: utilizing tables of derived properties require no redshift (K) corrections or extra dust corrected, as those are effectively applied in the measurement process; they are also closer to the quantities best determined in simulations. However, derived quantities have the disadvantage of the potential for significant systematic errors in measurement, as well as non-uniformity in their definition (e.g., differences in adopted IMF can change stellar masses by $\sim 0.5$ dex). \\~\\ +Stellar mass has emerged as a parameter of choice for selecting galaxy samples and attempting to make apples-to-apples comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a measure of a galaxy's star formation history. Dust attenuation and stellar metallicity can help to probe processes important for understanding galaxy evolution.\\ +~\\ +This task shares some goals with the Dark Energy Science Collaboration Photometric Redshifts working group, as laid out in their Science Roadmap \citep{LSSTDESC}, +who are also interested in multidimensional probability density functions joint in redshift and stellar mass, star formation rate, and dust content of the galaxies. Coordination on this area with the DESC Photo-z working group will benefit both groups. +} +~\\ +\activities{ +Deriving physical properties, usually accomplished by spectral energy distribution (SED) fitting, is an involved process and the results depend on a number of factors, including the underlying population models, assumed dust attenuation law, assumed star formation histories, choice of model priors, choice of IMF, emission line corrections, choice of input fluxes, type of flux measurements, treatment of flux errors, SED fitting methodology, and interpretation of the resulting probability distribution functions \citep[PDFs; e.g.,][]{salim2016a}.\\ +~\\ +In the case of LSST, an additional challenge is that the redshifts available will generally be photometric, and carry a PDF (a measure of uncertainty) of their own. In principle, the redshift and SED (or specific physical parameter) should be determined simultaneously, as the inferred galaxy properties such as luminosity and stellar mass are correlated with redshift. One alternative approach is to estimate the redshift PDF using empirical training sets, then estimate best fitting SEDs at each redshift to determine physical parameters. This approximation enables the use of potentially more accurate machine learning based methods to estimate the redshift PDF, at the possible expense of adding biases and degeneracies due to the assumptions inherent in treating the redshift and physical properties separately. Further study is necessary to determine whether the benefits of this approximation outweigh the drawbacks. +Activities will consist of testing whether the determination of physical parameters and photo-$z$ should be performed jointly or not, based on training sets with spectroscopic redshifts at a range of redshifts. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Pre-LSST: A set of guidelines as to optimal practices regarding the derivation of both the photo-$z$ and properties, together with the software to be used. +\item With LSST data: in consultation with the DESC Photo-z working group, the production of catalogs of properties to be used by the collaboration. +\end{enumerate} +} +\end{task} + +\subsection{Identifying Spectroscopic Redshift Training Sets for LSST} +\tasktitle{Identifying Spectroscopic Redshift Training Sets for LSST} +\begin{task} +\label{task:photo_z:specz_training_sets} +\motivation{ +Accurate photometric redshift estimates require deep spectroscopic redshift data in order to help train algorithms, either directly in the case of machine learning based algorithms, or to train Bayesian priors and adjust zero points, transmission curves, or error models for template-based methods. Representative spectroscopic samples can be used to investigate the accuracy of photo-$z$ algorithms. Obtaining representative training sets is a problem across multiple science tasks, and in fact, across many current and upcoming large surveys. As the telescope resources necessary will be quite extensive, coordination with the other large surveys is essential. A detailed study of spectroscopic training needs and potential spectroscopic instruments that will be available in the coming years was undertaken by \citet[]{newman2015a}. We must now begin our attempts to obtain the necessary samples. We must also identify any needs that are unique to galaxy science that may not be prioritized in the cosmology-focused efforts to date, e.~g.~are faint galaxy populations sampled adequately in the planned spectroscopic samples? +} +~\\ +\activities{In coordination with other large surveys and other LSST science collaborations, collate existing spectroscopic redshift data over both DDF and wider fields, and assess the biases due to selection and redshift incompleteness for each spectroscopic data set. Assess the robustness of existing data, and determine color spaces where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. This work should become much more efficient once PFS and MOONS become available. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item A list of existing {\it robust} spectroscopic objects, and identified gaps in the currently available training samples. +\item Telescope proposals for spectroscopic campaigns to fill in the sample gaps. +\end{enumerate} +} +\end{task} + +\subsection{Simulations with Realistic Galaxy Colors and Physical Properties} +\tasktitle{Simulations with Realistic Galaxy Colors and Physical Properties} +\begin{task} +\label{task:photo_z:color_simulations} +\motivation{ +As representative samples of spectroscopic redshifts will be very difficult to compile for LSST, simulations will play a key role in calibrating estimates of physical properties such as galaxy stellar mass, star formation rate, and other properties. This is particularly problematic for photometric surveys, where photometric redshift and physical property estimates must be calculated jointly. In addition, we must include prominent effects that will influence the expected photometric performance; for example, the presence of an active galactic nucleus can significantly impact the color of a galaxy and the inferred values for the physical parameters, so models of AGN components of varying strength must also be included in simulations. \\ +~\\ + Many current-generation simulations cannot or do not simultaneously match observed color distributions and physical property characteristics for the galaxy population at high-redshift. As photo-$z$ algorithms are highly dependent on accurate photometry, realistic color distributions are required to test the bivariate redshift-physical property estimates. Working with the galaxy simulations and high-redshift galaxy working groups to develop new simulations with more accurate high-redshift colors is a priority. These photo-$z$ needs are not unique, and the improved simulations will benefit both the Galaxies Collaboration and other science collaborations. Indeed, one fruitful way to proceed with this work may be to incorporate new tests into the DESCQA framework being used by the LSST Dark Energy Science Collaboration to improve mock catalogs for DESC work (Mao et al. 2017, in prep.). +} +~\\ +\activities{ +The main activity for this task is to develop improved simulation metrics based upon observational studies of both low- and high-redshift galaxies. This will require expertise from the photo-$z$, high-redshift galaxies, AGN, and simulations working groups. In order to test whether mock galaxy populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions.\\ +~\\ +If we then assume that the simulations are valid beyond the test intervals, we can use them as a testbed to develop improved algorithms for a wide variety of applications, e.~g.~selecting specific sub-populations of galaxies. +One key aspect of this work is that spectral energy distributions in simulations cannot be generated from discrete templates, but instead must span a continuous range of properties. If only a finite set of rest-frame SEDs are used in the simulation, the photo-$z$ problem would be unnaturally simplified and falsely strong photometric redshift predictions would result. Thus a method is required that simultaneously reproduces galaxy colors without resorting to a restricted set of SEDs. For example, this could be done by creating complete SEDs based on an extended set of principal components (e.g., extending the $kcorrect$ or EAZY basis set), though in general additional constraints are required with PCA-like techniques to ensure that unphysical spectra are not generated.\\ +~\\ +With sufficiently realistic simulations that reproduce the ensemble of galaxy star formation histories and the mapping between those histories and spectral energy distributions, we can use simulated catalogs to test techniques for identifying specific galaxy sub-populations. For some studies, we may wish to examine the relationship between galaxies in specific sub-populations and their large-scale structure environment. Thus, realistic density and clustering properties are also important in the simulation. There are a wide variety of techniques that may be used for environmental measures, operating on a variety of scales. As small-scale measurements can be noisy and/or washed out by photometric redshift errors, it may be more effective to measure the average overdensity/environment as a function of galaxy properties, rather than the reverse. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Determination of a list of which physical parameters are important for galaxy science. +\item Compiling observable datasets that can be used as comparators for simulated datasets. +\item Developing a set of metrics to compare simulations to the observational data. These may be implemented in the DESCQA framework. +\item Use the metrics in deliverable B to create updated simulations with more realistic parameter distributions. +\item Development of improved joint estimators for redshift and physical properties (M*, SFR, etc.). +\item Development of improved spectral extended basis sets to create galaxy colors which match observations, including emission lines, etc. +\item Using mock catalogs, developing techniques that for selecting specific galaxy sub-samples. +\item Developing environment estimators for simulated datasets and algorithms able to measure the strength of environmental dependence on galaxy properties. +\end{enumerate} +} +\end{task} + +\subsection{Incorporating Galaxy Size and Surface Brightness into Photometric Redshift Estimates} +\tasktitle{Incorporating Galaxy Size and Surface Brightness into Photometric Redshift Estimates} +\begin{task} +\label{task:photo_z:size_and_sb_priors} +\motivation{ +Photometric redshift algorithms most commonly have used galaxy fluxes and/or colors alone to estimate redshifts. However, morphological information on a galaxy’s size, shape, overall surface brightness (SB), or detailed surface brightness (SB) profile can provide additional information that can aid in constraining the redshift and/or type of a galaxy, breaking potential degeneracies that using colors alone would miss. Gains can be particularly substantial at low redshift where LSST will at least partially resolve galaxies. Incorporating morphological information may help to improve joint predictions for galaxy properties and redshift as well, at the cost of imposing assumptions about links between morphology and color/SED that may not apply to all galaxies. +If sufficient training samples are available, priors for redshift and SED parameters given morphological parameters, $p(z, SED | P)$, can be constructed that can be incorporated into Bayesian analyses of photometric redshifts and potentially lead to improved constraints on the redshift PDF (i.e., $p(z | P, C )$ , where $P$ represents observed morphological parameters, $C$ represents observed flux/color measurements, and $SED$ represents one or more parameters representing the rest-frame SED of a galaxy). +} +~\\ +\activities{ +The first activity for this task will be to assess whether LSST Data Management algorithms for multiple-Sersic model fits to galaxy photometry are sufficient for the needs of this working group. Evaluation of DM pipeline-processed precursor datasets in regions with HST imaging may be particularly valuable. +With measures of morphological parameters in hand, a useful next step would be to evaluate whether photometric redshift estimates in fact improve with the incorporation of morphological information (in the domain where training is perfect, i.e., with training sets and test sets with matching properties); this may be done using machine learning-based codes, which can make maximal use of all information available in the parameter set provided without requiring the development of a detailed model (such methods extrapolate poorly, but that is not a problem for this test). +If incorporating morphological information does in fact yield improvements, the next step would be the development of Bayesian priors for redshift given galaxy photometry and morphology measurements for incorporation into template-based methods. This may be done using either pipeline-processed simulated datasets (if they are sufficiently realistic) or real observations with spectroscopic redshifts. Tests will then show the performance of photometric redshifts incorporating morphological priors relative to performance using galaxy photometry alone. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Tests of LSST DM algorithms for measuring morphological parameters for galaxies. +\item A cross-matched catalog containing objects with known redshifts and DM pipeline-measured morphology measurements. +\item Tests of whether incorporating morphological information improves photometric redshift measurements using machine learning-based algorithms, as well as examination of what parameters are most informative +\item Bayesian priors $p(z, SED | P)$ that can be incorporate into template-based algorithms and used to improve photo-$z$ measurements. +\end{enumerate} +} +\end{task} +\end{tasklist} +} diff --git a/arxiv/references.bib b/arxiv/references.bib new file mode 100644 index 0000000..3d3c9c4 --- /dev/null +++ b/arxiv/references.bib @@ -0,0 +1,1754 @@ +@ARTICLE{LSSTSciBook, + author = {{LSST Science Collaboration} and {Abell}, P.~A. and {Allison}, J. and + {Anderson}, S.~F. and {Andrew}, J.~R. and {Angel}, J.~R.~P. and + {Armus}, L. and {Arnett}, D. and {Asztalos}, S.~J. and {Axelrod}, T.~S. and et al.}, + title = "{LSST Science Book, Version 2.0}", + journal = {arXiv:0912.0201}, +archivePrefix = "arXiv", + eprint = {0912.0201}, + primaryClass = "astro-ph.IM", + keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Galaxy Astrophysics, Astrophysics - Solar and Stellar Astrophysics}, + year = 2009, + month = dec, + adsurl = {http://adsabs.harvard.edu/abs/2009arXiv0912.0201L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{LSSTDESC, + author = {{LSST Dark Energy Science Collaboration}}, + title = "{Large Synoptic Survey Telescope: Dark Energy Science Collaboration}", + journal = {arXiv:1211.0310}, +archivePrefix = "arXiv", + eprint = {1211.0310}, + primaryClass = "astro-ph.CO", + keywords = {Astrophysics - Cosmology and Extragalactic Astrophysics, High Energy Physics - Experiment}, + year = 2012, + month = nov, + adsurl = {http://adsabs.harvard.edu/abs/2012arXiv1211.0310L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@BOOK{nrc2010a, + author = "{National Research Council}", + title = "New Worlds, New Horizons in Astronomy and Astrophysics", + isbn = "978-0-309-15799-5", + doi = "10.17226/12951", + abstract = "Driven by discoveries, and enabled by leaps in technology and imagination, our understanding of the universe has changed dramatically during the course of the last few decades. The fields of astronomy and astrophysics are making new connections to physics, chemistry, biology, and computer science. Based on a broad and comprehensive survey of scientific opportunities, infrastructure, and organization in a national and international context, New Worlds, New Horizons in Astronomy and Astrophysics outlines a plan for ground- and space- based astronomy and astrophysics for the decade of the 2010's.\nRealizing these scientific opportunities is contingent upon maintaining and strengthening the foundations of the research enterprise including technological development, theory, computation and data handling, laboratory experiments, and human resources. New Worlds, New Horizons in Astronomy and Astrophysics proposes enhancing innovative but moderate-cost programs in space and on the ground that will enable the community to respond rapidly and flexibly to new scientific discoveries. The book recommends beginning construction on survey telescopes in space and on the ground to investigate the nature of dark energy, as well as the next generation of large ground-based giant optical telescopes and a new class of space-based gravitational observatory to observe the merging of distant black holes and precisely test theories of gravity.\nNew Worlds, New Horizons in Astronomy and Astrophysics recommends a balanced and executable program that will support research surrounding the most profound questions about the cosmos. The discoveries ahead will facilitate the search for habitable planets, shed light on dark energy and dark matter, and aid our understanding of the history of the universe and how the earliest stars and galaxies formed. The book is a useful resource for agencies supporting the field of astronomy and astrophysics, the Congressional committees with jurisdiction over those agencies, the scientific community, and the public.\n ", + url = "https://www.nap.edu/catalog/12951/new-worlds-new-horizons-in-astronomy-and-astrophysics", + year = 2010, + publisher = "The National Academies Press", + address = "Washington, DC" +} +%AAAAAAAAAAA +@ARTICLE{abraham1994a, + author = {{Abraham}, R.~G. and {Valdes}, F. and {Yee}, H.~K.~C. and {van den Bergh}, S. + }, + title = "{The morphologies of distant galaxies. 1: an automated classification system}", + journal = {\apj}, + keywords = {Astronomical Models, Computerized Simulation, Galactic Clusters, Image Classification, Mathematical Models, Morphology, Sky Surveys (Astronomy), Astronomical Photometry, Atmospheric Effects, Atmospheric Turbulence, Charge Coupled Devices, Monte Carlo Method, Seeing (Astronomy)}, + year = 1994, + month = sep, + volume = 432, + pages = {75-90}, + doi = {10.1086/174550}, + adsurl = {http://adsabs.harvard.edu/abs/1994ApJ...432...75A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{abraham2003a, + author = {{Abraham}, R.~G. and {van den Bergh}, S. and {Nair}, P.}, + title = "{A New Approach to Galaxy Morphology. I. Analysis of the Sloan Digital Sky Survey Early Data Release}", + journal = {\apj}, + eprint = {astro-ph/0301239}, + keywords = {Galaxies: Evolution, Galaxies: Fundamental Parameters}, + year = 2003, + month = may, + volume = 588, + pages = {218-229}, + doi = {10.1086/373919}, + adsurl = {http://adsabs.harvard.edu/abs/2003ApJ...588..218A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{abraham2014a, + author = {{Abraham}, R.~G. and {van Dokkum}, P.~G.}, + title = "{Ultra--Low Surface Brightness Imaging with the Dragonfly Telephoto Array}", + journal = {\pasp}, +archivePrefix = "arXiv", + eprint = {1401.5473}, + primaryClass = "astro-ph.IM", + keywords = {Astronomical Instrumentation}, + year = 2014, + month = jan, + volume = 126, + pages = {55-69}, + doi = {10.1086/674875}, + adsurl = {http://adsabs.harvard.edu/abs/2014PASP..126...55A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{applegate2014a, + author = {{Applegate}, D.~E. and {von der Linden}, A. and {Kelly}, P.~L. and + {Allen}, M.~T. and {Allen}, S.~W. and {Burchat}, P.~R. and {Burke}, D.~L. and + {Ebeling}, H. and {Mantz}, A. and {Morris}, R.~G.}, + title = "{Weighing the Giants - III. Methods and measurements of accurate galaxy cluster weak-lensing masses}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1208.0605}, + keywords = {gravitational lensing: weak, methods: data analysis, methods: statistical, galaxies: clusters: general, galaxies: distances and redshifts, cosmology: observations}, + year = 2014, + month = mar, + volume = 439, + pages = {48-72}, + doi = {10.1093/mnras/stt2129}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.439...48A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{atkinson2013, + author = {{Atkinson}, A.~M. and {Abraham}, R.~G. and {Ferguson}, A.~M.~N. + }, + title = "{Faint Tidal Features in Galaxies within the Canada-France-Hawaii Telescope Legacy Survey Wide Fields}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1301.4275}, + keywords = {astronomical databases: miscellaneous, catalogs, galaxies: general, galaxies: interactions, galaxies: peculiar, galaxies: statistics}, + year = 2013, + month = mar, + volume = 765, + eid = {28}, + pages = {28}, + doi = {10.1088/0004-637X/765/1/28}, + adsurl = {http://adsabs.harvard.edu/abs/2013ApJ...765...28A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{awan2016a, + author = {{Awan}, H. and {Gawiser}, E. and {Kurczynski}, P. and {Jones}, R.~L. and + {Zhan}, H. and {Padilla}, N.~D. and {Mu{\~n}oz Arancibia}, A.~M. and + {Orsi}, A. and {Cora}, S.~A. and {Yoachim}, P.}, + title = "{Testing LSST Dither Strategies for Survey Uniformity and Large-scale Structure Systematics}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1605.00555}, + keywords = {dark energy, large-scale structure of universe, surveys}, + year = 2016, + month = sep, + volume = 829, + eid = {50}, + pages = {50}, + doi = {10.3847/0004-637X/829/1/50}, + adsurl = {http://adsabs.harvard.edu/abs/2016ApJ...829...50A}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%BBBBBBBBBBB +@ARTICLE{baldry2006a, + author = {{Baldry}, I.~K. and {Balogh}, M.~L. and {Bower}, R.~G. and {Glazebrook}, K. and + {Nichol}, R.~C. and {Bamford}, S.~P. and {Budavari}, T.}, + title = "{Galaxy bimodality versus stellar mass and environment}", + journal = {\mnras}, + eprint = {astro-ph/0607648}, + keywords = {galaxies: evolution, galaxies: fundamental parameters, galaxies: luminosity function, mass function}, + year = 2006, + month = dec, + volume = 373, + pages = {469-483}, + doi = {10.1111/j.1365-2966.2006.11081.x}, + adsurl = {http://adsabs.harvard.edu/abs/2006MNRAS.373..469B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{barth2007, + author = {{Barth}, A.~J.}, + title = "{A Normal Stellar Disk in the Galaxy Malin 1}", + journal = {\aj}, + eprint = {astro-ph/0701018}, + keywords = {galaxies: individual: Malin 1, galaxies: spiral, galaxies: structure}, + year = 2007, + month = mar, + volume = 133, + pages = {1085-1091}, + doi = {10.1086/511180}, + adsurl = {http://cdsads.u-strasbg.fr/abs/2007AJ....133.1085B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{bellagamba2017a, + author = {{Bellagamba}, F. and {Roncarelli}, M. and {Maturi}, M. and {Moscardini}, L. + }, + title = "{AMICO: optimised detection of galaxy clusters in photometric surveys}", + journal = {ArXiv e-prints}, +archivePrefix = "arXiv", + eprint = {1705.03029}, + keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies}, + year = 2017, + month = may, + adsurl = {http://adsabs.harvard.edu/abs/2017arXiv170503029B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{bowler2017a, + author = {{Bowler}, R.~A.~A. and {Dunlop}, J.~S. and {McLure}, R.~J. and + {McLeod}, D.~J.}, + title = "{Unveiling the nature of bright z {\sime} 7 galaxies with the Hubble Space Telescope}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1605.05325}, + keywords = {galaxies: evolution, galaxies: formation, galaxies: high-redshift}, + year = 2017, + month = apr, + volume = 466, + pages = {3612-3635}, + doi = {10.1093/mnras/stw3296}, + adsurl = {http://adsabs.harvard.edu/abs/2017MNRAS.466.3612B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{bullock2005a, + author = {{Bullock}, J.~S. and {Johnston}, K.~V.}, + title = "{Tracing Galaxy Formation with Stellar Halos. I. Methods}", + journal = {\apj}, + eprint = {astro-ph/0506467}, + keywords = {Cosmology: Dark Matter, Galaxies: Dwarf, Galaxies: Evolution, Galaxies: Formation, Galaxies: Halos, Galaxies: Kinematics and Dynamics, Galaxy: Evolution, Galaxy: Formation, Galaxy: Halo, Galaxy: Kinematics and Dynamics, Galaxies: Local Group}, + year = 2005, + month = dec, + volume = 635, + pages = {931-949}, + doi = {10.1086/497422}, + adsurl = {http://adsabs.harvard.edu/abs/2005ApJ...635..931B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%CCCCCCCCCCC +@ARTICLE{chiang2014a, + author = {{Chiang}, Y.-K. and {Overzier}, R. and {Gebhardt}, K.}, + title = "{Discovery of a Large Number of Candidate Protoclusters Traced by \~{}15 Mpc-scale Galaxy Overdensities in COSMOS}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1312.4747}, + keywords = {cosmology: observations, galaxies: clusters: general, galaxies: evolution, galaxies: high-redshift}, + year = 2014, + month = feb, + volume = 782, + eid = {L3}, + pages = {L3}, + doi = {10.1088/2041-8205/782/1/L3}, + adsurl = {http://adsabs.harvard.edu/abs/2014ApJ...782L...3C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{choi2012a, + author = {{Choi}, A. and {Tyson}, J.~A. and {Morrison}, C.~B. and {Jee}, M.~J. and + {Schmidt}, S.~J. and {Margoniner}, V.~E. and {Wittman}, D.~M. + }, + title = "{Galaxy-Mass Correlations on 10 Mpc Scales in the Deep Lens Survey}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1208.3904}, + keywords = {cosmology: observations, dark matter, galaxies: evolution, gravitational lensing: weak, large-scale structure of universe}, + year = 2012, + month = nov, + volume = 759, + eid = {101}, + pages = {101}, + doi = {10.1088/0004-637X/759/2/101}, + adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...759..101C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{conselice2000a, + author = {{Conselice}, C.~J. and {Bershady}, M.~A. and {Jangren}, A.}, + title = "{The Asymmetry of Galaxies: Physical Morphology for Nearby and High-Redshift Galaxies}", + journal = {\apj}, + eprint = {astro-ph/9907399}, + keywords = {GALAXIES: PHOTOMETRY, GALAXIES: STRUCTURE, Galaxies: Photometry, Galaxies: Structure}, + year = 2000, + month = feb, + volume = 529, + pages = {886-910}, + doi = {10.1086/308300}, + adsurl = {http://adsabs.harvard.edu/abs/2000ApJ...529..886C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{conselice2003a, + author = {{Conselice}, C.~J. and {Bershady}, M.~A. and {Dickinson}, M. and + {Papovich}, C.}, + title = "{A Direct Measurement of Major Galaxy Mergers at z{\lt}\~{}3}", + journal = {\aj}, + eprint = {astro-ph/0306106}, + keywords = {Galaxies: Evolution, Galaxies: Formation, Galaxies: Interactions}, + year = 2003, + month = sep, + volume = 126, + pages = {1183-1207}, + doi = {10.1086/377318}, + adsurl = {http://adsabs.harvard.edu/abs/2003AJ....126.1183C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{cooper2010a, + author = {{Cooper}, M.~C. and {Coil}, A.~L. and {Gerke}, B.~F. and {Newman}, J.~A. and + {Bundy}, K. and {Conselice}, C.~J. and {Croton}, D.~J. and {Davis}, M. and + {Faber}, S.~M. and {Guhathakurta}, P. and {Koo}, D.~C. and {Lin}, L. and + {Weiner}, B.~J. and {Willmer}, C.~N.~A. and {Yan}, R.}, + title = "{Absence of evidence is not evidence of absence: the colour-density relation at fixed stellar mass persists to z \~{} 1}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1007.1967}, + primaryClass = "astro-ph.CO", + keywords = {galaxies: evolution, formation, statistics, large-scale structure of Universe}, + year = 2010, + month = nov, + volume = 409, + pages = {337-345}, + doi = {10.1111/j.1365-2966.2010.17312.x}, + adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.409..337C}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%DDDDDDDDDDD +@ARTICLE{darg2010a, + author = {{Darg}, D.~W. and {Kaviraj}, S. and {Lintott}, C.~J. and {Schawinski}, K. and + {Sarzi}, M. and {Bamford}, S. and {Silk}, J. and {Andreescu}, D. and + {Murray}, P. and {Nichol}, R.~C. and {Raddick}, M.~J. and {Slosar}, A. and + {Szalay}, A.~S. and {Thomas}, D. and {Vandenberg}, J.}, + title = "{Galaxy Zoo: the properties of merging galaxies in the nearby Universe - local environments, colours, masses, star formation rates and AGN activity}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {0903.5057}, + keywords = {catalogues, galaxies: elliptical and lenticular, cD, galaxies: evolution, galaxies: general, galaxies: interactions, galaxies: spiral}, + year = 2010, + month = jan, + volume = 401, + pages = {1552-1563}, + doi = {10.1111/j.1365-2966.2009.15786.x}, + adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.401.1552D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{dejong2015a, + author = {{de Jong}, J.~T.~A. and {Verdoes Kleijn}, G.~A. and {Boxhoorn}, D.~R. and + {Buddelmeijer}, H. and {Capaccioli}, M. and {Getman}, F. and + {Grado}, A. and {Helmich}, E. and {Huang}, Z. and {Irisarri}, N. and + {Kuijken}, K. and {La Barbera}, F. and {McFarland}, J.~P. and + {Napolitano}, N.~R. and {Radovich}, M. and {Sikkema}, G. and + {Valentijn}, E.~A. and {Begeman}, K.~G. and {Brescia}, M. and + {Cavuoti}, S. and {Choi}, A. and {Cordes}, O.-M. and {Covone}, G. and + {Dall'Ora}, M. and {Hildebrandt}, H. and {Longo}, G. and {Nakajima}, R. and + {Paolillo}, M. and {Puddu}, E. and {Rifatto}, A. and {Tortora}, C. and + {van Uitert}, E. and {Buddendiek}, A. and {Harnois-D{\'e}raps}, J. and + {Erben}, T. and {Eriksen}, M.~B. and {Heymans}, C. and {Hoekstra}, H. and + {Joachimi}, B. and {Kitching}, T.~D. and {Klaes}, D. and {Koopmans}, L.~V.~E. and + {K{\"o}hlinger}, F. and {Roy}, N. and {Sif{\'o}n}, C. and {Schneider}, P. and + {Sutherland}, W.~J. and {Viola}, M. and {Vriend}, W.-J.}, + title = "{The first and second data releases of the Kilo-Degree Survey}", + journal = {\aap}, +archivePrefix = "arXiv", + eprint = {1507.00742}, + keywords = {methods: observational, surveys, galaxies: general, large-scale structure of Universe}, + year = 2015, + month = oct, + volume = 582, + eid = {A62}, + pages = {A62}, + doi = {10.1051/0004-6361/201526601}, + adsurl = {http://adsabs.harvard.edu/abs/2015A%26A...582A..62D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{driver2009a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2009A%26G....50e..12D}, + Archiveprefix = {arXiv}, + Author = {{Driver}, S.~P. and {Norberg}, P. and {Baldry}, I.~K. and {Bamford}, S.~P. and {Hopkins}, A.~M. and {Liske}, J. and {Loveday}, J. and {Peacock}, J.~A. and {Hill}, D.~T. and {Kelvin}, L.~S. and {Robotham}, A.~S.~G. and {Cross}, N.~J.~G. and {Parkinson}, H.~R. and {Prescott}, M. and {Conselice}, C.~J. and {Dunne}, L. and {Brough}, S. and {Jones}, H. and {Sharp}, R.~G. and {van Kampen}, E. and {Oliver}, S. and {Roseboom}, I.~G. and {Bland-Hawthorn}, J. and {Croom}, S.~M. and {Ellis}, S. and {Cameron}, E. and {Cole}, S. and {Frenk}, C.~S. and {Couch}, W.~J. and {Alister}, W.~G. and {Proctor}, R. and {De Propris}, R. and {Doyle}, I.~F. and {Edmondson}, E.~M. and {Nichol}, R.~C. and {Thomas}, D. and {Eales}, S.~A. and {Jarvis}, M.~J. and {Kuijken}, K. and {Lahav}, O. and {Madore}, B.~F. and {Seibert}, M. and {Meyer}, M.~J. and {Staveley-Smith}, L. and {Phillipps}, S. and {Popescu}, C.~C. and {Sansom}, A.~E. and {Sutherland}, W.~J. and {Tuffs}, R.~J. and {Warren}, S.~J.}, + Date-Added = {2017-04-25 15:30:19 +0000}, + Date-Modified = {2017-04-25 15:30:19 +0000}, + Doi = {10.1111/j.1468-4004.2009.50512.x}, + Eprint = {0910.5123}, + Journal = {Astronomy and Geophysics}, + Month = oct, + Number = 5, + Pages = {050000-5}, + Title = {{GAMA: towards a physical understanding of galaxy formation}}, + Volume = 50, + Year = 2009 +} +@ARTICLE{driver2011a, + author = {{Driver}, S.~P. and {Hill}, D.~T. and {Kelvin}, L.~S. and {Robotham}, A.~S.~G. and + {Liske}, J. and {Norberg}, P. and {Baldry}, I.~K. and {Bamford}, S.~P. and + {Hopkins}, A.~M. and {Loveday}, J. and {Peacock}, J.~A. and + {Andrae}, E. and {Bland-Hawthorn}, J. and {Brough}, S. and {Brown}, M.~J.~I. and + {Cameron}, E. and {Ching}, J.~H.~Y. and {Colless}, M. and {Conselice}, C.~J. and + {Croom}, S.~M. and {Cross}, N.~J.~G. and {de Propris}, R. and + {Dye}, S. and {Drinkwater}, M.~J. and {Ellis}, S. and {Graham}, A.~W. and + {Grootes}, M.~W. and {Gunawardhana}, M. and {Jones}, D.~H. and + {van Kampen}, E. and {Maraston}, C. and {Nichol}, R.~C. and + {Parkinson}, H.~R. and {Phillipps}, S. and {Pimbblet}, K. and + {Popescu}, C.~C. and {Prescott}, M. and {Roseboom}, I.~G. and + {Sadler}, E.~M. and {Sansom}, A.~E. and {Sharp}, R.~G. and {Smith}, D.~J.~B. and + {Taylor}, E. and {Thomas}, D. and {Tuffs}, R.~J. and {Wijesinghe}, D. and + {Dunne}, L. and {Frenk}, C.~S. and {Jarvis}, M.~J. and {Madore}, B.~F. and + {Meyer}, M.~J. and {Seibert}, M. and {Staveley-Smith}, L. and + {Sutherland}, W.~J. and {Warren}, S.~J.}, + title = "{Galaxy and Mass Assembly (GAMA): survey diagnostics and core data release}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1009.0614}, + keywords = {surveys, galaxies: distances and redshifts, galaxies: fundamental parameters, galaxies: general, galaxies: statistics}, + year = 2011, + month = may, + volume = 413, + pages = {971-995}, + doi = {10.1111/j.1365-2966.2010.18188.x}, + adsurl = {http://adsabs.harvard.edu/abs/2011MNRAS.413..971D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{driver2016a, + author = {{Driver}, S.~P. and {Wright}, A.~H. and {Andrews}, S.~K. and + {Davies}, L.~J. and {Kafle}, P.~R. and {Lange}, R. and {Moffett}, A.~J. and + {Mannering}, E. and {Robotham}, A.~S.~G. and {Vinsen}, K. and + {Alpaslan}, M. and {Andrae}, E. and {Baldry}, I.~K. and {Bauer}, A.~E. and + {Bamford}, S.~P. and {Bland-Hawthorn}, J. and {Bourne}, N. and + {Brough}, S. and {Brown}, M.~J.~I. and {Cluver}, M.~E. and {Croom}, S. and + {Colless}, M. and {Conselice}, C.~J. and {da Cunha}, E. and + {De Propris}, R. and {Drinkwater}, M. and {Dunne}, L. and {Eales}, S. and + {Edge}, A. and {Frenk}, C. and {Graham}, A.~W. and {Grootes}, M. and + {Holwerda}, B.~W. and {Hopkins}, A.~M. and {Ibar}, E. and {van Kampen}, E. and + {Kelvin}, L.~S. and {Jarrett}, T. and {Jones}, D.~H. and {Lara-Lopez}, M.~A. and + {Liske}, J. and {Lopez-Sanchez}, A.~R. and {Loveday}, J. and + {Maddox}, S.~J. and {Madore}, B. and {Mahajan}, S. and {Meyer}, M. and + {Norberg}, P. and {Penny}, S.~J. and {Phillipps}, S. and {Popescu}, C. and + {Tuffs}, R.~J. and {Peacock}, J.~A. and {Pimbblet}, K.~A. and + {Prescott}, M. and {Rowlands}, K. and {Sansom}, A.~E. and {Seibert}, M. and + {Smith}, M.~W.~L. and {Sutherland}, W.~J. and {Taylor}, E.~N. and + {Valiante}, E. and {Vazquez-Mata}, J.~A. and {Wang}, L. and + {Wilkins}, S.~M. and {Williams}, R.}, + title = "{Galaxy And Mass Assembly (GAMA): Panchromatic Data Release (far-UV-far-IR) and the low-z energy budget}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1508.02076}, + keywords = {astronomical data bases: miscellaneous, galaxies: evolution, galaxies: general, galaxies: photometry, cosmology: observations}, + year = 2016, + month = feb, + volume = 455, + pages = {3911-3942}, + doi = {10.1093/mnras/stv2505}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.455.3911D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@article{duffy2012a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2012MNRAS.426.3385D}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1208.5592}, + Author = {{Duffy}, A.~R. and {Meyer}, M.~J. and {Staveley-Smith}, L. and {Bernyk}, M. and {Croton}, D.~J. and {Koribalski}, B.~S. and {Gerstmann}, D. and {Westerlund}, S.}, + Date-Added = {2017-04-25 15:30:27 +0000}, + Date-Modified = {2017-04-25 15:30:27 +0000}, + Doi = {10.1111/j.1365-2966.2012.21987.x}, + Eprint = {1208.5592}, + Journal = {\mnras}, + Keywords = {galaxies: evolution, galaxies: luminosity function, mass function, radio lines: galaxies}, + Month = nov, + Pages = {3385-3402}, + Primaryclass = {astro-ph.CO}, + Title = {{Predictions for ASKAP neutral hydrogen surveys}}, + Volume = 426, + Year = 2012 +} +%FFFFFFFFFFF +@article{fernandez2013a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2013arXiv1303.2659F}, + Archiveprefix = {arXiv}, + Author = {{Fern{\'a}ndez}, X. and {van Gorkom}, J.~H. and {Hess}, K.~M. and {Pisano}, D.~J. and {Kreckel}, K. and {Momjian}, E. and {Popping}, A. and {Oosterloo}, T. and {Chomiuk}, L. and {Verheijen}, M.~A.~W. and {Henning}, P.~A. and {Schiminovich}, D. and {Bershady}, M.~A. and {Wilcots}, E.~M. and {Scoville}, N.}, + Date-Added = {2017-04-25 15:27:22 +0000}, + Date-Modified = {2017-04-25 15:27:22 +0000}, + Eprint = {1303.2659}, + Journal = {arXiv:1303.2659}, + Keywords = {Astrophysics - Galaxy Astrophysics, Astrophysics - Cosmology and Extragalactic Astrophysics}, + Month = mar, + Primaryclass = {astro-ph.GA}, + Title = {{A Pilot for a VLA HI Deep Field}}, + Year = 2013 +} +@article{fernandez2016a, + Author = {{Fern{\'a}ndez}, X. and {Gim}, H.~B. and {van Gorkom}, J.~H. and {Yun}, M.~S. and {Momjian}, E. and {Popping}, A. and {Chomiuk}, L. and {Hess}, K.~M. and {Hunt}, L. and {Kreckel}, K. and {Lucero}, D. and {Maddox}, N. and {Oosterloo}, T. and {Pisano}, D.~J. and {Verheijen}, M.~A.~W. and {Hales}, C.~A. and {Chung}, A. and {Dodson}, R. and {Golap}, K. and {Gross}, J. and {Henning}, P. and {Hibbard}, J. and {Jaff{\'e}}, Y.~L. and {Donovan Meyer}, J. and {Meyer}, M. and {Sanchez-Barrantes}, M. and {Schiminovich}, D. and {Wicenec}, A. and {Wilcots}, E. and {Bershady}, M. and {Scoville}, N. and {Strader}, J. and {Tremou}, E. and {Salinas}, R. and {Ch{\'a}vez}, R.}, + Date-Added = {2017-04-25 15:27:24 +0000}, + Date-Modified = {2017-04-25 15:27:24 +0000}, + Doi = {10.3847/2041-8205/824/1/L1}, + Eid = {L1}, + Journal = {\apjl}, + Keywords = {galaxies: evolution, galaxies: starburst, radio lines: galaxies}, + Month = jun, + Pages = {L1}, + Title = {{Highest Redshift Image of Neutral Hydrogen in Emission: A CHILES Detection of a Starbursting Galaxy at z = 0.376}}, + Volume = 824, + Year = 2016 +} +@ARTICLE{flaugher2005a, + author = {{Flaugher}, B.}, + title = "{The Dark Energy Survey}", + journal = {International Journal of Modern Physics A}, + keywords = {Dark energy, galaxies, supernovae}, + year = 2005, + volume = 20, + pages = {3121-3123}, + doi = {10.1142/S0217751X05025917}, + adsurl = {http://adsabs.harvard.edu/abs/2005IJMPA..20.3121F}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%GGGGGGGGGGGGGG +@ARTICLE{galaz2015a, + author = {{Galaz}, G. and {Milovic}, C. and {Suc}, V. and {Busta}, L. and + {Lizana}, G. and {Infante}, L. and {Royo}, S.}, + title = "{Deep Optical Images of Malin 1 Reveal New Features}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1512.01095}, + keywords = {galaxies: general, galaxies: spiral, techniques: image processing}, + year = 2015, + month = dec, + volume = 815, + eid = {L29}, + pages = {L29}, + doi = {10.1088/2041-8205/815/2/L29}, + adsurl = {http://cdsads.u-strasbg.fr/abs/2015ApJ...815L..29G}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@article{glazebrook2013a, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1305.2469}, + Author = {{Glazebrook}, K.}, + Date-Added = {2017-04-25 15:25:24 +0000}, + Date-Modified = {2017-04-25 15:25:24 +0000}, + Doi = {10.1017/pasa.2013.34}, + Eid = {e056}, + Eprint = {1305.2469}, + Journal = {\pasa}, + Keywords = {galaxies: evolution, galaxies: formation, galaxies: high-redshift, galaxies: kinematics and dynamics, galaxies: stellar content, galaxies: structure}, + Month = nov, + Pages = {e056}, + Primaryclass = {astro-ph.CO}, + Title = {{The Dawes Review 1: Kinematic Studies of Star-Forming Galaxies Across Cosmic Time}}, + Volume = 30, + Year = 2013 +} + +@ARTICLE{grogin2011a, + author = {{Grogin}, N.~A. and {Kocevski}, D.~D. and {Faber}, S.~M. and + {Ferguson}, H.~C. and {Koekemoer}, A.~M. and {Riess}, A.~G. and + {Acquaviva}, V. and {Alexander}, D.~M. and {Almaini}, O. and + {Ashby}, M.~L.~N. and {Barden}, M. and {Bell}, E.~F. and {Bournaud}, F. and + {Brown}, T.~M. and {Caputi}, K.~I. and {Casertano}, S. and {Cassata}, P. and + {Castellano}, M. and {Challis}, P. and {Chary}, R.-R. and {Cheung}, E. and + {Cirasuolo}, M. and {Conselice}, C.~J. and {Roshan Cooray}, A. and + {Croton}, D.~J. and {Daddi}, E. and {Dahlen}, T. and {Dav{\'e}}, R. and + {de Mello}, D.~F. and {Dekel}, A. and {Dickinson}, M. and {Dolch}, T. and + {Donley}, J.~L. and {Dunlop}, J.~S. and {Dutton}, A.~A. and + {Elbaz}, D. and {Fazio}, G.~G. and {Filippenko}, A.~V. and {Finkelstein}, S.~L. and + {Fontana}, A. and {Gardner}, J.~P. and {Garnavich}, P.~M. and + {Gawiser}, E. and {Giavalisco}, M. and {Grazian}, A. and {Guo}, Y. and + {Hathi}, N.~P. and {H{\"a}ussler}, B. and {Hopkins}, P.~F. and + {Huang}, J.-S. and {Huang}, K.-H. and {Jha}, S.~W. and {Kartaltepe}, J.~S. and + {Kirshner}, R.~P. and {Koo}, D.~C. and {Lai}, K. and {Lee}, K.-S. and + {Li}, W. and {Lotz}, J.~M. and {Lucas}, R.~A. and {Madau}, P. and + {McCarthy}, P.~J. and {McGrath}, E.~J. and {McIntosh}, D.~H. and + {McLure}, R.~J. and {Mobasher}, B. and {Moustakas}, L.~A. and + {Mozena}, M. and {Nandra}, K. and {Newman}, J.~A. and {Niemi}, S.-M. and + {Noeske}, K.~G. and {Papovich}, C.~J. and {Pentericci}, L. and + {Pope}, A. and {Primack}, J.~R. and {Rajan}, A. and {Ravindranath}, S. and + {Reddy}, N.~A. and {Renzini}, A. and {Rix}, H.-W. and {Robaina}, A.~R. and + {Rodney}, S.~A. and {Rosario}, D.~J. and {Rosati}, P. and {Salimbeni}, S. and + {Scarlata}, C. and {Siana}, B. and {Simard}, L. and {Smidt}, J. and + {Somerville}, R.~S. and {Spinrad}, H. and {Straughn}, A.~N. and + {Strolger}, L.-G. and {Telford}, O. and {Teplitz}, H.~I. and + {Trump}, J.~R. and {van der Wel}, A. and {Villforth}, C. and + {Wechsler}, R.~H. and {Weiner}, B.~J. and {Wiklind}, T. and + {Wild}, V. and {Wilson}, G. and {Wuyts}, S. and {Yan}, H.-J. and + {Yun}, M.~S.}, + title = "{CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {1105.3753}, + primaryClass = "astro-ph.CO", + keywords = {cosmology: observations, galaxies: high-redshift}, + year = 2011, + month = dec, + volume = 197, + eid = {35}, + pages = {35}, + doi = {10.1088/0067-0049/197/2/35}, + adsurl = {http://adsabs.harvard.edu/abs/2011ApJS..197...35G}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%HHHHHHHHHHH +@ARTICLE{hocking2015a, + author = {{Hocking}, A. and {Geach}, J.~E. and {Davey}, N. and {Sun}, Y. + }, + title = "{Teaching a machine to see: unsupervised image segmentation and categorisation using growing neural gas and hierarchical clustering}", + journal = {arXiv:arXiv150701589}, +archivePrefix = "arXiv", + eprint = {1507.01589}, + primaryClass = "astro-ph.IM", + keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics}, + year = 2015, + month = jul, + adsurl = {http://adsabs.harvard.edu/abs/2015arXiv150701589H}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{hoekstra2015a, + author = {{Hoekstra}, H. and {Herbonnet}, R. and {Muzzin}, A. and {Babul}, A. and + {Mahdavi}, A. and {Viola}, M. and {Cacciato}, M.}, + title = "{The Canadian Cluster Comparison Project: detailed study of systematics and updated weak lensing masses}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1502.01883}, + keywords = {cosmology: observations, dark matter}, + year = 2015, + month = may, + volume = 449, + pages = {685-714}, + doi = {10.1093/mnras/stv275}, + adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.449..685H}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{holwerda2010a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2010iska.meetE..68H}, + Archiveprefix = {arXiv/1007.4101}, + Author = {{Holwerda}, B. and {Blyth}, S.}, + Date-Added = {2017-04-25 15:29:43 +0000}, + Date-Modified = {2017-04-25 15:29:43 +0000}, + Eprint = {1007.4101}, + journal = {arXiv:1007.4101}, + Primaryclass = {astro-ph.CO}, + Title = {{Trumpeting the Vuvuzela: The deepest HI observations with MeerKAT}}, + Year = 2010 +} +@inproceedings{holwerda2011a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2011AAS...21743317H}, + Author = {{Holwerda}, B.~W. and {Blyth}, S. and {Baker}, A.~J. and {MeerKAT Deep HI Survey Team}}, + Booktitle = {Abstract \#217}, + Date-Added = {2017-04-25 15:30:04 +0000}, + Date-Modified = {2017-04-25 15:30:04 +0000}, + Month = jan, + Pages = {\#433.17}, + Series = {Bulletin of the AAS}, + Title = {{A 5000-hour Meerkat Large Survey Project To Observe Hi To Z=1}}, + Volume = 43, + Year = 2011 +} +%IIIIIIIIIII +@ARTICLE{ivezic2008a, + author = {{Ivezic}, Z. and {Tyson}, J.~A. and {Abel}, B. and {Acosta}, E. and + {Allsman}, R. and {AlSayyad}, Y. and {Anderson}, S.~F. and {Andrew}, J. and + {Angel}, R. and {Angeli}, G. and {Ansari}, R. and {Antilogus}, P. and + {Arndt}, K.~T. and {Astier}, P. and {Aubourg}, E. and {Axelrod}, T. and + {Bard}, D.~J. and {Barr}, J.~D. and {Barrau}, A. and {Bartlett}, J.~G. and + {Bauman}, B.~J. and {Beaumont}, S. and {Becker}, A.~C. and {Becla}, J. and + {Beldica}, C. and {Bellavia}, S. and {Blanc}, G. and {Blandford}, R.~D. and + {Bloom}, J.~S. and {Bogart}, J. and {Borne}, K. and {Bosch}, J.~F. and + {Boutigny}, D. and {Brandt}, W.~N. and {Brown}, M.~E. and {Bullock}, 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Drivers to Reference Design and Anticipated Data Products}", + journal = {arXiv:0805.2366}, +archivePrefix = "arXiv", + eprint = {0805.2366}, + keywords = {Astrophysics}, + year = 2008, + month = may, + adsurl = {http://adsabs.harvard.edu/abs/2008arXiv0805.2366I}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%JJJJJJJJJJJ +@article{jarvis2012a, + Adsurl = {http://adsabs.harvard.edu/abs/2012AfrSk..16...44J}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1107.5165}, + Author = {{Jarvis}, M.~J.}, + Date-Added = {2017-04-25 15:27:37 +0000}, + Date-Modified = {2017-04-25 15:27:37 +0000}, + Eprint = {1107.5165}, + Journal = {African Skies}, + Keywords = {Astrophysics - Cosmology and Extragalactic Astrophysics}, + Month = mar, + Pages = {44}, + Primaryclass = {astro-ph.CO}, + Title = {{Multi-wavelength Extragalactic Surveys and the Role of MeerKAT and SALT}}, + Volume = 16, + Year = 2012 +} +@ARTICLE{johnston2007a, + author = {{Johnston}, S. and {Bailes}, 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Relating Substructure in Phase and Abundance Space to Accretion Histories}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {0807.3911}, + keywords = {Cosmology: Dark Matter, Galaxies: Dwarf, Galaxies: Evolution, Galaxies: Formation, Galaxies: Halos, Galaxies: Kinematics and Dynamics, Galaxy: Evolution, Galaxy: Formation, Galaxy: Halo, Galaxy: Kinematics and Dynamics, Galaxies: Local Group}, + year = 2008, + month = dec, + volume = 689, + pages = {936-957}, + doi = {10.1086/592228}, + adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...689..936J}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%KKKKKKKKKKK +@INPROCEEDINGS{kaiser2010a, + author = {{Kaiser}, N. and {Burgett}, W. and {Chambers}, K. and {Denneau}, L. and + {Heasley}, J. and {Jedicke}, R. and {Magnier}, E. and {Morgan}, J. and + {Onaka}, P. and {Tonry}, J.}, + title = "{The Pan-STARRS wide-field optical/NIR imaging survey}", +booktitle = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + year = 2010, + series = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + volume = 7733, + month = jul, + eid = {77330E}, + pages = {0}, + doi = {10.1117/12.859188}, + adsurl = {http://adsabs.harvard.edu/abs/2010SPIE.7733E..0EK}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kartaltepe2007a, + author = {{Kartaltepe}, J.~S. and {Sanders}, D.~B. and {Scoville}, N.~Z. and + {Calzetti}, D. and {Capak}, P. and {Koekemoer}, A. and {Mobasher}, B. and + {Murayama}, T. and {Salvato}, M. and {Sasaki}, S.~S. and {Taniguchi}, Y. + }, + title = "{Evolution of the Frequency of Luminous ({\gt}=L$^{*}$$_{V}$) Close Galaxy Pairs at z {\lt} 1.2 in the COSMOS Field}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {0705.2266}, + keywords = {Cosmology: Observations, Galaxies: Evolution, Galaxies: Formation, Galaxies: Interactions, Cosmology: Large-Scale Structure of Universe, Surveys}, + year = 2007, + month = sep, + volume = 172, + pages = {320-328}, + doi = {10.1086/519953}, + adsurl = {http://adsabs.harvard.edu/abs/2007ApJS..172..320K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2005a, + author = {{Kaviraj}, S. and {Devriendt}, J.~E.~G. and {Ferreras}, I. and + {Yi}, S.~K.}, + title = "{The elliptical galaxy colour-magnitude relation as a discriminant between the monolithic and merger paradigms}", + journal = {\mnras}, + eprint = {astro-ph/0401126}, + keywords = {galaxies: elliptical and lenticular, cD, galaxies: evolution, galaxies: formation, galaxies: fundamental parameters}, + year = 2005, + month = jun, + volume = 360, + pages = {60-68}, + doi = {10.1111/j.1365-2966.2005.08883.x}, + adsurl = {http://adsabs.harvard.edu/abs/2005MNRAS.360...60K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2009a, + author = {{Kaviraj}, S. and {Peirani}, S. and {Khochfar}, S. and {Silk}, J. and + {Kay}, S.}, + title = "{The role of minor mergers in the recent star formation history of early-type galaxies}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {0711.1493}, + keywords = {methods: N-body simulations , galaxies: elliptical and lenticular, cD , galaxies: evolution , galaxies: formation}, + year = 2009, + month = apr, + volume = 394, + pages = {1713-1720}, + doi = {10.1111/j.1365-2966.2009.14403.x}, + adsurl = {http://adsabs.harvard.edu/abs/2009MNRAS.394.1713K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2014a, + author = {{Kaviraj}, S.}, + title = "{The significant contribution of minor mergers to the cosmic star formation budget}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1310.0007}, + keywords = {galaxies: elliptical and lenticular, cD, galaxies: evolution, galaxies: formation, galaxies: interactions, galaxies: starburst}, + year = 2014, + month = jan, + volume = 437, + pages = {L41-L45}, + doi = {10.1093/mnrasl/slt136}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.437L..41K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2014b, + author = {{Kaviraj}, S.}, + title = "{The importance of minor-merger-driven star formation and black hole growth in disc galaxies}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1402.1166}, + keywords = {galaxies: evolution, galaxies: formation, galaxies: interactions, galaxies: spiral}, + year = 2014, + month = jun, + volume = 440, + pages = {2944-2952}, + doi = {10.1093/mnras/stu338}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.440.2944K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2015a, + author = {{Kaviraj}, S. and {Devriendt}, J. and {Dubois}, Y. and {Slyz}, A. and + {Welker}, C. and {Pichon}, C. and {Peirani}, S. and {Le Borgne}, D. + }, + title = "{Galaxy merger histories and the role of merging in driving star formation at z $\gt$ 1}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1411.2595}, + keywords = {galaxies: evolution, galaxies: formation, galaxies: high-redshift, galaxies: interactions}, + year = 2015, + month = sep, + volume = 452, + pages = {2845-2850}, + doi = {10.1093/mnras/stv1500}, + adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.452.2845K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{kaviraj2017a, + author = {{Kaviraj}, S. and {Laigle}, C. and {Kimm}, T. and {Devriendt}, J.~E.~G. and + {Dubois}, Y. and {Pichon}, C. and {Slyz}, A. and {Chisari}, E. and + {Peirani}, S.}, + title = "{The Horizon-AGN simulation: evolution of galaxy properties over cosmic time}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1605.09379}, + keywords = {methods: numerical, galaxies: evolution, galaxies: formation, galaxies: high-redshift, cosmology: theory, large-scale structure of Universe}, + year = 2017, + month = jun, + volume = 467, + pages = {4739-4752}, + doi = {10.1093/mnras/stx126}, + adsurl = {http://adsabs.harvard.edu/abs/2017MNRAS.467.4739K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{koekemoer2011a, + author = {{Koekemoer}, A.~M. and {Faber}, S.~M. and {Ferguson}, H.~C. and + {Grogin}, N.~A. and {Kocevski}, D.~D. and {Koo}, D.~C. and {Lai}, K. and + {Lotz}, J.~M. and {Lucas}, R.~A. and {McGrath}, E.~J. and {Ogaz}, S. and + {Rajan}, A. and {Riess}, A.~G. and {Rodney}, S.~A. and {Strolger}, L. and + {Casertano}, S. and {Castellano}, M. and {Dahlen}, T. and {Dickinson}, M. and + {Dolch}, T. and {Fontana}, A. and {Giavalisco}, M. and {Grazian}, A. and + {Guo}, Y. and {Hathi}, N.~P. and {Huang}, K.-H. and {van der Wel}, A. and + {Yan}, H.-J. and {Acquaviva}, V. and {Alexander}, D.~M. and + {Almaini}, O. and {Ashby}, M.~L.~N. and {Barden}, M. and {Bell}, E.~F. and + {Bournaud}, F. and {Brown}, T.~M. and {Caputi}, K.~I. and {Cassata}, P. and + {Challis}, P.~J. and {Chary}, R.-R. and {Cheung}, E. and 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+ year = 2011, + month = dec, + volume = 197, + eid = {36}, + pages = {36}, + doi = {10.1088/0067-0049/197/2/36}, + adsurl = {http://adsabs.harvard.edu/abs/2011ApJS..197...36K}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%HHHHHHHHHHH +@ARTICLE{heckman2005a, + author = {{Heckman}, T.~M. and {Hoopes}, C.~G. and {Seibert}, M. and {Martin}, D.~C. and + {Salim}, S. and {Rich}, R.~M. and {Kauffmann}, G. and {Charlot}, S. and + {Barlow}, T.~A. and {Bianchi}, L. and {Byun}, Y.-I. and {Donas}, J. and + {Forster}, K. and {Friedman}, P.~G. and {Jelinsky}, P.~N. and + {Lee}, Y.-W. and {Madore}, B.~F. and {Malina}, R.~F. and {Milliard}, B. and + {Morrissey}, P.~F. and {Neff}, S.~G. and {Schiminovich}, D. and + {Siegmund}, O.~H.~W. and {Small}, T. and {Szalay}, A.~S. and + {Welsh}, B.~Y. and {Wyder}, T.~K.}, + title = "{The Properties of Ultraviolet-luminous Galaxies at the Current Epoch}", + journal = {\apjl}, + eprint = {astro-ph/0412577}, + keywords = {Galaxies: Evolution, Galaxies: General, Galaxies: Starburst, Ultraviolet: Galaxies}, + year = 2005, + month = jan, + volume = 619, + pages = {L35-L38}, + doi = {10.1086/425979}, + adsurl = {http://adsabs.harvard.edu/abs/2005ApJ...619L..35H}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%LLLLLLLLLLL +@ARTICLE{leauthaud2012a, + author = {{Leauthaud}, A. and {Tinker}, J. and {Bundy}, K. and {Behroozi}, P.~S. and + {Massey}, R. and {Rhodes}, J. and {George}, M.~R. and {Kneib}, J.-P. and + {Benson}, A. and {Wechsler}, R.~H. and {Busha}, M.~T. and {Capak}, P. and + {Cort{\^e}s}, M. and {Ilbert}, O. and {Koekemoer}, A.~M. and + {Le F{\`e}vre}, O. and {Lilly}, S. and {McCracken}, H.~J. and + {Salvato}, M. and {Schrabback}, T. and {Scoville}, N. and {Smith}, T. and + {Taylor}, J.~E.}, + title = "{New Constraints on the Evolution of the Stellar-to-dark Matter Connection: A Combined Analysis of Galaxy-Galaxy Lensing, Clustering, and Stellar Mass Functions from z = 0.2 to z =1}", + 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+ keywords = {surveys, galaxies: distances and redshifts, galaxies: fundamental parameters, galaxies: general, galaxies: photometry, galaxies: statistics}, + year = 2015, + month = sep, + volume = 452, + pages = {2087-2126}, + doi = {10.1093/mnras/stv1436}, + adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.452.2087L}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{lofthouse2017a, + author = {{Lofthouse}, E.~K. and {Kaviraj}, S. and {Conselice}, C.~J. and + {Mortlock}, A. and {Hartley}, W.}, + title = "{Major mergers are not significant drivers of star formation or morphological transformation around the epoch of peak cosmic star formation}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1608.03892}, + keywords = {galaxies: elliptical and lenticular, CD, galaxies: evolution, galaxies: formation, galaxies: high-redshift, galaxies: interactions}, + year = 2017, + month = mar, + volume = 465, + pages = {2895-2900}, + doi = 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Date-Modified = {2017-04-25 15:26:41 +0000}, + Doi = {10.1086/312628}, + Eprint = {arXiv:astro-ph/0003001}, + Journal = {\apjl}, + Keywords = {COSMOLOGY: DARK MATTER, GALAXIES: DWARF, GALAXIES: FORMATION, GALAXIES: FUNDAMENTAL PARAMETERS, GALAXIES: KINEMATICS AND DYNAMICS, GALAXIES: SPIRAL}, + Month = apr, + Pages = {L99-L102}, + Title = {{The Baryonic Tully-Fisher Relation}}, + Volume = 533, + Year = 2000 +} +@article{meyer2015a, + Adscomment = {to be published in: 'Advancing Astrophysics with the Square Kilometre Array', Proceedings of Science, PoS(AASKA14)131}, + Adsurl = {http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1501.01082}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1501.01082v1}, + Author = {{Meyer}, Martin and {Robotham}, Aaron and {Obreschkow}, Danail and {Driver}, Simon and {Staveley-Smith}, Lister and {Zwaan}, Martin}, + Date-Added = {2017-04-25 15:30:42 +0000}, + Date-Modified = {2017-04-25 15:30:42 +0000}, + Eprint = {1501.01082v1}, + Journal = {arXiv:1501.01082}, + Month = {Jan}, + Primaryclass = {astro-ph.GA}, + Title = {Connecting the Baryons: Multiwavelength Data for SKA HI Surveys}, + Year = {2015} +} +@article{meyer2016a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.455.3136M}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1510.07785}, + Author = {{Meyer}, S.~A. and {Meyer}, M. and {Obreschkow}, D. and {Staveley-Smith}, L.}, + Date-Added = {2017-04-25 15:25:50 +0000}, + Date-Modified = {2017-04-25 15:25:50 +0000}, + Doi = {10.1093/mnras/stv2458}, + Eprint = {1510.07785}, + Journal = {\mnras}, + Keywords = {galaxies: evolution, galaxies: fundamental parameters, galaxies: kinematics and dynamics, galaxies: spiral, dark matter, radio lines: galaxies}, + Month = jan, + Pages = {3136-3147}, + Title = {{Extended Tully-Fisher relations using H I stacking}}, + Volume = 455, + Year = 2016 +} +@INPROCEEDINGS{miyazaki2012a, + author = {{Miyazaki}, S. and {Komiyama}, Y. and {Nakaya}, H. and {Kamata}, Y. and + {Doi}, Y. and {Hamana}, T. and {Karoji}, H. and {Furusawa}, H. and + {Kawanomoto}, S. and {Morokuma}, T. and {Ishizuka}, Y. and {Nariai}, K. and + {Tanaka}, Y. and {Uraguchi}, F. and {Utsumi}, Y. and {Obuchi}, Y. and + {Okura}, Y. and {Oguri}, M. and {Takata}, T. and {Tomono}, D. and + {Kurakami}, T. and {Namikawa}, K. and {Usuda}, T. and {Yamanoi}, H. and + {Terai}, T. and {Uekiyo}, H. and {Yamada}, Y. and {Koike}, M. and + {Aihara}, H. and {Fujimori}, Y. and {Mineo}, S. and {Miyatake}, H. and + {Yasuda}, N. and {Nishizawa}, J. and {Saito}, T. and {Tanaka}, M. and + {Uchida}, T. and {Katayama}, N. and {Wang}, S.-Y. and {Chen}, H.-Y. and + {Lupton}, R. and {Loomis}, C. and {Bickerton}, S. and {Price}, P. and + {Gunn}, J. and {Suzuki}, H. and {Miyazaki}, Y. and {Muramatsu}, M. and + {Yamamoto}, K. and {Endo}, M. and {Ezaki}, Y. and {Itoh}, N. and + {Miwa}, Y. and {Yokota}, H. and {Matsuda}, T. and {Ebinuma}, R. and + {Takeshi}, K.}, + title = "{Hyper Suprime-Cam}", +booktitle = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + year = 2012, + series = {Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series}, + volume = 8446, + month = sep, + eid = {84460Z}, + pages = {0}, + doi = {10.1117/12.926844}, + adsurl = {http://adsabs.harvard.edu/abs/2012SPIE.8446E..0ZM}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%NNNNNNNNNNN +@ARTICLE{newman2008a, + author = {{Newman}, J.~A.}, + title = "{Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross-Correlations}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {0805.1409}, + keywords = {galaxies: distances and redshifts, large-scale structure of universe, methods: miscellaneous, surveys}, + year = 2008, + month = sep, + volume = 684, + eid = {88-101}, + pages = {88-101}, + doi = {10.1086/589982}, + adsurl = {http://adsabs.harvard.edu/abs/2008ApJ...684...88N}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{newman2015a, + author = {{Newman}, J.~A. and {Abate}, A. and {Abdalla}, F.~B. and {Allam}, S. and + {Allen}, S.~W. and {Ansari}, R. and {Bailey}, S. and {Barkhouse}, W.~A. and + {Beers}, T.~C. and {Blanton}, M.~R. and {Brodwin}, M. and {Brownstein}, J.~R. and + {Brunner}, R.~J. and {Carrasco Kind}, M. and {Cervantes-Cota}, J.~L. and + {Cheu}, E. and {Chisari}, N.~E. and {Colless}, M. and {Comparat}, J. and + {Coupon}, J. and {Cunha}, C.~E. and {de la Macorra}, A. and + {Dell'Antonio}, I.~P. and {Frye}, B.~L. and {Gawiser}, E.~J. and + {Gehrels}, N. and {Grady}, K. and {Hagen}, A. and {Hall}, P.~B. and + {Hearin}, A.~P. and {Hildebrandt}, H. and {Hirata}, C.~M. and + {Ho}, S. and {Honscheid}, K. and {Huterer}, D. and {Ivezi{\'c}}, {\v Z}. and + {Kneib}, J.-P. and {Kruk}, J.~W. and {Lahav}, O. and {Mandelbaum}, R. and + {Marshall}, J.~L. and {Matthews}, D.~J. and {M{\'e}nard}, B. and + {Miquel}, R. and {Moniez}, M. and {Moos}, H.~W. and {Moustakas}, J. and + {Myers}, A.~D. and {Papovich}, C. and {Peacock}, J.~A. and {Park}, C. and + {Rahman}, M. and {Rhodes}, J. and {Ricol}, J.-S. and {Sadeh}, I. and + {Slozar}, A. and {Schmidt}, S.~J. and {Stern}, D.~K. and {Anthony Tyson}, J. and + {von der Linden}, A. and {Wechsler}, R.~H. and {Wood-Vasey}, W.~M. and + {Zentner}, A.~R.}, + title = "{Spectroscopic needs for imaging dark energy experiments}", + journal = {Astroparticle Physics}, +archivePrefix = "arXiv", + eprint = {1309.5384}, + keywords = {Cosmology, Dark energy, Surveys}, + year = 2015, + month = mar, + volume = 63, + pages = {81-100}, + doi = {10.1016/j.astropartphys.2014.06.007}, + adsurl = {http://adsabs.harvard.edu/abs/2015APh....63...81N}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{noeske2007a, + author = {{Noeske}, K.~G. and {Weiner}, B.~J. and {Faber}, S.~M. and {Papovich}, C. and + {Koo}, D.~C. and {Somerville}, R.~S. and {Bundy}, K. and {Conselice}, C.~J. and + {Newman}, J.~A. and {Schiminovich}, D. and {Le Floc'h}, E. and + {Coil}, A.~L. and {Rieke}, G.~H. and {Lotz}, J.~M. and {Primack}, J.~R. and + {Barmby}, P. and {Cooper}, M.~C. and {Davis}, M. and {Ellis}, R.~S. and + {Fazio}, G.~G. and {Guhathakurta}, P. and {Huang}, J. and {Kassin}, S.~A. and + {Martin}, D.~C. and {Phillips}, A.~C. and {Rich}, R.~M. and + {Small}, T.~A. and {Willmer}, C.~N.~A. and {Wilson}, G.}, + title = "{Star Formation in AEGIS Field Galaxies since z=1.1: The Dominance of Gradually Declining Star Formation, and the Main Sequence of Star-forming Galaxies}", + journal = {\apjl}, + eprint = {astro-ph/0701924}, + keywords = {Galaxies: Evolution, Galaxies: Formation, Galaxies: High-Redshift, Galaxies: Starburst}, + year = 2007, + month = may, + volume = 660, + pages = {L43-L46}, + doi = {10.1086/517926}, + adsurl = {http://adsabs.harvard.edu/abs/2007ApJ...660L..43N}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%OOOOOOOOOOO +@article{oh2015a, + Adscomment = {100 pages, 85 figures, Accepted for publication on AJ}, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2015arXiv150201281O}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arXiv.org/abs/1502.01281}, + Author = {{Oh}, S.-H. and {Hunter}, D.~A. and {Brinks}, E. and {Elmegreen}, B.~G. and {Schruba}, A. and {Walter}, F. and {Rupen}, M.~P. and {Young}, L.~M. and {Simpson}, C.~E. and {Johnson}, M. and {Herrmann}, K.~A. and {Ficut-Vicas}, D. and {Cigan}, P. and {Heesen}, V. and {Ashley}, T. and {Zhang}, H.-X.}, + Date-Added = {2017-04-25 15:26:51 +0000}, + Date-Modified = {2017-04-25 15:26:51 +0000}, + Eprint = {1502.01281}, + Journal = {arXiv:1502.01281}, + Keywords = {Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics}, + Month = feb, + Title = {{High-resolution mass models of dwarf galaxies from LITTLE THINGS}}, + Year = 2015 +} +@ARTICLE{okabe2013a, + author = {{Okabe}, N. and {Smith}, G.~P. and {Umetsu}, K. and {Takada}, M. and + {Futamase}, T.}, + title = "{LoCuSS: The Mass Density Profile of Massive Galaxy Clusters at z = 0.2}", + journal = {\apjl}, +archivePrefix = "arXiv", + eprint = {1302.2728}, + keywords = {cosmology: observations, galaxies: clusters: general, gravitational lensing: weak }, + year = 2013, + month = jun, + volume = 769, + eid = {L35}, + pages = {L35}, + doi = {10.1088/2041-8205/769/2/L35}, + adsurl = {http://adsabs.harvard.edu/abs/2013ApJ...769L..35O}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{okabe2016a, + author = {{Okabe}, N. and {Smith}, G.~P.}, + title = "{LoCuSS: weak-lensing mass calibration of galaxy clusters}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1507.04493}, + keywords = {gravitational lensing: weak}, + year = 2016, + month = oct, + volume = 461, + pages = {3794-3821}, + doi = {10.1093/mnras/stw1539}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.461.3794O}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +%PPPPPPPPPPP +@ARTICLE{pasquali2010a, + author = {{Pasquali}, A. and {Gallazzi}, A. and {Fontanot}, F. and {van den Bosch}, F.~C. and + {De Lucia}, G. and {Mo}, H.~J. and {Yang}, X.}, + title = "{Ages and metallicities of central and satellite galaxies: implications for galaxy formation and evolution}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {0912.1853}, + keywords = {galaxies: clusters: general, galaxies: evolution, galaxies: general, galaxies: statistics, galaxies: stellar content, dark matter}, + year = 2010, + month = sep, + volume = 407, + pages = {937-954}, + doi = {10.1111/j.1365-2966.2010.17074.x}, + adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.407..937P}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{ponomareva2016a, + Adscomment = {50 pages, 9 figures, 32 atlas figures. Accepted for publication in MNRAS}, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2016arXiv160900378P}, + Archiveprefix = {arXiv}, + Arxivurl = {http://arxiv.org/abs/1609.00378}, + Author = {{Ponomareva}, A.~A. and {Verheijen}, M.~A.~W. and {Bosma}, A.}, + Date-Added = {2017-04-25 15:24:09 +0000}, + Date-Modified = {2017-04-25 15:24:09 +0000}, + Eprint = {1609.00378}, + Journal = {arXiv:1609.00378}, + Keywords = {Astrophysics - Astrophysics of Galaxies}, + Month = sep, + Title = {{Detailed HI kinematics of Tully-Fisher calibrator galaxies}}, + Year = 2016, +} +%RRRRRRRRRRR +@ARTICLE{richards2006a, + author = {{Richards}, G.~T. and {Lacy}, M. and {Storrie-Lombardi}, L.~J. and + {Hall}, P.~B. and {Gallagher}, S.~C. and {Hines}, D.~C. and + {Fan}, X. and {Papovich}, C. and {Vanden Berk}, D.~E. and {Trammell}, G.~B. and + {Schneider}, D.~P. and {Vestergaard}, M. and {York}, D.~G. and + {Jester}, S. and {Anderson}, S.~F. and {Budav{\'a}ri}, T. and + {Szalay}, A.~S.}, + title = "{Spectral Energy Distributions and Multiwavelength Selection of Type 1 Quasars}", + journal = {\apjs}, + eprint = {astro-ph/0601558}, + keywords = {Catalogs, Galaxies: Active, Infrared: Galaxies, Galaxies: Quasars: General, Radio Continuum: Galaxies, Surveys, Ultraviolet: Galaxies, X-Rays: Galaxies}, + year = 2006, + month = oct, + volume = 166, + pages = {470-497}, + doi = {10.1086/506525}, + adsurl = {http://adsabs.harvard.edu/abs/2006ApJS..166..470R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{robertson2007a, + author = {{Robertson}, B. and {Li}, Y. and {Cox}, T.~J. and {Hernquist}, L. and + {Hopkins}, P.~F.}, + title = "{Photometric Properties of the Most Massive High-Redshift Galaxies}", + journal = {\apj}, + eprint = {astro-ph/0703456}, + keywords = {Galaxies: Evolution, Galaxies: Formation}, + year = 2007, + month = sep, + volume = 667, + pages = {60-78}, + doi = {10.1086/520057}, + adsurl = {http://adsabs.harvard.edu/abs/2007ApJ...667...60R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{robotham2014a, + author = {{Robotham}, A.~S.~G. and {Driver}, S.~P. and {Davies}, L.~J.~M. and + {Hopkins}, A.~M. and {Baldry}, I.~K. and {Agius}, N.~K. and + {Bauer}, A.~E. and {Bland-Hawthorn}, J. and {Brough}, S. and + {Brown}, M.~J.~I. and {Cluver}, M. and {De Propris}, R. and + {Drinkwater}, M.~J. and {Holwerda}, B.~W. and {Kelvin}, L.~S. and + {Lara-Lopez}, M.~A. and {Liske}, J. and {L{\'o}pez-S{\'a}nchez}, {\'A}.~R. and + {Loveday}, J. and {Mahajan}, S. and {McNaught-Roberts}, T. and + {Moffett}, A. and {Norberg}, P. and {Obreschkow}, D. and {Owers}, M.~S. and + {Penny}, S.~J. and {Pimbblet}, K. and {Prescott}, M. and {Taylor}, E.~N. and + {van Kampen}, E. and {Wilkins}, S.~M.}, + title = "{Galaxy And Mass Assembly (GAMA): galaxy close pairs, mergers and the future fate of stellar mass}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1408.1476}, + keywords = {galaxies: evolution, galaxies: fundamental parameters, galaxies: interactions, galaxies: kinematics and dynamics, galaxies: luminosity function, mass function, galaxies: stellar content}, + year = 2014, + month = nov, + volume = 444, + pages = {3986-4008}, + doi = {10.1093/mnras/stu1604}, + adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.444.3986R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{rykoff2014a, + author = {{Rykoff}, E.~S. and {Rozo}, E. and {Busha}, M.~T. and {Cunha}, C.~E. and + {Finoguenov}, A. and {Evrard}, A. and {Hao}, J. and {Koester}, B.~P. and + {Leauthaud}, A. and {Nord}, B. and {Pierre}, M. and {Reddick}, R. and + {Sadibekova}, T. and {Sheldon}, E.~S. and {Wechsler}, R.~H.}, + title = "{redMaPPer. I. Algorithm and SDSS DR8 Catalog}", + journal = {\apj}, +archivePrefix = "arXiv", + eprint = {1303.3562}, + keywords = {galaxies: clusters: general}, + year = 2014, + month = apr, + volume = 785, + eid = {104}, + pages = {104}, + doi = {10.1088/0004-637X/785/2/104}, + adsurl = {http://adsabs.harvard.edu/abs/2014ApJ...785..104R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%SSSSSSSSSSS +@ARTICLE{salim2016a, + author = {{Salim}, S. and {Lee}, J.~C. and {Janowiecki}, S. and {da Cunha}, E. and + {Dickinson}, M. and {Boquien}, M. and {Burgarella}, D. and {Salzer}, J.~J. and + {Charlot}, S.}, + title = "{GALEX-SDSS-WISE Legacy Catalog (GSWLC): Star Formation Rates, Stellar Masses, and Dust Attenuations of 700,000 Low-redshift Galaxies}", + journal = {\apjs}, +archivePrefix = "arXiv", + eprint = {1610.00712}, + keywords = {galaxies: fundamental parameters, galaxies: star formation}, + year = 2016, + month = nov, + volume = 227, + eid = {2}, + pages = {2}, + doi = {10.3847/0067-0049/227/1/2}, + adsurl = {http://adsabs.harvard.edu/abs/2016ApJS..227....2S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + + +@BOOK{sersic1968a, + author = {{Sersic}, J.~L.}, + title = "{Atlas de galaxias australes.}", + keywords = {GALAXIES, GROUPS OF GALAXIES, ATLASES}, +booktitle = {Cordoba, Argentina: Observatorio Astronomico, 1968}, +publisher = {Cordoba, Argentina: Observatorio Astronomico}, + year = 1968, + adsurl = {http://adsabs.harvard.edu/abs/1968adga.book.....S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@ARTICLE{stott2012a, + author = {{Stott}, J.~P. and {Hickox}, R.~C. and {Edge}, A.~C. and {Collins}, C.~A. and + {Hilton}, M. and {Harrison}, C.~D. and {Romer}, A.~K. and {Rooney}, P.~J. and + {Kay}, S.~T. and {Miller}, C.~J. and {Sahl{\'e}n}, M. and {Lloyd-Davies}, E.~J. and + {Mehrtens}, N. and {Hoyle}, B. and {Liddle}, A.~R. and {Viana}, P.~T.~P. and + {McCarthy}, I.~G. and {Schaye}, J. and {Booth}, C.~M.}, + title = "{The XMM Cluster Survey: the interplay between the brightest cluster galaxy and the intracluster medium via AGN feedback}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1202.3787}, + primaryClass = "astro-ph.CO", + keywords = {galaxies: active, galaxies: clusters: intracluster medium, galaxies: elliptical and lenticular, cD}, + year = 2012, + month = may, + volume = 422, + pages = {2213-2229}, + doi = {10.1111/j.1365-2966.2012.20764.x}, + adsurl = {http://adsabs.harvard.edu/abs/2012MNRAS.422.2213S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +%TTTTTTTTTTTTTTTTT +@ARTICLE{tiley2016a, + author = {{Tiley}, A.~L. and {Stott}, J.~P. and {Swinbank}, A.~M. and + {Bureau}, M. and {Harrison}, C.~M. and {Bower}, R. and {Johnson}, H.~L. and + {Bunker}, A.~J. and {Jarvis}, M.~J. and {Magdis}, G. and {Sharples}, R. and + {Smail}, I. and {Sobral}, D. and {Best}, P.}, + title = "{The KMOS Redshift One Spectroscopic Survey (KROSS): the Tully-Fisher relation at z {\tilde} 1}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1604.06103}, + keywords = {galaxies: evolution, galaxies: general, galaxies: kinematics and dynamics}, + year = 2016, + month = jul, + volume = 460, + pages = {103-129}, + doi = {10.1093/mnras/stw936}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.460..103T}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@ARTICLE{tiley2016b, + author = {{Tiley}, A.~L. and {Bureau}, M. and {Saintonge}, A. and {Topal}, S. and {Davis}, T.~A. and {Torii}, K.}, + title = "{The Tully-Fisher relation of COLD GASS Galaxies}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1607.01393}, + keywords = {galaxies: general}, + year = 2016, + month = oct, + volume = 461, + pages = {3494-3515}, + doi = {10.1093/mnras/stw1545}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.461.3494T}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} +@article{trachternach2008a, + Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/2008AJ....136.2720T}, + Archiveprefix = {arXiv}, + Author = {{Trachternach}, C. and {de Blok}, W.~J.~G. and {Walter}, F. and {Brinks}, E. and {Kennicutt}, R.~C.}, + Date-Added = {2017-04-25 15:26:32 +0000}, + Date-Modified = {2017-04-25 15:26:32 +0000}, + Doi = {10.1088/0004-6256/136/6/2720}, + Eprint = {0810.2116}, + Journal = {\aj}, + Keywords = {dark matter, galaxies: dwarf, galaxies: fundamental parameters, galaxies: ISM, galaxies: kinematics and dynamics, galaxies: spiral}, + Month = dec, + Pages = {2720-2760}, + Title = {{Dynamical Centers and Noncircular Motions in Things Galaxies: Implications for Dark Matter Halos}}, + Volume = 136, + Year = 2008 +} +@article{tully1977a, + Adsnote = {Provided by the Smithsonian/NASA Astrophysics Data System}, + Adsurl = {http://adsabs.harvard.edu/abs/1977A%26A....54..661T}, + Author = {{Tully}, R.~B. and 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The progressive mix of +disk and spheroidal morphological components of +galaxies communicate the relative importance of +energy dissipation and collisionless processes +for their formation. +Correlations between internal galaxy properties and +cosmic environments indicate +the ways the universe nurtures galaxies as they form. +The evolution of the +detailed characteristics of galaxies over cosmic time +reflects how fundamental astrophysics +operates to generate the rich variety of +astronomical structures observed today. + +Study of the astrophysics of galaxy formation represents +a vital science of its own, but the ready +observability of galaxies critically enables a host of +astronomical experiments in other fields. +Galaxies act as the semaphores of the +universe, encoding information about +the development of large scale +structures and the mass-energy budget of the +universe in their spatial distribution. The mass distribution +and clustering of galaxies reflect essential +properties of dark matter, including potential +constraints on the velocity and mass of particle candidates. +Galaxies famously host supermassive black holes, +and observations of active galactic nuclei provide +a window into the high-energy astrophysics of black hole +accretion processes. The porous interface between the +astrophysics of black holes, galaxies, and +dark matter structures allows for astronomers to +achieve gains in each field using the same datasets. + +LSST will provide a +digital image of the southern sky in six bands ($ugrizy$). +The area ($\sim18,000~\mathrm{deg}^2$) and depth +($r\sim24.5$ for a single visit, $r\sim27.5$ coadded) of +the survey will enable research of such breadth +that LSST may influence essentially all extragalactic +science programs that rely primarily on photometric data. +For studies of galaxies, LSST will provide both an unequaled +catalogue of billions of extragalactic sources and high-quality +multiband imaging of individual objects. This section of +the {\it LSST Galaxies Science Roadmap} presents scientific +background for studies of these galaxies with LSST to provide a +context for considering how the astronomical community can +best leverage the catalogue and imaging datasets and for +identifying required preparatory science tasks. + +LSST will begin science operations during the next decade, +more than twenty years after the start of the Sloan +Digital Sky Survey \citep{york2000a} and subsequent precursor surveys +including PanSTARRS \citep{kaiser2010a}, the Subaru +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, the +Kilo-Degree Survey \citep{dejong2015a}, and the Dark +Energy Survey \citep{flaugher2005a}. Relative to these prior +efforts, extragalactic science breakthroughs +generated by LSST will likely benefit from its increased area, source +counts and statistical samples, the constraining power of the +six-band imaging, and the survey depth and image quality. The following +discussion of LSST efforts focusing on the astrophysics of galaxies +will highlight how these features of the survey enable new science +programs. + + + +\section{Star Formation and Stellar Populations in Galaxies} +\label{sec:sci:gal:bkgnd:stars} + +Light emitted by stellar populations will +provide all the direct measurements made by +LSST. This information will be filtered through +the six passbands utilized by the survey, +providing constraints on the +rest-frame ultraviolet SEDs of galaxies to +redshift $z\sim6$ and a probe of rest-frame +optical spectral breaks to $z\sim1.5$. By +using stellar population synthesis modeling, +these measures of galaxy SEDS will enable +estimates of the redshifts, star formation rates, +stellar masses, dust content, and +population ages for potentially +billions of galaxies. In the context of previous +extragalactic surveys, LSST +will enable new advances in our understanding +of stellar populations in galaxies by contributing +previously unachievable statistical power and an +areal coverage that samples the rarest cosmic +environments. + +A variety of ground- and space-based observations +have constrained the +star formation history of the universe over the +redshift range that LSST will likely probe +\citep[for a recent review, see][]{madau2014a}. +The statistical power of LSST will improve our +knowledge of the evolving UV luminosity function, +luminosity density, and cosmic +star formation rate. The LSST observations can +constrain how the astrophysics of gas +cooling within dark matter halos, the efficiency +of molecular cloud formation and the star formation +within them, and +regulatory mechanisms like supernova and radiative +heating give rise to these statistical features +of the galaxy population. While measurement of +the evolving UV luminosity function can +help quantify the role of these +astrophysical processes, the ability of LSST +to probe vastly different cosmic environments +will also allow for the robust quantification of any +changes in the UV luminosity function with +environmental density, and an examination of +connections between environment and the fueling +of star formation. + +Optical observations teach us about +the established stellar content of galaxies. +For stellar populations older than $\sim100$ million +years, optical observations provide +sensitivity to the spectral breaks near a +wavelength of $\lambda\approx4000\mbox{\normalfont\AA}$ in the +rest-frame related to absorption in the +atmospheres of mature stars. +Such observations help constrain +the amount of stellar mass in galaxies. For +passive galaxies that lack vigorous star formation, +these optical observations reveal +the well-defined ``red sequence'' of +galaxies in the color-magnitude plane +that traces the succession of +galaxies from recently-merged spheroids +to the most massive systems at the +centers of galaxy clusters \citep[e.g.][]{kaviraj2005a}. For blue, +star-forming +galaxies, optical light can help +quantify the relative contribution of +evolved stars to total galaxy luminosity, +and indeed has +led to the identification of a well-defined +locus of galaxies in the parameter space of +star formation rate and stellar mass +\citep[e.g.,][]{noeske2007a}. This +relation, often called the ``star-forming +main sequence'' of galaxies, indicates that +galaxies of the same stellar mass typically +sustain a similar star-formation rate. +Determining the +physical or possibly statistical +origin of the relation remains an active +line of inquiry \citep[e.g.][]{lofthouse2017a}, guided by recently improved +data from Hubble Space Telescope over the +$\sim0.2$ deg$^{2}$ Cosmic Assembly Near-Infrared +Deep Extragalactic Survey +\citep{grogin2011a,koekemoer2011a}. While +LSST will be comparably limited in redshift +selection, its $\sim30,000$ times larger area +will enable a much fuller sampling of the +star formation--stellar mass plane, allowing +for a characterization of the distribution +of galaxies that lie off the main sequence +that can help discriminate between phenomenological +explanations of the sequence. + +\section{Galaxies as Cosmic Structures} +\label{sec:sci:gal:bkgnd:structures} + +The structural properties of galaxies arise from +an intricate combination of important astrophysical +processes. Driven by dark matter structure growth, the dynamical +interplay between baryonic and dark matter components form +the basis for the development of galaxy properties. +The gaseous disks of galaxies require +substantial energy dissipation while depositing +angular momentum into a rotating structure. These +gaseous disks form stars with a +surface density that declines exponentially with +galactic radius, populating stellar orbits that +differentially rotate about the galactic center and +somehow organize into spiral features. +Many disk galaxies contain (pseudo-)bulges that form through +a combination of violent relaxation and orbital dynamics. +These disk galaxy features contrast with systems where +spheroidal stellar distributions dominate the galactic +structure. Massive ellipticals form through galaxy +mergers and accretions, and manage to forge a regular +sequence of surface density, size, and stellar velocity +dispersion from the chaos of strong gravitational +encounters. Since these astrophysical +processes may operate with great +variety as a function of galaxy mass and +cosmic environment, LSST will revolutionize studies +of evolving galaxy morphologies by providing enormous +samples with deep imaging of exquisite quality. These data also enable +studies of galaxy mass profiles via weak lensing of the background +galaxy population. + +The huge sample of galaxies provided by LSST will +provide a definitive view of how the sizes and +structural parameters of disk and spheroidal systems +vary with color, total mass, stellar mass, and luminosity. +Morphological studies will employ several complementary techniques for quantifying the +structural properties of galaxies. Bayesian +methods can yield multi-component +parameterized models for all the galaxies +in the LSST sample, including the quantified +contribution of bulge, disk, and +spheroid structures to the observed galaxy +surface brightness profiles. The parameterized +models will supplement non-parametric measures +of the light distribution including the +Gini and M20 metrics that quantify the surface +brightness uniformity and spatial moment of +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume +and steadily increasing depth of the LSST dataset, +new machine-learning algorithms \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided +by analyzing the LSST imaging data will enable +a consummate determination of the relation between +structural properties and other features of +galaxies over a range of galaxy mass and luminosity +previously unattainable. + +While the size of the LSST sample supplies the +statistical power for definitive morphological studies, +the sample size also enables the identification of rare +objects. This capability will benefit our efforts for +connecting the distribution of galaxy morphologies to their +evolutionary origin during the structure formation process, +including the formation of disk galaxies. +The emergence of ordered disk galaxies remains a hallmark +event in cosmic history, with so-called ``grand design'' +spirals like the Milky Way forming dynamically cold, thin +disks in the last $\sim10$ Gyr. Before thin disks emerged, +rotating systems featured ``clumpy'' mass distributions with +density enhancements +that may originate from large scale gravitational instability. +Whether the ground-based LSST can effectively probe +the exact timing and duration of the transition from +clumpy to well-ordered disks remains +unknown, but LSST can undoubtedly contribute to studying the +variation in forming disk structures at the present day. +Unusual objects, such as the UV luminous local galaxies identified +by \citet{heckman2005a} that display physical features analogous to +Lyman break galaxies at higher redshifts, may provide a +means to study the formation of disks in the present day +under rare conditions only well-probed by the sheer size +of the LSST survey. + +Similarly, characterizing the extremes of the +massive spheroid population can critically inform +theoretical models for their formation. For instance, +the most massive galaxies at the centers of galaxy clusters +contain vast numbers of stars within enormous stellar +envelopes. The definitive LSST sample can capture enough +of the most massive, rare clusters to quantify the +spatial extent of these galaxies at +low surface brightnesses, where the bound stellar +structures blend with the intracluster light of +their hosts. +LSST data +can improve understanding of +the central densities of local +ellipticals that have seemingly decreased compared with +field ellipticals at higher redshifts. The transformation +of these dense, early ellipticals to the spheroids in the +present day may involve galaxy mergers and environmental +effects, two astrophysical processes that LSST can characterize +through unparalleled statistics and environmental probes. +By measuring the +surface brightness profiles of billions of +ellipticals LSST can determine whether any such dense +early ellipticals survive to the present day, whatever +their rarity. + +Beyond the statistical advances enabled by LSST and the +wide variation in environments probed by a survey +of half the sky, the image quality of LSST will permit +studies of galaxy structures in the very low surface +brightness regime. This capability +will allow for the characterization of stellar halos that +surround nearby galaxies. Structures in stellar halos, +such as tidal features produced by mergers and interactions and density inhomogeneities, originate +from the hierarchical formation process and their +morphological properties provides critical clues to the formation history +on a galaxy-by-galaxy basis \citep{bullock2005a,johnston2008a}. +Observational studies using small, deep surveys like the SDSS Stripe 82 \citep[e.g.][]{kaviraj2014a,kaviraj2014b} and recent work using small telescopes \citep{martinez-delgado2008a,atkinson2013,abraham2014a,van_dokkum2014a} +have +demonstrated the critical importance of probing the low surface brightness universe +in order to test the hierarchical galaxy formation paradigm. +Since low-mass galaxies far outnumber their massive counterparts, the assembly history of massive galaxies is dominated by mergers of unequal mass ratios (`minor' mergers). +However, such mergers typically produce tidal features that are fainter +than the surface brightness limits of current surveys like the SDSS. +Hence, the majority of merging remains, from an empirical point of view, unquantified. +Deep-wide surveys like LSST are crucial for empirically testing the hierarchical paradigm +and understanding the role of galaxy merging in driving star formation, black hole growth, and morphological transformations over cosmic time \citep{kaviraj2014b}. +The examination of stellar halos around galaxies will +result in the identification of small mass satellites +whose sizes, luminosities, and abundances can constrain +the nature of dark matter and models of the galaxy formation process at the extreme +low-mass end of the mass function. + +Finally, observational measures of the outermost regions of thin disks can reveal +how such disks ``end'', how dynamical effects might truncate +disks, and whether some disks smoothly transition into stellar +halos. LSST will provide such measures and help quantify the +relative importance of the physical effects that influence the +low surface brightness regions in disks. Other galaxies +have low surface brightnesses throughout their stellar +structures, and the image quality and sensitivity +of LSST will enable the most complete census +of low surface brightness galaxies to date. LSST will provide +the best available constraints on the extremes of disk +surface brightness, which relates to the extremes of +star formation in low surface density environments. + + + +The LSST survey uniquely enables precision statistical studies of +galaxy mass +distribution via weak gravitational. +From the radial dependence of +the galaxy-mass correlation function, galaxy morphological properties +can be compared with the mass distribution, as a function +of redshift of the lens galaxy population (Choi et al. 2012, +Leauthaud et al. 2012). Even dwarf galaxies +can be studied in this way: the LSST survey will enable mass +mapping of samples of hundreds of thousands of dwarf galaxies. +With a sample of hundreds of millions of foreground galaxies, +for the first time trends in galaxy stellar evolution and type +can be correlated with halo mass and mass environment on cosmological scales. + +\section{Probing the Extremes of Galaxy Formation} +\label{sec:sci:gal:bkgnd:rare} + +The deep, multiband imaging that LSST will provide over an enormous +area will enable the search for galaxies that form in the +rarest environments, under the most unusual conditions, +and at very early times. By probing the extremes of +galaxy formation, the LSST data will push our +understanding of the structure formation process. + +The rarest, most massive early galaxies may form in +conjunction with the supermassive black holes that +power distant quasars. LSST can use the same +types of color-color selections to identify extremely +luminosity galaxies out to redshift $z\sim6$, and +monitor whether the stellar mass build-up in these +galaxies tracks the accretion history of the most +massive supermassive black holes. If stellar mass +builds proportionally to black hole mass in quasars, +then very rare luminous star-forming galaxies at +early times may immediately proceed the formation +of bright quasars. LSST has all the requisite +survey properties (area, multiband imaging, and +depth) to investigate this long-standing problem \citep{robertson2007a}. + +The creation of LSST Deep Drilling fields will +enable a precise measurement of the +high-redshift galaxy luminosity function. +Independent determinations of the distribution of +galaxy luminosities at $z\sim6$ show substantial +variations. The origin of +the discrepancies between various determinations remains +unclear, but the substantial cosmic variance expected +for the limited volumes probed and the intrinsic +rarity of the bright objects may conspire to +introduce large potential differences between +the abundance of massive galaxies in different +areas of the sky. Reducing this uncertainty requires +deep imaging over a wide area, and the LSST Deep Drilling +fields satisfy this need by achieving sensitivities +beyond the rest of the survey. + +The spatial rarity of extreme objects discovered +in the wide LSST area may reflect an intrinsically +small volumetric density of objects or the short duration +of an event that gives rise to the observed properties of the +rare objects. Mergers represent a critical class +of short-lived epochs in the formation histories of +individual galaxies. Current determinations of the evolving numbers +of close galaxy pairs or morphological indicators of +mergers provide varying estimates for the +redshift dependence of the galaxy merger rate +\citep[e.g.,][]{darg2010a,conselice2003a,kartaltepe2007a,lotz2008a,lin2008a,kaviraj2009a,robotham2014a,kaviraj2015a}. +The identification of merging +galaxy pairs as a function of separation, merger +mass ratio, and environment in the LSST data will enable +a full accounting of how galaxy mergers influence +the observed properties of galaxies as a function of +cosmic time. + +\vspace{-0.05in} + +\section{Photometric Redshifts} +\label{sec:sci:gal:bkgnd:photoz} +As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. +However, the third dimension of cosmic distance to each galaxy must often +come from photometric redshifts (photo-$z$'s). Many quantities that LSST data can +reveal about distant galaxy populations, including intrinsic luminosities, physical +sizes, star formation rates, and stellar masses, will ultimately rely on photo-$z$ +determinations. The engineering of accurate and precise photo-$z$ methods +therefore represents an important science effort for LSST science collaborations. + +Spectroscopic distance estimates rely on the identification of atomic or molecular transitions in expensive, +high resolution spectra. In contrast, photometric redshifts estimate the rough distance to an object based on its broad-band photometric colors and, potentially, other properties measurable from imaging. +Photo-$z$ measurements are akin to determining redshifts from a very low-resolution but high signal-to-noise spectrum, where each broad-band filter contributes a single sample in that spectrum. Photometric +redshifts are therefore sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.,~the 4000~\AA\ and Lyman breaks), but in general lack the definitiveness of a redshift measured from multiple well-centroided spectral features (e.g., a pair of emission or absorption lines of known separation). As a result, photometric redshifts will generally be more uncertain than spectroscopic redshift estimates and can be affected by degeneracies in the color-redshift relation. + +By relying on imaging data alone, we will be able to measure photo-$z$'s for billions of galaxies in the LSST survey. +As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys. +Assigning an incorrect redshift to a galaxy also assigns an incorrect luminosity +owing to misestimation of both the distance modulus and $k$-corrections, and hence can bias estimates of the luminosity function. Errors in redshift will also bias the inferred rest-frame colors of a galaxy, propagating to errors in the inferred spectral type, stellar mass, star formation rate, and other quantities. +Ideally, estimates of any physical quantity should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if measurements are to be +made in an unbiased way. + +To develop optimal estimates of photo-$z$'s for a particular survey, photo-$z$ algorithms +should be trained using a set of galaxies with known redshifts. If spectroscopy is obtained for a fully representative sub-sample of the underlying galaxy population spanning the full domain of application, this spectroscopy can also be used to characterize the biases and uncertainties in the photometric redshift estimates, calibrating their use for science. + +Obtaining such a fair spectroscopic sample for LSST will be very difficult to achieve due to limitations in instrumentation, telescope time, and the astrophysical properties of galaxies (e.g., weak spectral features). +Biases owing to incomplete training data can be identified and removed using a variety of redshift calibration techniques, such as spatially cross-correlating photo-$z$-selected datasets with a sample of objects with secure redshifts over wide fields, as will be provided by DESI and 4MOST \citep{newman2008a}. A detailed plan describing the spectroscopic needs for training and calibrating photometric redshifts for LSST is laid out in \citet[]{newman2015a}, where potential scenarios for obtaining the necessary spectroscopy using existing facilities and those expected to be available in the near future are detailed. + +The insights about the formation and evolution of galaxies we expect to gain from LSST can also be used to improve photo-$z$ algorithms, both by constraining the family of spectral energy distributions of galaxies as a function of redshift and by improving our knowledge of distributions of other observable quantities such as size and surface brightness. This mutual synergy between understanding galaxy evolution and improved photometric redshift performance should lead to improvements in both areas as the survey progresses. + +\vspace{-0.05in} +\section{Science Book} +\label{sec:sci:gal:bkgnd:scibook} + +The LSST Science Book (\citealt{LSSTSciBook}) provided +detailed descriptions of foundational science enabled +by LSST. The LSST Galaxies Science Collaboration authored +the Chapter 9 ``Galaxies'' of the Science Book, and the +table of contents of that chapter follows below to +provide an example list of topics in extragalactic +science that LSST data will help revolutionize. The +interested reader is referred to the LSST Science +Book for more details. + + +\begin{enumerate} +\item Measurements, Detection, Photometry, Morphology +\item Demographics of Galaxy Populations +\begin{itemize} +\item Passively evolving galaxies +\item High-redshift star-forming galaxies +\item Dwarf galaxies +\item Mergers and interactions +\end{itemize} +\item Distribution Functions and Scaling Relations +\begin{itemize} +\item Luminosity and size evolution +\item Relations between observables +\item Quantifying the Biases and Uncertainties +\end{itemize} +\item Galaxies in their Dark-Matter Context +\begin{itemize} +\item Measuring Galaxy Environments with LSST +\item The Galaxy-Halo Connection +\item Clusters and Cluster Galaxy Evolution +\item Probing Galaxy Evolution with Clustering Measurements +\item Measuring Angular Correlations with LSST, Cross-correlations +\end{itemize} +\item Galaxies at Extremely Low Surface Brightness +\begin{itemize} +\item Spiral Galaxies with LSB Disks +\item Dwarf Galaxies +\item Tidal Tails and Streams +\item Intracluster Light +\end{itemize} +\item Wide Area, Multiband Searches for High-Redshift Galaxies +\item Deep Drilling Fields +\item Galaxy Mergers and Merger Rates +\item Special Populations of Galaxies +\item Public Involvement +\end{enumerate} +} diff --git a/arxiv/structure.tex b/arxiv/structure.tex new file mode 100644 index 0000000..8bd3c63 --- /dev/null +++ b/arxiv/structure.tex @@ -0,0 +1,63 @@ +\usepackage{amsmath} +\usepackage{amssymb} +\usepackage[top=3cm,bottom=3cm,left=0.8in,right=0.8in,headsep=10pt]{geometry} % Page margins +\usepackage{graphicx} % Required for including pictures + + + +\usepackage{verbatim} +\usepackage{enumitem} % Customize lists +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists +\usepackage{booktabs} % Required for nicer horizontal rules in tables +\usepackage{xcolor} % Required for specifying colors by name +\usepackage{listings} +\usepackage{color} + +%FONTS +\usepackage{anyfontsize} +\usepackage{avant} % Use the Avantgarde font for headings +\usepackage{mathptmx} % Use the Adobe Times Roman as the default text font together with math symbols from the Sym­bol, Chancery and Com­puter Modern fonts +\usepackage{microtype} % Slightly tweak font spacing for aesthetics + + + +\usepackage{calc} % For simpler calculation - used for spacing the index letter headings correctly +\usepackage{makeidx} % Required to make an index +\makeindex % Tells LaTeX to create the files required for indexing + + + +\bibliographystyle{apj} +\usepackage{natbib} + +%\usepackage{titletoc} % Required for manipulating the table of contents + + + +\setlist{nolistsep} % Reduce spacing between bullet points and numbered lists + +\def\motivation#1{\item[Motivation:] #1} +\def\activities#1{\item[Activities:] #1} +\def\deliverables#1{\item[Deliverables:] #1} + +\newenvironment{task}% +{\renewcommand\descriptionlabel[1]{\hspace{\labelsep}\textit{##1}} + \begin{description}\setlength{\itemsep}{0.15\baselineskip}} +{\end{description}} + +% Example usage: +% +% \begin{task} +% \motivation{Currently things are bad}. +% \activities{We will work to make them better}. +% \deliverables{Code to solve all problems}. +% \end{task} + +% PJM: here's a tasklist environment to take care of Michael's enumeration: + +%\def\tasktitle#1{\item{\bf #1}} +\def\tasktitle#1{\item{}} + +\newenvironment{tasklist}[1]% +{\begin{enumerate}[label=#1-\arabic{*}.,ref=\thesubsection:#1-\arabic{*},font=\bf]} +{\end{enumerate}} diff --git a/arxiv/task_lists.tex b/arxiv/task_lists.tex new file mode 100644 index 0000000..e4eef9b --- /dev/null +++ b/arxiv/task_lists.tex @@ -0,0 +1,23 @@ +% LSST Galaxies Science Roadmap +% Chapter: task_lists +% First draft by + +\chapter[Task Lists by Science Area]{Task Lists by Science Area} +\label{ch:task_lists} +\input{agn.tex} +\newpage +\input{clss.tex} +\newpage +\input{ddf.tex} +\newpage +\input{galaxies.tex} +\newpage +\input{high_z.tex} +\newpage +\input{lsb.tex} +\newpage +\input{photo_z.tex} +\newpage +\input{tmc.tex} +\newpage +\input{aux.tex} diff --git a/arxiv/tmc.tex b/arxiv/tmc.tex new file mode 100644 index 0000000..04029c2 --- /dev/null +++ b/arxiv/tmc.tex @@ -0,0 +1,140 @@ +\section{Theory and Mock Catalogs}\label{sec:tasks:tmc} +{\justify +A critical challenge for interpreting the vast LSST dataset +in the context of a cosmological model for galaxy formation +involves the development of theory, both in the practical applications +of realistic simulations and the engineering of new physical +models for the important processes that govern the observable +properties of galaxies. The following preparatory science tasks +for LSST-related theoretical efforts range from understanding the +detailed properties of galaxies that LSST will uncover to predicting +the large-scale properties of galaxy populations that LSST will probe +on unprecedented scales. + + +\begin{tasklist}{TMC} +\subsection{Image Simulations of Galaxies with Complex Morphologies} +\tasktitle{Image Simulations of Galaxies with Complex Morphologies} +\begin{task} +\label{task:tmc:complex_morphology} +\motivation{ +LSST images will contain significant information about the dynamical state of galaxies. In principle, we can exploit +this morphological information to learn about the formation and evolutionary histories +of both individual and populations of galaxies. +Examples of important morphological features include spiral arms, tidal tails, double nuclei, clumps, warps, and streams. +A wide variety of analysis and modeling techniques can help determine the past, present, or future states of observed galaxies with complex morphologies, +and thereby improve our understanding of galaxy assembly. +} +~\\ +\activities{ +Activities include creating synthetic LSST observations containing a wide variety of galaxies with complex morphologies, for the purpose of testing analysis algorithms such as de-blending, photometry, and morphological characterization. Supporting activities include creating databases of galaxy images from models (such as cosmological simulations) or existing optical data, analyzing them using LSST software or prototype algorithms, and distributing the findings of these studies. These analyses may involve small subsets of the sky and do not necessarily require very-large-area image simulations or need to match known constraints on source density. +Results will include predicting the incidence of measured morphological features, optimizing Level 3 measurements on galaxy images, and determining the adequacy of LSST data management processes for these science goals.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Creating synthetic LSST images of galaxies with complex morphology from simulations. +\item Creating synthetic LSST images based on prior observations in similar filters. +\item Making LSST-specific complex galaxy data products widely available. +\item Publicizing results from algorithm tests based on these LSST simulations. +\item Assessing Level 3 measurements to propose and/or apply in maximizing the return of LSST catalogs for complex galaxy morphology science. +\end{enumerate} +} +\end{task} + + +\subsection{New Theoretical Models for the Galaxy Distribution} +\tasktitle{New Theoretical Models for the Galaxy Distribution} +\begin{task} +\label{task:tmc:galaxy_distribution} +\motivation{ +Meeting the challenge of building synthetic, computer-generated mock surveys for use in the preparation +of extragalactic science with LSST will require the assembly of experts in key theoretical areas. +LSST will collect more data than contained in the current largest survey, the SDSS, +every night for ten years. The analysis of such data demands a complete overhaul of traditional techniques and will require the incorporation of ideas from different disciplines. +Mock catalogs +offer the best means to test and constrain theoretical models using observational data, and +play a well-established role in modern galaxy surveys. +For the first time, systematic uncertainties will limit +the scientific potential of the new surveys, rather than sampling errors driven by the volume mapped. +A variety of viable, competing cosmological models already provide only subtly discernible +signals in survey data. +Distinguishing between the models requires the best possible theoretical predictions to understand the measurements and their subsequent analysis, and to +understand the uncertainties on the measurements. +} +~\\ +\activities{ +Develop a new state-of-the-art in physical models of the galaxy distribution by +combining models of the physics of galaxy formation with high resolution N-body simulations that track the hierarchical growth of structure in the matter distribution. +The key task involves performing moderate volume cosmological N-body simulations, generating +predictions from an associated model of galaxy formation, and then embedding +this information into very large volume simulations that can represent LSST datasets. +The large volume simulations will extend beyond the volume of the target survey, +allowing a robust assessment of the systematic uncertainties on large-scale structure measurements.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Physically motivated mock galaxy catalogues on volumes larger than those sampled by LSST, with a consistently evolving population of galaxies. +\item Base catalogues of dark matter haloes and their merger trees suitable for use by theoretical models for populating these with galaxies (halo and subhalo occupation/abundance matching techniques). +\item Small volume simulations for further tests of baryonic physics and detailed observational comparisons. +\end{enumerate} +} +\end{task} + +\subsection{Design of New Empirical Models for the Galaxy Distribution} +\tasktitle{Design of New Empirical Models for the Galaxy Distribution} +\begin{task} +\label{task:section:title} +\motivation{ +The galaxy-halo connection represents the end state of the combined physics of baryonic galaxy formation and dark matter structure formation processes. +A full exploitation of the LSST dataset for understanding galaxy formation will +necessarily involve the exploration of the galaxy-halo connection, +using the simulations of the galaxy formation process to build better empirical models. +Empirical models can adjust to reproduce observational results as closely as possible, whereas computationally expensive physical models often prove too expensive to +tune in the same manner. +Empirical models also have the advantage of being extremely fast, allowing large parameter spaces to be explored. +} +~\\ +\activities{ +Developing models of the galaxy-halo connection for LSST require two main stages. The +first step tests current empirical models to judge the fidelity with which they +reproduce the predictions of physical models based on simulations. The second step +uses physical models to devise new parametrizations for empirical models to +describe galaxy populations for which little or no data yet exists, providing enhanced +empirical models relevant for upcoming surveys that will probe regimes that remain +largely unmapped.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Predictions for the evolution of clustering from physical models. +\item Enhanced paramertizations for empirical models with reduced freedom, greater +applicability, and more rapid population of catalogs to describe the observer's past +lightcone. +\end{enumerate} +} +\end{task} + + +\subsection{Estimating Uncertainties for Large-Scale Structure Statistics} +\tasktitle{Estimating Uncertainties for Large-Scale Structure Statistics} +\begin{task} +\label{task:tmc:uncertainties} +\motivation{ +The ability to interpret the relation between galaxies and the matter density field will depend critically on how well we understand the uncertainties of large-scale structure measurements. The accurate estimation of the covariance on a large-scale structure measurement such as the correlation function would require tens of thousands of simulations. +} +~\\ +\activities{ +Devise and calibrate analytic methods for estimating the covariance matrix on large-scale structure statistics using N-body simulations and more rapid but more approximate schemes, such as those based on perturbation theory. +Coordinate with Dark Energy Science Collaboration Working Groups, as these covariance matrices can also inform cosmological parameter constraints.} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item Physically motivated estimates of covariance matrices for galaxy occupation (and other) parameter searches. +\end{enumerate} +} +\end{task} +\end{tasklist} +} diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 4ae031d..7f06b1c 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -1,15 +1,15 @@ -\section{Clusters and Large Scale Structure}\label{sec:tasks:clss} +\section{Clusters and Large-Scale Structure}\label{sec:tasks:clss} {\justify The cosmological process of galaxy formation inextricably links -together environment and large scale structure with the detailed +together environment and large-scale structure with the detailed properties of galaxy populations. The extent of this connection ranges from the scales of superclusters down to small groups. The following preparatory science tasks focus on this critical connection -between galaxy formation, clusters, and large scale structure (LSS). +between galaxy formation, clusters, and large-scale structure (LSS). \begin{tasklist}{CLSS} -\subsection{Cluster and Large Scale Structure Sample Emulator} -\tasktitle{Cluster and Large Scale Structure Sample Emulator} +\subsection{Cluster and Large-Scale Structure Sample Emulator} +\tasktitle{Cluster and Large-Scale Structure Sample Emulator} \begin{task} \label{task:clss:emulator} \motivation{ @@ -218,7 +218,7 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} completeness as a function of galaxy properties. \item Development and refinement of techniques for measuring galaxy clustering of large LSST galaxy samples. Together, these techniques will enable the -full potential of LSST data for combined studies of large scale structure and +full potential of LSST data for combined studies of large-scale structure and galaxy formation to be realized. \end{enumerate} } @@ -314,7 +314,7 @@ \subsection{Enabling Cluster Science through Robust Photometry and Photometric R -\subsection{ Enabling Cluster Physics Through Forward Modeling of LSST +\subsection{Enabling Cluster Physics Through Forward Modeling of LSST Clusters and Groups} \tasktitle{Enabling Cluster Physics Through Forward Modeling of LSST Clusters and Groups} From c6e2d4c1e40e4c075767d2ffadcdf95ce62c647e Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Fri, 4 Aug 2017 00:26:05 -0700 Subject: [PATCH 64/64] Final formatting tweaks, submitted arxiv version. Multiple formatting tweaks were required given the arXiv latex formatting. This version reflects the arxiv version posted August 4, 2017. --- arxiv/aux.tex | 4 +- arxiv/introduction.tex | 5 + arxiv/lsb.tex | 4 +- arxiv/lsst_galaxies.tar | Bin 0 -> 275456 bytes arxiv/main.tex | 565 ++++++++++- arxiv/photo_z.tex | 4 +- arxiv/references.bib | 1754 ---------------------------------- arxiv/science_background.tex | 6 + arxiv/task_lists.tex | 5 + task_lists/lsb/lsb.tex | 4 +- 10 files changed, 588 insertions(+), 1763 deletions(-) create mode 100644 arxiv/lsst_galaxies.tar delete mode 100644 arxiv/references.bib diff --git a/arxiv/aux.tex b/arxiv/aux.tex index 758b860..c3ce368 100644 --- a/arxiv/aux.tex +++ b/arxiv/aux.tex @@ -22,6 +22,7 @@ \subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} \item A process for establishing quality control and homogenization of datasets including assignment of revised quality flags. \item A pathway for ingesting future datasets as they become available and potentially in advance via MOU arrangements, e.g., TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid, etc. \end{enumerate} +~\\ Approximately 6 million spectroscopic redshifts are known, with the majority of these already in the public domain, along with associated flux and wavelength calibrated spectra. In addition, derived parameters also exist for many of these spectra including, but not limited too, redshifts, equivalent widths, velocity dispersions, line asymmetries etc. Many of these measurements have been made using bespoke software specific to each originating survey (e.g., SDSS v 2dFGRS), creating an inhomogeneous network of data, measurements and quality control flags within the LSST footprint. In addition, in the next decade a number of new surveys will expand these measurements from millions to tens of millions of spectra through facilities and programs such as LAMOST, 4MOST, DESI as well as coarse spectroscopic information via GRISM data from Euclid and eventually WFIRST, leading to a wealth of spectroscopic data which will be invaluable to LSST. The community has two specific problems, i) collating this data and ii) ensuring quality control and standardization. Due to differing observing and analysis techniques not all spectroscopic measurements will be equal, and will depend on the resolution, signal-to-noise and precise software applied. @@ -104,7 +105,8 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} However, some progress can be made by stacking low signal-to-noise H\,{\sc{i}} spectra using an optical prior \citep{meyer2016a}.\\ ~\\ The $z=0$ calibration however is very solid with large samples \citep[e.g.][]{ponomareva2016a,tiley2016b} and -detailed kinematics \citep{trachternach2008a} extending down to low mass galaxies \citep{mcgaugh2000a,oh2015a}. +detailed kinematics \citep{trachternach2008a} extending down to low mass galaxies +\citep{mcgaugh2000a,oh2015a}. The first deep, higher redshift observations have been made but are still limited in scope and samples sizes \citep{verheijen2010a,fernandez2013a,fernandez2016a}.\\ ~\\ For a Tully-Fisher measurement, one needs a kinematic measurement (preferably through H\,{\sc{i}} measurement), diff --git a/arxiv/introduction.tex b/arxiv/introduction.tex index d5ee9ec..6450811 100644 --- a/arxiv/introduction.tex +++ b/arxiv/introduction.tex @@ -2,8 +2,13 @@ % Chapter: Introduction % First draft by +\makeatletter +\let\savedchap\@makechapterhead +\def\@makechapterhead{\vspace*{-3cm}\savedchap} \chapter[Introduction]{Introduction} \label{ch:intro} +\let\@makechapterhead\savedchap +\makeatletter {\justify The Large Synoptic Survey Telescope (LSST) is a wide-field, ground-based diff --git a/arxiv/lsb.tex b/arxiv/lsb.tex index 55c48a0..cb2fdfe 100644 --- a/arxiv/lsb.tex +++ b/arxiv/lsb.tex @@ -85,8 +85,8 @@ \subsection{Faint Outskirts of Galaxies} } ~\\ \activities{ -Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modeling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyze the outskirts. Dithering and rotation of individual imaging will need to be modeled before stacking multiple imaging. -\\ +Most of the activities to be performed in relation to this task will be in common with other LSB tasks, in particular those related to understanding the systematics and how they vary with time and position on the sky. Good and very deep PSF models will have to be built, likely from a combination of theoretical modeling and empirical measurements, and the PSF scattering of light from the brighter parts of the galaxies will need to be de-contaminated and subtracted before we can analyze the outskirts. Dithering and rotation of individual imaging will need to be modeled before stacking multiple imaging.\\ +~\\ Commissioning data will need to be used to study the temporal and positional variations of the PSF, and how accurate theoretical predictions for the PSF are (in other words, how much a variable atmospheric PSF component complicates matters). } ~\\ diff --git a/arxiv/lsst_galaxies.tar b/arxiv/lsst_galaxies.tar new file mode 100644 index 0000000000000000000000000000000000000000..d010b3104c1dadcfbc55c98ac4847130df468e05 GIT binary patch literal 275456 zcmeFaS$7=CdH1QAbLPx(-OpU7A!=qzwjjF`RSBTTLKRdC zNf3wqIp%sk(|n-${hucyGP0_GW=m?h{kmbd2xP|k>{~>BU5zLG(ePn8tvb`{!!Le} zpS88MJ6l`DFZlP1JGbrMwGIE9M|!$htZ%Mwt@GRM&D+J=`qsu5o4+X5evHM;k2#x6 z%P~tk9GAoC{LAcbnjIZwf6xEwJMqn}trhdHf2w~U99GBu;YGI^POI^!*4IuB#d>G$ zeo?fxXUD*&*lHIWYwKUM4ys`}UECB#(T*?2N z2!nb4-`M(@|9=1)|MI5)+yD8$|KflB#V?+h-Qwk5@rNS(=-Ds+f&Vu6@BigL{r&&( z-)H=6@9)13&D7)n;lF>L>-N9Y&;O6^=(JOwoeiqapJ%0{aDQ0+;?K9%*6wcp=JvhY 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z(KE;f3hvtdUEAM@CMx$mnT7-t)X;LHv2l+Z51LNm;J4)h`hnlJ8$QgYL`W+v9meXs zhbRyVJXVKz(snr&e2pR!*(wcN;y20M0YLJ&tolqvE2r4S2}T9LdflO)J-Wn9O8ENlwqz}>zdolXLeZ*DX@$SHr1?{-cy)OY)Od6aVK^m+TzEa zhD$L?Qb}VR>Pb*W1v&4^l>5F@K$#~@53-KomR3K>>V-Gk6030CmsAKyKwjMR}05wx|370>NP=9HhMZaq-A|AnmG5G!Es zkF3-g%W`^r4o&}3mBZv@186NH;=2H*w9MiDF!{gl6`9S6zJVoF2U~P5evAfM!m| gt;VOh@9X!}$1l*w$r&gvDkd%p2J-Nz8)yLk2mS4&*Z=?k diff --git a/science_background/science_background.tex b/science_background/science_background.tex index 9a6da5d..22dd20d 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -55,7 +55,7 @@ the survey will enable research of such breadth that LSST may influence essentially all extragalactic science programs that rely primarily on photometric data. -For studies of galaxies, LSST provide both an unequaled +For studies of galaxies, LSST will provide both an unequaled catalogue of billions of extragalactic sources and high-quality multiband imaging of individual objects. This section of the {\it LSST Galaxies Science Roadmap} presents scientific @@ -251,7 +251,7 @@ \section{Galaxies as Cosmic Structures} Whether the ground-based LSST can effectively probe the exact timing and duration of the transition from clumpy to well-ordered disks remains -unknown, but LSST can undoubtedly contribute studying the +unknown, but LSST can undoubtedly contribute to studying the variation in forming disk structures at the present day. Unusual objects, such as the UV luminous local galaxies identified by \citet{heckman2005a} that display physical features analogous to @@ -315,7 +315,7 @@ \section{Galaxies as Cosmic Structures} how such disks ``end'', how dynamical effects might truncate disks, and whether some disks smoothly transition into stellar halos. LSST will provide such measures and help quantify the -relative importance the physical effects that influence the +relative importance of the physical effects that influence the low surface brightness regions in disks. Other galaxies have low surface brightnesses throughout their stellar structures, and the image quality and sensitivity @@ -363,7 +363,7 @@ \section{Probing the Extremes of Galaxy Formation} then very rare luminous star forming galaxies at early times may immediately proceed the formation of bright quasars. LSST has all the requisite -survey properties (area, mutliband imaging, and +survey properties (area, multiband imaging, and depth) to investigate this long-standing problem \citep{robertson2007a}. The creation of LSST Deep Drilling fields will diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index dfd88c9..88d00c1 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -123,7 +123,7 @@ \subsection{Developing and Optimizing Measurements of Galaxy Environment} lower-mass groups, where the expected photo-$z$ precision will be much coarser than the corresponding the velocity dispersion of typical host halos. -Instead, LSST will likely be better suited to measuring environment by +Instead, LSST will likely be better suited to measure environment by tracing the local galaxy density and identifying filaments. However, LSST is unlike any previous photometric survey and may require new approaches to measuring environment. diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index dfb38e1..a595744 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -53,7 +53,7 @@ \subsection{Low Surface Brightness Galaxies} ~\\ \activities{The key activities for this task include the production of simulated data e.g. from new hydrodynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. Once produce, analysis of simulated images is needed to ensure that LSB galaxies can be accurately detected. This analysis will require the development of new object detection software specifically designed for the detection of LSB galaxies, in particular objects with large size, near or melted with brighter galaxies, and highly irregular and distorted objects. Precursor data sets that can be used to test our methods will need to be identified. Data generated using numerical simulations can be used to examine the types of galaxies produced that have sufficient angular momentum to become LSB disks. These disks can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. -New methods of detecting LSB objects will be engineered, including pixel clustering methods and the labeling of pixels with certain properties, i.e., surface brightness level, SED shape, and proximity to other similar pixels. We will trian our methods on other currently available data sets (KIDS, CFHT etc). These analyses will further +New methods of detecting LSB objects will be engineered, including pixel clustering methods and the labeling of pixels with certain properties, i.e., surface brightness level, SED shape, and proximity to other similar pixels. We will train our methods on other currently available data sets (KIDS, CFHT etc). These analyses will further require the production of realistic simulated LSST images of nearby dwarf galaxies (from high resolution hydrodynamical simulations like New Horizon which has resolutions of tens of parsecs), the identification of nearby semi-resolved dwarf galaxies in precursor data sets to use to develop the LSST tools, and the development and testing of the database search queries for finding candidates of several shapes and sizes. From 55245af9086fff5ea397f05be0666b950f90cad0 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 08:44:13 -0700 Subject: [PATCH 38/64] Added affiliation for Matt Jarvis. Resolves #18 . --- authorlist.tex | 55 +++++++++++++++++++++++++------------------------- 1 file changed, 28 insertions(+), 27 deletions(-) diff --git a/authorlist.tex b/authorlist.tex index 2b4c94d..68e4499 100644 --- a/authorlist.tex +++ b/authorlist.tex @@ -30,23 +30,23 @@ Galaz, Gaspar$^{14}$, Grazian, Andrea$^{24}$, Holwerda, Benne W.$^{25}$, -Jarvis, Matt J.$^{4}$, -Kasliwal, Vishal$^{26,27,28}$, +Jarvis, Matt J.$^{4,26}$, +Kasliwal, Vishal$^{27,28,29}$, Lacerna, Ivan$^{14}$, -Loveday, Jon$^{29}$, -Marshall, Phil$^{30}$, +Loveday, Jon$^{30}$, +Marshall, Phil$^{31}$, Merlin, Emiliano$^{24}$, -Napolitano, Nicola R.$^{31}$, +Napolitano, Nicola R.$^{32}$, Puzia, Thomas H.$^{14}$, Robotham, Aaron$^{5}$, -Salim, Samir$^{32}$, -Sereno, Mauro$^{33}$, +Salim, Samir$^{33}$, +Sereno, Mauro$^{34}$, Snyder, Gregory F.$^{7}$, -Stott, John P.$^{34}$, -Tissera, Patricia B.$^{35}$, -Werner, Norbert$^{36,37,38}$, -Yoachim, Peter$^{39}$, -Borne, Kirk D.$^{40}$, +Stott, John P.$^{35}$, +Tissera, Patricia B.$^{36}$, +Werner, Norbert$^{37,38,39}$, +Yoachim, Peter$^{40}$, +Borne, Kirk D.$^{41}$, and Members of the LSST Galaxies Science Collaboration \vspace*{5mm} @@ -78,21 +78,22 @@ $^{23}$Departamento de Astronomía, Universidad de Concepci{\'{o}}n,Casilla 160-C, Concepción, Chile, $^{24}$INAF - Osservatorio Astronomico di Roma, Via Frascati, 33, I-00078, Monte Porzio Catone (Roma), Italy, $^{25}$Department of Physics and Astronomy, 102 Natural Science Building, University of Louisville, Louisville KY 40292, USA, -$^{26}$Colfax International, 750 Palomar Avenue, Sunnyvale, CA 94085, USA, -$^{27}$University of Pennsylvania, Department of Physics \& Astronomy, 209 S 33rd St, Philadelphia, PA 19104, USA, -$^{28}$Princeton University, Department of Astrophysical Sciences; 4 Ivy Ln, Princeton, NJ 08544, USA, -$^{29}$Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QH, UK, -$^{30}$Kavli Institute for Particle Astrophysics and Cosmology, P.O. Box 20450, MS29, Stanford, CA 94309, USA, -$^{31}$INAF -Osservatorio Astronomico di Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy, -$^{32}$Indiana University, Department of Astronomy, Bloomington, IN 47405, USA, -$^{33}$INAF - Osservatorio Astronomico di Bologna; Dipartimento di Fisica e Astronomia, Universit\`a di Bologna Alma-Mater, via Piero Gobetti 93/3, I-40129 Bologna, Italy, -$^{34}$Department of Physics, Lancaster University, Lancaster LA1 4YB, UK, -$^{35}$Astrophysics Group, Department of Physics - Campus La Casona, Universidad Andres Bello, Fernandez Concha 700, Las Condes, Santiago, Chile, -$^{36}$1 MTA-Eotvos University Hot Universe Research Group, Pazmany Peter Setany 1/A, Budapest, 1117, Hungary, -$^{37}$Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, Brno, 611 37, Czech Republic, -$^{38}$School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan, -$^{39}$University of Washington, Box 351580, U.W. Seattle, WA 98195-1580, USA, -$^{40}$Booz Allen Hamilton, 308 Sentinel Drive, Suite 100, Annapolis Junction, MD 20701, USA +$^{26}$Department of Physics, University of the Western Cape, Bellville 7535, South Africa, +$^{27}$Colfax International, 750 Palomar Avenue, Sunnyvale, CA 94085, USA, +$^{28}$University of Pennsylvania, Department of Physics \& Astronomy, 209 S 33rd St, Philadelphia, PA 19104, USA, +$^{29}$Princeton University, Department of Astrophysical Sciences; 4 Ivy Ln, Princeton, NJ 08544, USA, +$^{30}$Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QH, UK, +$^{31}$Kavli Institute for Particle Astrophysics and Cosmology, P.O. Box 20450, MS29, Stanford, CA 94309, USA, +$^{32}$INAF -Osservatorio Astronomico di Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy, +$^{33}$Indiana University, Department of Astronomy, Bloomington, IN 47405, USA, +$^{34}$INAF - Osservatorio Astronomico di Bologna; Dipartimento di Fisica e Astronomia, Universit\`a di Bologna Alma-Mater, via Piero Gobetti 93/3, I-40129 Bologna, Italy, +$^{35}$Department of Physics, Lancaster University, Lancaster LA1 4YB, UK, +$^{36}$Astrophysics Group, Department of Physics - Campus La Casona, Universidad Andres Bello, Fernandez Concha 700, Las Condes, Santiago, Chile, +$^{37}$1 MTA-Eotvos University Hot Universe Research Group, Pazmany Peter Setany 1/A, Budapest, 1117, Hungary, +$^{38}$Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, Brno, 611 37, Czech Republic, +$^{39}$School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8526, Japan, +$^{40}$University of Washington, Box 351580, U.W. Seattle, WA 98195-1580, USA, +$^{41}$Booz Allen Hamilton, 308 Sentinel Drive, Suite 100, Annapolis Junction, MD 20701, USA From 1033f3bd894ff340585a8243312db5deb3ad3ac4 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 08:46:38 -0700 Subject: [PATCH 39/64] Removed sentence from acknowledgement. Closes issue #13 . --- main.tex | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/main.tex b/main.tex index 243a165..242212a 100644 --- a/main.tex +++ b/main.tex @@ -41,8 +41,7 @@ the science return of the LSST dataset. We want to thank the LSST Corporation for their support in developing this Roadmap and for supporting LSST-related science more broadly. We also wish to thank the LSST Galaxies Science Collaboration members for their efforts -over the years in developing the case for extragalactic science with LSST. Lastly, we -wish to thank Harry Ferguson for his continued efforts to organize this document. +over the years in developing the case for extragalactic science with LSST. } \vspace{1in} From 2f7934fac3afa47870f9f7ea836890aad3134bba Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 21:13:33 -0700 Subject: [PATCH 40/64] Improve science relevance of photo-z section. Text addition closes #17 . --- science_background/science_background.tex | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/science_background/science_background.tex b/science_background/science_background.tex index 22dd20d..7b144a0 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -407,14 +407,20 @@ \section{Photometric Redshifts} \label{sec:sci:gal:bkgnd:photoz} As a purely photometric survey, LSST provides an exquisite data set of two-dimensional images of the sky in six passbands. However, the third dimension of cosmic distance to each galaxy must often -come from photometric redshifts (photo-$z$'s). +come from photometric redshifts (photo-$z$'s). Many quantities that LSST data can +reveal about distant galaxy populations, including intrinsic luminosities, physical +sizes, star formation rates, and stellar masses, will ultimately rely on photo-$z$ +determinations. The engineering of accurate and precise photo-$z$ methods +therefore represents an important science effort for LSST science collaborations. + Spectroscopic distance estimates rely on the identification of atomic or molecular transitions in expensive, high resolution spectra. In contrast, photometric redshifts estimate the rough distance to an object based on its broad-band photometric colors and, potentially, other properties measurable from imaging. Photo-$z$ measurements are akin to determining redshifts from a very low-resolution but high signal-to-noise spectrum, where each broad-band filter contributes a single sample in that spectrum. Photometric redshifts are therefore sensitive to the large-scale features of a galaxy spectral energy distribution (e.~g.,~the 4000~\AA\ and Lyman breaks), but in general lack the definitiveness of a redshift measured from multiple well-centroided spectral features (e.g., a pair of emission or absorption lines of known separation). As a result, photometric redshifts will generally be more uncertain than spectroscopic redshift estimates and can be affected by degeneracies in the color-redshift relation. By relying on imaging data alone, we will be able to measure photo-$z$'s for billions of galaxies in the LSST survey. -As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys.Assigning an incorrect redshift to a galaxy also assigns an incorrect luminosity +As errors in the assigned redshift propagate directly to physical quantities of interest, understanding the uncertainties and systematic errors in photo-$z$'s is of the utmost importance for LSST and other photometric surveys. +Assigning an incorrect redshift to a galaxy also assigns an incorrect luminosity owing to misestimation of both the distance modulus and $k$-corrections, and hence can bias estimates of the luminosity function. Errors in redshift will also bias the inferred rest-frame colors of a galaxy, propagating to errors in the inferred spectral type, stellar mass, star formation rate, and other quantities. Ideally, estimates of any physical quantity should be performed jointly with a redshift fit, and the expected uncertainties and degeneracies should be fully understood and propagated if measurements are to be made in an unbiased way. From b63ec56cf2edac6e6489dc37f672a6a29b783008 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 21:21:32 -0700 Subject: [PATCH 41/64] Add requested reference to AMICO. Closes issue #7 . --- references.bib | 13 +++++++++++++ task_lists/clss/clss.tex | 4 +++- 2 files changed, 16 insertions(+), 1 deletion(-) diff --git a/references.bib b/references.bib index 0e791bf..bcb3498 100644 --- a/references.bib +++ b/references.bib @@ -165,6 +165,19 @@ @ARTICLE{barth2007 adsurl = {http://cdsads.u-strasbg.fr/abs/2007AJ....133.1085B}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{bellagamba2017a, + author = {{Bellagamba}, F. and {Roncarelli}, M. and {Maturi}, M. and {Moscardini}, L. + }, + title = "{AMICO: optimised detection of galaxy clusters in photometric surveys}", + journal = {ArXiv e-prints}, +archivePrefix = "arXiv", + eprint = {1705.03029}, + keywords = {Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies}, + year = 2017, + month = may, + adsurl = {http://adsabs.harvard.edu/abs/2017arXiv170503029B}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{bowler2017a, author = {{Bowler}, R.~A.~A. and {Dunlop}, J.~S. and {McLure}, R.~J. and {McLeod}, D.~J.}, diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 88d00c1..c17ddbc 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -68,7 +68,9 @@ \subsection{Identifying and Characterizing Clusters} sequence method, will be hampered by the limited wavelength coverage of LSST. For example, at $z \gtrsim 1.5$, near-IR photometry is required to -identify systems with Balmer/$4000$\AA\ breaks. +identify systems with Balmer/$4000$\AA\ breaks. +Exploration of optimal filter methods could improve cluster identification +\citep[e.g.,][]{bellagamba2017a}. To maximize cluster science with LSST, new techniques for cluster identification and the incorporate complementary data from projects such as \emph{Euclid} or \emph{eROSITA} must be devised. From dafc2679fec3c1b4b5c3df0746288e3c1fa5b75f Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 21:30:46 -0700 Subject: [PATCH 42/64] Removed british spelling. --- task_lists/clss/clss.tex | 2 +- task_lists/high_z/high_z.tex | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index c17ddbc..ce4a90b 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -248,7 +248,7 @@ \subsection{Disentangling Complicated Lines-of-Sight} A tool is therefore envisaged that can take an input catalogue of cluster centers that has been obtained from LSST or any other dataset (e.g.~\emph{Planck}, \emph{eROSITA}), extract the -basic L2 LSST photometry of objects within a cone centred on the +basic L2 LSST photometry of objects within a cone centered on the cluster center, and compute the redshift probability distribution $p(z)$ of each galaxy based on a cluster-specific algorithm. When available, t diff --git a/task_lists/high_z/high_z.tex b/task_lists/high_z/high_z.tex index ed9403c..328aee2 100644 --- a/task_lists/high_z/high_z.tex +++ b/task_lists/high_z/high_z.tex @@ -72,7 +72,7 @@ \subsection{High-Redshift Galaxies and Interlopers in LSST Simulations} Using the LSST simulations, one wants to devise the most effective way of separating these different populations by utilizing both photometric and morphological information for the sources. Based on experience with ground-based surveys such as the Dark Energy Survey and VISTA, one expects LSST images to spatially resolve at least some of the most luminous $z > 6$ galaxies \citep{willott2013a, bowler2017a}. -For fainter high-redshift galaxies however, a morphological distinction between faint ultra-cool brown dwarfs may not be possible, and further information such as near-infrared colours or proper motions will be required for identification. +For fainter high-redshift galaxies however, a morphological distinction between faint ultra-cool brown dwarfs may not be possible, and further information such as near-infrared colors or proper motions will be required for identification. } ~\\ \activities{ From 8cef41257e9cb8962ededece3e881747037ce921 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 21:34:29 -0700 Subject: [PATCH 43/64] Revised BCG deliverable in AGN section. Closes #14 . --- task_lists/agn/agn.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index dd5747d..606e457 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -119,7 +119,7 @@ \subsection{AGN Feedback in Clusters} \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item Investigation of the number of BCGs and the mass range of their clusters with redshift that LSST will likely observe. +\item Investigation and quantification of the ability of the LSST pipeline to select BCGs using precursor datasets such as the HSC survey. \item Compilation of existing and forthcoming radio and X-ray data available for AGN feedback studies (XCS, eROSITA, SKA-pathfinders, SUMSS, etc.). \item Assessment of theoretical predictions expected for the multi-wavelength properties of AGN host galaxies in clusters or groups (e.g., cosmological simulations such as EAGLE or more detailed single cluster studies). From e76253a679c58214e6a46b879cf7c6681e9e9bcd Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 21:39:56 -0700 Subject: [PATCH 44/64] Rewording on LSST pipeline requirements for clustering measurements. Closes #15 --- task_lists/clss/clss.tex | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index ce4a90b..6506e26 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -206,9 +206,7 @@ \subsection{Enabling and Optimizing Measurements of Galaxy Clustering} \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item Guidance for LSST galaxy pipelines to include all the necessary -information for measurements of the correlation function and related -statistics to take place once LSST data is available. +\item Guidance for LSST galaxy pipelines to include all the necessary information for measurements of the correlation function and related statistics to take place once LSST data is available. This deliverable requires the engineering of ancillary products such as masks and maps of completeness as a function of galaxy properties. \item Development and refinement of techniques for measuring galaxy clustering of large LSST galaxy samples. Together these will enable realizing the full potential of LSST data for large-scale structure studies and From 1ceeeb960a6c795c92b4b6f08ff14a1705834ff3 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 22:00:27 -0700 Subject: [PATCH 45/64] Minor text format issue in 3.6.4. --- task_lists/lsb/lsb.tex | 31 +++++++++++++++++++++++++++++++ 1 file changed, 31 insertions(+) diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index a595744..fd7048b 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -100,6 +100,37 @@ \subsection{Faint Outskirts of Galaxies} \end{task} +\subsection{Sky Estimation} +\tasktitle{Sky Estimation} +\begin{task} +\label{task:lsb:task_label} +\motivation{ +LSST is likely to reveal new aspects of galaxies as low surface brightness objects. A relatively unexplored area is ultra-low surface brightness morphology and tails over a wide range of angular scales at levels of 31-32 mag/sq.~arcsec. Accurate sky estimation is key. There is a wide literature on failed attempts at unbiased sky estimation, from SDSS Photo, to SExtractor, to GalFit and PyMorph. The problem is typically encountered on scales large compared with the PSF where the counts from the object become indistinguishable from the ``sky'' counts. For example, fits of Sersic profiles [after PSF convolution] suffer from bias at large Sersic index due to sky mis-estimation (usually over-subtraction of sky due to systematic non-detection of fainter objects). +~\\~\\ +The discovery space is large: LSB features can exist on scales of arcseconds to many arcminutes -- spanning the majority of faint galaxies at redshift $z\sim 1$ to more nearby LSB galaxies. In the past it has been assumed that galaxies at all redshifts fit the profiles of low-z galaxies, and that the surface brightness level beyond $\sim$10 half light radii represents the sky background, as opposed to some extended LSB halo. In the era of LSST, we can afford to let the data speak for themselves. +~\\~\\ +The correct sky estimation on any angular scale is actually an ill-posed problem. The proper sky for barely resolved galaxies at high redshift is in principle quite different from the correct sky level for large angular scale LSB features. Indeed, the flux from barely resolved galaxies sits on top of the fainter larger angular scale flux associated with arcminute scale LSB extragalactic features, which in turn sits on top of the starlight reflected by Galactic cirrus, night sky surface brightness caused by atmosphere emission and scattered light from bright objects in the camera and the atmosphere. Thus for LSST, there will be a separate sky estimate appropriate for each of the different morphological classes of LSB objects. To make the problem tractable, a multi-component sky model must be built. +} +~\\ +\activities{ +The research program starts with the current best methods, improving sky estimates on all angular scales via new algorithms, and then validation via simulations. The sky model in principle can be built using knowledge of the LSST system, locations of bright objects, the observational data, and statistical summaries of faint galaxy counts from HST. The first step is to detect all objects above a position-variable local sky estimate, masking them, and then growing the masks. The remaining pixels contain undetected galaxies, giving an over-estimate of the sky level around compact objects if left uncorrected. Statistical faint galaxy counts can help in making these corrections. When corrected, the Poisson noise from the remaining sky may be fit with a Gaussian. Even then, 3-$\sigma$ clipping and/or one-sided fitting may be required. This entire process is recursive on every angular scale where there are important sky components. +~\\~\\ +LSST data management are planning novel algorithms of this general sort, and close coordination will be necessary and beneficial. The Dark Energy Science Collaboration (DESC) Science Roadmap\footnote{The DESC Science Roadmap is available at: \url{http://lsst-desc.org/sites/default/files/DESC_SRM_V1_0.pdf}} includes plans for realistic image-based simulations of the LSST sky. In coordination with DESC, the inclusion of faint, large-scale LSB objects in future Data Challenge catalogs and images would benefit all groups involved in testing algorithms and characterizing LSB objects. Improvements we make may be ingested by LSST DM as a Level-3 contribution. LSB ghosts due to reflected bright star light in the camera should also be included. +} +~\\ +\deliverables{%Deliverables over the next several years from the activities described above include the following: +~ +\begin{enumerate} +\item In coordination with the Dark Energy Science Collaboration, generate realistic image simulations. Faint, large-scale LSB objects should be included in Data Challenge image based simulations. The level of realism in the simulations can be extended to what is physically possible, rather than limited to conventional morphological models. +\item Recursive sky model building algorithms applied to these simulations, with statistical galaxy count corrections. +\item Development of metrics for successful detection and characterization of each extragalactic component. +\item Tests of degeneracies among models, and sensitivity to priors. Validation on simulations, on various types of objects. +\item Tests on LSST precursor deep survey data, for performance estimates. +\item Tests on deep LSST commissioning data. +\end{enumerate} +} +\end{task} + \subsection{Intracluster Light} \tasktitle{Intracluster Light} From d5381645647a77822516887a4cc67e2b007178e1 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 22:11:49 -0700 Subject: [PATCH 46/64] Dara's updates to AGN section Closes issue # 12 . --- references.bib | 19 +++++++++++++++++++ task_lists/agn/agn.tex | 13 ++++++++----- 2 files changed, 27 insertions(+), 5 deletions(-) diff --git a/references.bib b/references.bib index bcb3498..24d1185 100644 --- a/references.bib +++ b/references.bib @@ -1369,6 +1369,25 @@ @article{ponomareva2016a Year = 2016, } %RRRRRRRRRRR +@ARTICLE{richards2006a, + author = {{Richards}, G.~T. and {Lacy}, M. and {Storrie-Lombardi}, L.~J. and + {Hall}, P.~B. and {Gallagher}, S.~C. and {Hines}, D.~C. and + {Fan}, X. and {Papovich}, C. and {Vanden Berk}, D.~E. and {Trammell}, G.~B. and + {Schneider}, D.~P. and {Vestergaard}, M. and {York}, D.~G. and + {Jester}, S. and {Anderson}, S.~F. and {Budav{\'a}ri}, T. and + {Szalay}, A.~S.}, + title = "{Spectral Energy Distributions and Multiwavelength Selection of Type 1 Quasars}", + journal = {\apjs}, + eprint = {astro-ph/0601558}, + keywords = {Catalogs, Galaxies: Active, Infrared: Galaxies, Galaxies: Quasars: General, Radio Continuum: Galaxies, Surveys, Ultraviolet: Galaxies, X-Rays: Galaxies}, + year = 2006, + month = oct, + volume = 166, + pages = {470-497}, + doi = {10.1086/506525}, + adsurl = {http://adsabs.harvard.edu/abs/2006ApJS..166..470R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @ARTICLE{robertson2007a, author = {{Robertson}, B. and {Li}, Y. and {Cox}, T.~J. and {Hernquist}, L. and {Hopkins}, P.~F.}, diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index 606e457..9e2060a 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -18,7 +18,7 @@ \subsection{AGN Selection from LSST Data} \label{task:agn:selection} \motivation{ LSST multiband photometry may select Active Galactic Nuclei using a variety of different methods. At optical and near infrared wavelengths, the distinctive colors of AGN -at particular redshifts enables their photometric selection. +at particular redshifts enables their photometric selection \citep[e.g.,][]{richards2006a}. The LSST data will therefore augment methods that rely on X-ray or radio activity, or the identification of emission lines in spectroscopic data. LSST will also open up, in a more practical way, the identification of AGN based on their variability. @@ -45,7 +45,7 @@ \subsection{AGN Selection from LSST Data} \begin{enumerate} \item Creation of a cross-matched catalog of known AGN selected and verified using different methods. \item Understanding of AGN variability sensitivity given the nominal LSST cadence. -\item Development of algorithms for color selection account for AGN variability. +\item Development of algorithms that probe how color selection accounts for AGN variability. \end{enumerate} } \end{task} @@ -176,7 +176,8 @@ \subsection{AGN Photometric Redshifts from LSST Data} ~ \begin{enumerate} \item Development of AGN host color selection criteria, and an identification of objects for which color selection might prove ambiguous or degenerate. -\item Exploration of multiwavelength, morphological, or variability information that might break photo-$z$ degeneracies. +\item Analysis of multiwavelength, morphological, or variability information that might break photo-$z$ degeneracies. This task complements work described in Section \ref{task:photo_z:color_simulations} +(Photometric Redshifts) and should be coordinated with those efforts. \end{enumerate} } \end{task} @@ -201,13 +202,15 @@ \subsection{AGN Merger Signatures from LSST Data} Run the LSST software stack on these images, and engineer metrics that quantify the accurate detection of galaxy mergers with and without AGN. +Activities for detecting some of these low surface brightness (LSB) features will parallel work described in Section \ref{task:gal:lsb} +(Galaxy Evolution) and should be coordinated with those efforts. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: ~ \begin{enumerate} -\item Characterization and optimization of the ability of the LSST Level 2 data to enable the detection of galaxy mergers with AGN. -\item Identification of merging galaxy properties or categories that will prove challenging to measure using the LSST datasets. +\item Characterization and optimization of the ability of the LSST Level 2 data to enable the detection of galaxy mergers that host AGN. +\item Identification of catalog parameters or merging galaxy images with properties that will prove challenging to recognize (semi-)automatically in the LSST dataset. \end{enumerate} } \end{task} From 8d452b653aa452174e2e7052d0b239bccfb8a3d7 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 22:23:57 -0700 Subject: [PATCH 47/64] Edits suggested by Nicola. Closes issue #21 --- references.bib | 29 +++++++++++++++++++++++ science_background/science_background.tex | 3 ++- task_lists/ddf/ddf.tex | 2 +- task_lists/galaxies/galaxies.tex | 2 +- task_lists/lsb/lsb.tex | 2 +- 5 files changed, 34 insertions(+), 4 deletions(-) diff --git a/references.bib b/references.bib index 24d1185..2b14f58 100644 --- a/references.bib +++ b/references.bib @@ -312,6 +312,35 @@ @ARTICLE{darg2010a adsurl = {http://adsabs.harvard.edu/abs/2010MNRAS.401.1552D}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } +@ARTICLE{dejong2015a, + author = {{de Jong}, J.~T.~A. and {Verdoes Kleijn}, G.~A. and {Boxhoorn}, D.~R. and + {Buddelmeijer}, H. and {Capaccioli}, M. and {Getman}, F. and + {Grado}, A. and {Helmich}, E. and {Huang}, Z. and {Irisarri}, N. and + {Kuijken}, K. and {La Barbera}, F. and {McFarland}, J.~P. and + {Napolitano}, N.~R. and {Radovich}, M. and {Sikkema}, G. and + {Valentijn}, E.~A. and {Begeman}, K.~G. and {Brescia}, M. and + {Cavuoti}, S. and {Choi}, A. and {Cordes}, O.-M. and {Covone}, G. and + {Dall'Ora}, M. and {Hildebrandt}, H. and {Longo}, G. and {Nakajima}, R. and + {Paolillo}, M. and {Puddu}, E. and {Rifatto}, A. and {Tortora}, C. and + {van Uitert}, E. and {Buddendiek}, A. and {Harnois-D{\'e}raps}, J. and + {Erben}, T. and {Eriksen}, M.~B. and {Heymans}, C. and {Hoekstra}, H. and + {Joachimi}, B. and {Kitching}, T.~D. and {Klaes}, D. and {Koopmans}, L.~V.~E. and + {K{\"o}hlinger}, F. and {Roy}, N. and {Sif{\'o}n}, C. and {Schneider}, P. and + {Sutherland}, W.~J. and {Viola}, M. and {Vriend}, W.-J.}, + title = "{The first and second data releases of the Kilo-Degree Survey}", + journal = {\aap}, +archivePrefix = "arXiv", + eprint = {1507.00742}, + keywords = {methods: observational, surveys, galaxies: general, large-scale structure of Universe}, + year = 2015, + month = oct, + volume = 582, + eid = {A62}, + pages = {A62}, + doi = {10.1051/0004-6361/201526601}, + adsurl = {http://adsabs.harvard.edu/abs/2015A%26A...582A..62D}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} @article{driver2009a, Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, Adsurl = {http://adsabs.harvard.edu/abs/2009A%26G....50e..12D}, diff --git a/science_background/science_background.tex b/science_background/science_background.tex index 7b144a0..643e194 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -68,7 +68,8 @@ more than twenty years after the start of the Sloan Digital Sky Survey \citep{york2000a} and subsequent precursor surveys including PanSTARRS \citep{kaiser2010a}, the Subaru -survey with Hyper Suprime-Cam \citep{miyazaki2012a}, and the Dark +survey with Hyper Suprime-Cam \citep{miyazaki2012a}, the +Kilo-Degree Survey \citep{dejong2015a}, and the Dark Energy Survey \citep{flaugher2005a}. Relative to these prior efforts, extragalactic science breakthroughs generated by LSST will likely benefit from its increased area, source diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index e0ca659..430c8eb 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -78,7 +78,7 @@ \subsection{Data Processing} \motivation{ Getting the most out of the DDFs may require data processing beyond that required for the LSST WFD Survey. A variety of issues will need consideration in trying to optimize the science output, -including different strategies for making co-adds, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features, deblending overlapping objects, or estimating photometric redshifts. Reprocessing the DDF data while utilizing +including different strategies for making co-adds, masking bright stars and ghosts, determining sky levels, treating scattered light, detecting and characterizing faint or low-surface brightness features, deblending overlapping objects, or estimating photometric redshifts. Reprocessing the DDF data while utilizing supporting observations may prove feasible. While there exists a clear advantage to issue one ``official'' LSST-released catalog at Level 2, defining such a catalog to support a very broad range of science remains challenging. diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 23783a5..2c7f198 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -249,7 +249,7 @@ \subsection{Galaxy Structural Parameters} will allow for the identification dwarf galaxies at $z\sim0.5$, and up to $M_*+2$ galaxies in clusters and field at $z\sim1.5$, and reach deep enough to study the structural parameters (size, Sersic index, ellipticity etc.) of $M_*$ galaxies at $z\sim1.2$ (for seeing$<0.5$"). The LSST data will allow for size, Sersic index, and bulge-to-disk ratio for over a billion galaxies to be correlatedd with mass, color, and other intrinsic properties at different epochs and thereby clarify the mechanisms that drive the galaxy assembly and transformation. } ~\\ -\activities{Preparatory work will consist of testing parametric methods for seeing-convolved 2D fitting of the galaxy light distribution on precursor surveys (e.g. Subaru or KiDS) and on simulated LSST images, with the aim of providing viable tools for automatic image masking, catalogue extraction, source classification, and 2D galaxy fitting +\activities{Preparatory work will consist of testing parametric methods for seeing-convolved 2D fitting of the galaxy light distribution on precursor surveys (e.g., HSC or KiDS) and on simulated LSST images, with the aim of providing viable tools for automatic image masking, catalogue extraction, source classification, and 2D galaxy fitting in Level 3 datasets. This task will involve optimizing tool performance to guarantee meet time metrics (e.g., processing 100 million LSST galaxies in all bands on a single week). The surface brightness profile of galaxies in different bands will finally generate a catalog of all relevant structural parameters via Level 3 products. } diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index fd7048b..dc06906 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -78,7 +78,7 @@ \subsection{Faint Outskirts of Galaxies} \motivation{ The outskirts of nearby galaxies, loosely defined as the regions below $ 25-26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ in surface brightness, have long been studied mainly in neutral -hydrogen, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, Subaru, GTC). The main science driver for studying the outskirts of galaxies is understanding the assembly, formation, and evolution of galaxies. These studies can be performed +hydrogen, and later in the UV thanks to the exquisite imaging by GALEX. Deep optical imaging of these regions has been performed on individual objects or on small samples by using extremely long exposures on small (including amateur and dedicated) telescopes, using the SDSS Stripe82 area, and using deep exposures with large telescopes (e.g., CFHT, VST, Subaru, GTC). The main science driver for studying the outskirts of galaxies is understanding the assembly, formation, and evolution of galaxies. These studies can be performed through imaging and subsequent parameterization of structural components such as outer exponential disks, thick disks, tidal streams, and stellar halos. From numerical modeling, it is known that the parameters of these components can give detailed information on the early history of the galaxies. For instance, halo properties, and structure within the stellar halo are tightly related to the accretion and merging history, as illustrated by the imaging of structures in the stars in the outskirts of M31 and other local group galaxies.\\ ~\\ Ultra-deep imaging over large areas of the sky, as will be provided by LSST, can in principle be used to extend the study so far mostly limited to Local Group galaxies to 1000s of nearby galaxies, and even, at lower physical scales, to galaxies at higher redshifts. It is imperative, however, to understand and correct for a number of systematic effects, including but not limited to internal reflections and scattered light inside the telescope/instrument, overall PSF, including light scattered by the brighter parts of the galaxy under consideration, flat fielding, masking, residual background subtraction, and foreground material (in particular Galactic cirrus). Many of these effects, and in particular the atmosphere part of the PSF vary with position and/or time on timescales as short as minutes, need to be understood before stacking. The systematics will affect some measurements more than others -- for instance, linear features such as tidal streams will be less affected by overall PSF. From 533f1afb8f4b6b1fb1e8813b22bc6e0b0bee5755 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 23:14:22 -0700 Subject: [PATCH 48/64] Address MED comments. Closes issue #19 --- references.bib | 87 +++++++++++------------ science_background/science_background.tex | 15 ++-- task_lists/agn/agn.tex | 6 +- task_lists/aux/aux.tex | 25 ++++--- task_lists/clss/clss.tex | 4 +- task_lists/ddf/ddf.tex | 4 +- task_lists/galaxies/galaxies.tex | 8 +-- task_lists/lsb/lsb.tex | 9 +-- task_lists/photo_z/photo_z.tex | 12 ++-- 9 files changed, 85 insertions(+), 85 deletions(-) diff --git a/references.bib b/references.bib index 2b14f58..6380ae1 100644 --- a/references.bib +++ b/references.bib @@ -3,7 +3,7 @@ @ARTICLE{LSSTSciBook {Anderson}, S.~F. and {Andrew}, J.~R. and {Angel}, J.~R.~P. and {Armus}, L. and {Arnett}, D. and {Asztalos}, S.~J. and {Axelrod}, T.~S. and et al.}, title = "{LSST Science Book, Version 2.0}", - journal = {ArXiv e-prints}, + journal = {arXiv:0912.0201}, archivePrefix = "arXiv", eprint = {0912.0201}, primaryClass = "astro-ph.IM", @@ -16,7 +16,7 @@ @ARTICLE{LSSTSciBook @ARTICLE{LSSTDESC, author = {{LSST Dark Energy Science Collaboration}}, title = "{Large Synoptic Survey Telescope: Dark Energy Science Collaboration}", - journal = {ArXiv e-prints}, + journal = {arXiv:1211.0310}, archivePrefix = "arXiv", eprint = {1211.0310}, primaryClass = "astro-ph.CO", @@ -450,7 +450,7 @@ @article{fernandez2013a Date-Added = {2017-04-25 15:27:22 +0000}, Date-Modified = {2017-04-25 15:27:22 +0000}, Eprint = {1303.2659}, - Journal = {ArXiv e-prints}, + Journal = {arXiv:1303.2659}, Keywords = {Astrophysics - Galaxy Astrophysics, Astrophysics - Cosmology and Extragalactic Astrophysics}, Month = mar, Primaryclass = {astro-ph.GA}, @@ -458,16 +458,11 @@ @article{fernandez2013a Year = 2013 } @article{fernandez2016a, - Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, - Adsurl = {http://adsabs.harvard.edu/abs/2016ApJ...824L...1F}, - Archiveprefix = {arXiv}, - Arxivurl = {http://arxiv.org/abs/1606.00013}, Author = {{Fern{\'a}ndez}, X. and {Gim}, H.~B. and {van Gorkom}, J.~H. and {Yun}, M.~S. and {Momjian}, E. and {Popping}, A. and {Chomiuk}, L. and {Hess}, K.~M. and {Hunt}, L. and {Kreckel}, K. and {Lucero}, D. and {Maddox}, N. and {Oosterloo}, T. and {Pisano}, D.~J. and {Verheijen}, M.~A.~W. and {Hales}, C.~A. and {Chung}, A. and {Dodson}, R. and {Golap}, K. and {Gross}, J. and {Henning}, P. and {Hibbard}, J. and {Jaff{\'e}}, Y.~L. and {Donovan Meyer}, J. and {Meyer}, M. and {Sanchez-Barrantes}, M. and {Schiminovich}, D. and {Wicenec}, A. and {Wilcots}, E. and {Bershady}, M. and {Scoville}, N. and {Strader}, J. and {Tremou}, E. and {Salinas}, R. and {Ch{\'a}vez}, R.}, Date-Added = {2017-04-25 15:27:24 +0000}, Date-Modified = {2017-04-25 15:27:24 +0000}, Doi = {10.3847/2041-8205/824/1/L1}, Eid = {L1}, - Eprint = {1606.00013}, Journal = {\apjl}, Keywords = {galaxies: evolution, galaxies: starburst, radio lines: galaxies}, Month = jun, @@ -604,15 +599,15 @@ @ARTICLE{hoekstra2015a adsurl = {http://adsabs.harvard.edu/abs/2015MNRAS.449..685H}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} } -@inproceedings{holwerda2010a, +@article{holwerda2010a, Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, Adsurl = {http://adsabs.harvard.edu/abs/2010iska.meetE..68H}, Archiveprefix = {arXiv/1007.4101}, Author = {{Holwerda}, B. and {Blyth}, S.}, - Booktitle = {ISKAF2010 Science Meeting}, Date-Added = {2017-04-25 15:29:43 +0000}, Date-Modified = {2017-04-25 15:29:43 +0000}, Eprint = {1007.4101}, + journal = {arXiv:1007.4101}, Primaryclass = {astro-ph.CO}, Title = {{Trumpeting the Vuvuzela: The deepest HI observations with MeerKAT}}, Year = 2010 @@ -684,7 +679,7 @@ @ARTICLE{ivezic2008a {Wood-Vasey}, W.~M. and {Yoachim}, P. and {Zhan}, H. and {for the LSST Collaboration} }, title = "{LSST: from Science Drivers to Reference Design and Anticipated Data Products}", - journal = {ArXiv e-prints}, + journal = {arXiv:0805.2366}, archivePrefix = "arXiv", eprint = {0805.2366}, keywords = {Astrophysics}, @@ -1325,7 +1320,7 @@ @article{oh2015a Date-Added = {2017-04-25 15:26:51 +0000}, Date-Modified = {2017-04-25 15:26:51 +0000}, Eprint = {1502.01281}, - Journal = {ArXiv e-prints}, + Journal = {arXiv:1502.01281}, Keywords = {Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics}, Month = feb, Title = {{High-resolution mass models of dwarf galaxies from LITTLE THINGS}}, @@ -1391,7 +1386,7 @@ @article{ponomareva2016a Date-Added = {2017-04-25 15:24:09 +0000}, Date-Modified = {2017-04-25 15:24:09 +0000}, Eprint = {1609.00378}, - Journal = {ArXiv e-prints}, + Journal = {arXiv:1609.00378}, Keywords = {Astrophysics - Astrophysics of Galaxies}, Month = sep, Title = {{Detailed HI kinematics of Tully-Fisher calibrator galaxies}}, @@ -1527,40 +1522,38 @@ @ARTICLE{stott2012a adsnote = {Provided by the SAO/NASA Astrophysics Data System} } %TTTTTTTTTTTTTTTTT -@article{tiley2016a, - Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, - Adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.tmp..713T}, - Archiveprefix = {arXiv}, - Arxivurl = {http://arxiv.org/abs/1604.06103}, - Author = {{Tiley}, A.~L. and {Stott}, J.~P. and {Swinbank}, A.~M. and {Bureau}, M. and {Harrison}, C.~M. and {Bower}, R. and {Johnson}, H.~L. and {Bunker}, A.~J. and {Jarvis}, M.~J. and {Magdis}, G. and {Sharples}, R. and {Smail}, I. and {Sobral}, D. and {Best}, P.}, - Date-Added = {2017-04-25 15:25:09 +0000}, - Date-Modified = {2017-04-25 15:25:09 +0000}, - Doi = {10.1093/mnras/stw936}, - Eprint = {1604.06103}, - Journal = {\mnras}, - Keywords = {galaxies: evolution, galaxies: general, galaxies: kinematics and dynamics}, - Month = apr, - Title = {{The KMOS Redshift One Spectroscopic Survey (KROSS): The Tully-Fisher Relation at z {\tilde} 1}}, - Year = 2016 +@ARTICLE{tiley2016a, + author = {{Tiley}, A.~L. and {Stott}, J.~P. and {Swinbank}, A.~M. and + {Bureau}, M. and {Harrison}, C.~M. and {Bower}, R. and {Johnson}, H.~L. and + {Bunker}, A.~J. and {Jarvis}, M.~J. and {Magdis}, G. and {Sharples}, R. and + {Smail}, I. and {Sobral}, D. and {Best}, P.}, + title = "{The KMOS Redshift One Spectroscopic Survey (KROSS): the Tully-Fisher relation at z {\tilde} 1}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1604.06103}, + keywords = {galaxies: evolution, galaxies: general, galaxies: kinematics and dynamics}, + year = 2016, + month = jul, + volume = 460, + pages = {103-129}, + doi = {10.1093/mnras/stw936}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.460..103T}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} } -@article{tiley2016b, - Adscomment = {Accepted for publication in MNRAS. 27 pages, 10 figures; doi:10.1093/mnras/stw1545}, - Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, - Adsurl = {http://adsabs.harvard.edu/abs/2016arXiv160701393T}, - Archiveprefix = {arXiv}, - Arxivurl = {http://arxiv.org/abs/1607.01393}, - Author = {{Tiley}, A.~L. and {Bureau}, M. and {Saintonge}, A. and {Topal}, S. and {Davis}, T.~A. and {Torii}, K.}, - Date-Added = {2017-04-25 15:26:22 +0000}, - Date-Modified = {2017-04-25 15:26:22 +0000}, - Doi = {10.1086/338962}, - Eprint = {1607.01393}, - Journal = {ArXiv e-prints}, - Keywords = {Astrophysics - Astrophysics of Galaxies}, - Month = jul, - Pages = {L69-L72}, - Title = {{The Tully-Fisher Relation of COLD GASS Galaxies}}, - Volume = {564}, - Year = 2016 +@ARTICLE{tiley2016b, + author = {{Tiley}, A.~L. and {Bureau}, M. and {Saintonge}, A. and {Topal}, S. and {Davis}, T.~A. and {Torii}, K.}, + title = "{The Tully-Fisher relation of COLD GASS Galaxies}", + journal = {\mnras}, +archivePrefix = "arXiv", + eprint = {1607.01393}, + keywords = {galaxies: general}, + year = 2016, + month = oct, + volume = 461, + pages = {3494-3515}, + doi = {10.1093/mnras/stw1545}, + adsurl = {http://adsabs.harvard.edu/abs/2016MNRAS.461.3494T}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} } @article{trachternach2008a, Adsnote = {Provided by the SAO/NASA Astrophysics Data System}, @@ -1634,7 +1627,7 @@ @article{verheijen2010a Date-Added = {2017-04-25 15:27:10 +0000}, Date-Modified = {2017-04-25 15:27:10 +0000}, Eprint = {1009.0279}, - Journal = {ArXiv e-prints}, + Journal = {arXiv:1009.0279}, Keywords = {Astrophysics - Cosmology and Extragalactic Astrophysics}, Month = sep, Primaryclass = {astro-ph.CO}, diff --git a/science_background/science_background.tex b/science_background/science_background.tex index 643e194..834b691 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -6,8 +6,7 @@ {\justify -Galaxies represent fundamental astronomical objects -outside our own Milky Way. +Galaxies comprise one of the most fundamental classes of astronomical objects. The large luminosities of galaxies enable their detection to extreme distances, providing abundant and far-reaching probes into the depths of the universe. @@ -195,7 +194,7 @@ \section{Galaxies as Cosmic Structures} galactic radius, populating stellar orbits that differentially rotate about the galactic center and somehow organize into spiral features. -Many disk galaxies contain (pseduo-)bulges that form through +Many disk galaxies contain (pseudo-)bulges that form through a combination of violent relaxation and orbital dynamics. These disk galaxy features contrast with systems where spheroidal stellar distributions dominate the galactic @@ -228,7 +227,9 @@ \section{Galaxies as Cosmic Structures} of the light distribution including the Gini and M20 metrics that quantify the surface brightness uniformity and spatial moment of -dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume of the LSST dataset, which will also change on short timescales in terms of depth, new machine-learning algorithms \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided +dominant pixels in a galaxy image \citep{abraham2003a,lotz2004a}. Given the volume +and steadily increasing depth of the LSST dataset, +new machine-learning algorithms \citep[e.g.][; Hausen \& Robertson, in prep]{hocking2015a} that enable fast morphological classifications of the LSST survey will be critical in enabling morphological studies from this unique dataset. Collectively, these morphological measures provided by analyzing the LSST imaging data will enable a consummate determination of the relation between structural properties and other features of @@ -345,7 +346,7 @@ \section{Galaxies as Cosmic Structures} \section{Probing the Extremes of Galaxy Formation} \label{sec:sci:gal:bkgnd:rare} -The deep, multiband imaging LSST provides over an enormous +The deep, multiband imaging that LSST will provide over an enormous area will enable the search for galaxies that form in the rarest environments, under the most unusual conditions, and at very early times. By probing the extremes of @@ -368,8 +369,8 @@ \section{Probing the Extremes of Galaxy Formation} depth) to investigate this long-standing problem \citep{robertson2007a}. The creation of LSST Deep Drilling fields will -enable a measurement of the very bright end -of the high-redshift galaxy luminosity function. +enable a precise measurement of the +high-redshift galaxy luminosity function. Independent determinations of the distribution of galaxy luminosities at $z\sim6$ show substantial variations at the bright end. The origin of diff --git a/task_lists/agn/agn.tex b/task_lists/agn/agn.tex index 9e2060a..a3a9c2b 100644 --- a/task_lists/agn/agn.tex +++ b/task_lists/agn/agn.tex @@ -110,10 +110,10 @@ \subsection{AGN Feedback in Clusters} The interplay between the BCG, its black hole, and the cluster gas can then be studied, providing an assessment of the balance of energies involved and a direct comparison with theoretical models of AGN feedback. SDSS has enabled this multi-wavelength analysis for a few hundred clusters at $z<0.3$, -but LSST cluster datasets to reach $z>1$. +but LSST cluster datasets will reach deeper to redshifts $z>1$. Such studies hold implications for cosmological studies by helping to distinguish between -X-ray gas properties strongly influenced by AGN in addition to the -cluster mass. +X-ray gas properties strongly influenced by AGN or simply the +cluster gravitational potential. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: diff --git a/task_lists/aux/aux.tex b/task_lists/aux/aux.tex index 0b87add..f715a81 100644 --- a/task_lists/aux/aux.tex +++ b/task_lists/aux/aux.tex @@ -1,6 +1,6 @@ \section{Auxiliary Data}\label{sec:tasks:aux} {\justify -While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing and upcoming external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, x-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation for and during LSST operations it is therefore prudent to ensure appropriate access, usability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. +While LSST will produce outstanding quality optical imaging with temporal spacing, a significant amount of additional science will be enabled through the combination of these data with existing, future, and proposed external datasets; both spectroscopic ($i.e.$, redshift and/or spectral line measurements) and panchromatic ($i.e.$, x-ray, UV, IR, radio photometry). However, bringing together these external datasets into a useable, coherent, and quality controlled format is non-trivial and requires significant effort. In particular, the number, size and complexity of both {\it spectroscopic} and {\it panchromatic} datasets is likely to dramatically increase with the advent of a number of new ground and space based facilities. Both in preparation for and during LSST operations it is therefore prudent to ensure appropriate access, usability, and quality control of external datasets are in place via the establishment of an auxiliary LSST database. @@ -10,7 +10,8 @@ \subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} \begin{task} \label{task:aux:spectroscopy} \motivation{ -Although great strides have been made in projects using photometric redshifts alone, some science is only possible with either spectroscopic redshifts and/or spectroscopic line measurements. In particular, spectroscopic redshifts are essential when distance accuracies of less than 1000 km/s are required; for example in identifying galaxy pairs and groups. Robust measurement of gas and stellar phase metalicities also require relatively high-S/N spectra (3 to 20 respectively) at a spectral resolution of better than a few Angstroms. Finally, photometric redshifts still require spectroscopic redshifts for both calibration and accuracy assessment. As such, it is essential that we ensure the LSST community has access to the available high precision redshifts, spectroscopically-derived properties and calibrated spectra for all available galaxies and quasars within the LSST footprint. This necessarily entails bringing together data from disparate surveys (such as 2dFGRS, SDSS, 6dF, MGC, GAMA, VIPERS, VVDS), the homogenization of data products and quality control, as well as the ongoing ingestion of upcoming spectroscopic campaigns such as TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. This will require significant pre-LSST effort. +Although great strides have been made in projects using photometric redshifts alone, some science is only possible with either spectroscopic redshifts and/or spectroscopic line measurements. In particular, spectroscopic redshifts are essential when distance accuracies of less than 1000 km/s are required; for example in identifying galaxy pairs and groups. Robust measurement of gas and stellar phase metalicities also require spectra with relatively high signal-to-noise and resolution. +Finally, photometric redshifts still require spectroscopic redshifts for both calibration and accuracy assessment. As such, it is essential that we ensure the LSST community has access to the available high precision redshifts, spectroscopically-derived properties and calibrated spectra for all available galaxies and quasars within the LSST footprint. This necessarily entails bringing together data from disparate surveys (such as 2dFGRS, SDSS, 6dF, MGC, GAMA, VIPERS, VVDS), the homogenization of data products and quality control, as well as the ongoing ingestion of upcoming spectroscopic campaigns such as TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid etc. This will require significant pre-LSST effort. } ~\\ \activities{ @@ -21,12 +22,11 @@ \subsection{Extragalactic Optical/NIR Spectroscopy within the LSST Footprint} \item A process for establishing quality control and homogenization of datasets including assignment of revised quality flags. \item A pathway for ingesting future datasets as they become available and potentially in advance via MOU arrangements, e.g., TAIPAN, DEVILS, MOONS, 4MOST, DESI, PFS, Euclid, etc. \end{enumerate} -Approximately 6 million spectroscopic redshifts are known, with the majority of these already in the public domain; along with associated flux and wavelength calibrated spectra. In addition, derived parameters also exist for many of these spectra including, but not limited too, redshifts, equivalent widths, velocity dispersions, line asymmetries etc. Many of these measurements have been made using bespoke software specific to each originating survey (e.g., SDSS v 2dFGRS), creating an inhomogeneous network of data, measurements and quality control flags within the LSST footprint. +Approximately 6 million spectroscopic redshifts are known, with the majority of these already in the public domain, along with associated flux and wavelength calibrated spectra. In addition, derived parameters also exist for many of these spectra including, but not limited too, redshifts, equivalent widths, velocity dispersions, line asymmetries etc. Many of these measurements have been made using bespoke software specific to each originating survey (e.g., SDSS v 2dFGRS), creating an inhomogeneous network of data, measurements and quality control flags within the LSST footprint. In addition, in the next decade a number of new surveys will expand these measurements from millions to tens of millions of spectra through facilities and programs such as LAMOST, 4MOST, DESI as well as coarse spectroscopic information via GRISM data from Euclid and eventually WFIRST, leading to a wealth of spectroscopic data which will be invaluable to LSST. The community has two specific problems, i) collating this data and ii) ensuring quality control and standardization. Due to differing observing and analysis techniques not all spectroscopic measurements will be equal, and will depend on the resolution, signal-to-noise and precise software applied. Within reason some effort should be made to both collate and standardize the data with some provision of a uniform quality control process. At the bare minimum this should result in a database which contains the flux and wavelength calibrated spectra, links or copies of original derived products, and crucially, measurements using a uniform set of software analysis tools (e.g., to produce consistent redshift and equivalent width measurements) with some coherent cross-survey quality control flags. While this task sounds intimidating, this is exactly what has been achieved within the 200 square degrees of the Galaxy And Mass Assembly survey \citep{driver2011a,driver2016a,liske2015a} and an expansion of this process to the full LSST footprint is not unreasonable or impossible. However, this process needs to commence imminently if the database is to be in place for both LSST and the next generation of spectroscopic surveys. -As the majority of LSST's footprint covers the Southern Hemisphere, where many (but not all) large spectroscopic surveys have been instigated from Australia, this task represents a potential contribution from the Australian LSST contingent. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: @@ -48,7 +48,7 @@ \subsection{Panchromatic Imaging within the LSST Footprint} \motivation{ LSST will only cover a small portion of the electromagnetic spectrum emanating from stars and accretion disks around supermassive black holes. In understanding the galaxy life cycle we inevitably require observations of the full gas-stars-dust cycle along with additional processes from AGN and dust attenuation. As such, many LSST science goals will require access to the best available x-ray, UV, IR, and radio data. While archives of these data exist independently, there is a dire need to establish a Universe database which federates these data in a coherent manner. One of the major concerns of such a database is the accurate multi-wavelength source identification and de-convolution in disparate data with wildly differing resolutions. For example, two closely separated sources in the LSST data may appear as a single source in lower resolution data. As such, significant errors will be made when simply table matching these photometric catalogues. -The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFITs; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to x-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse x-ray halos, discrete x-ray sources and extended radio lobes). +The unavoidable solution to this problem is to bring the data into a single repository and allow sophisticated codes ($e.g.$, TFIT/TPHOT; LAMBDAR etc.) to determine appropriate flux measurements with associated errors based on apertures defined in high-resolution (LSST or other) bands. This will be particularly important as we extend to x-ray and radio wavelengths where the radiation fundamentally arises from spatial locations which are aligned with, but not identically co-incident to, the optical radiation ($e.g.$, diffuse HI envelopes, diffuse x-ray halos, discrete x-ray sources and extended radio lobes). } ~\\ \activities{ @@ -59,9 +59,10 @@ \subsection{Panchromatic Imaging within the LSST Footprint} \item Software to measure flux across panchromatic data taking into account original aperture definition, facility resolution, signal-to-noise limitations, and any physical priors. \item Tools to serve imaging and photometric data either for individual or sets of objects. \end{enumerate} +~\\~\\ As galaxies emit radiation across the entire electromagnetic spectrum it is important to be able to trace this breadth of emission deriving from different astrophysical processes. This is particularly important in the LSST optical wavebands where anywhere from 0-90 per cent of the radiation might be attenuated by dust and re-radiated in the far-IR. -The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman- and the 4000Ang-breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. -Finally, x-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star-formation. Unification across the wavelength range requires federation of these very disparate datasets. This will become an increasingly common problem as we move into the ear of Big Data, and hence is worth centralizing prior to LSST operations. +The robustness of photometric redshifts also relies on folding in non-optical (i.e, UV, near-IR and mid-IR) priors to minimize ambiguities between, for example, the Lyman- and 4000\AA~breaks. Moreover robust photometric redshifts also require consistent and accurate error estimates which cannot be guaranteed when using table matched data produced by different groups using different methodologies. +Finally, X-ray and radio facilities that have traditionally focused on the AGN population. However, other processes are now becoming increasingly relevant as they extend to deeper observations (such as those with SKA-precursors and eROSITA) and become sensitive to both extended emission and/or emission related to star-formation. Unification across the wavelength range requires federation of these very disparate datasets, and may be worth centralizing prior to LSST operations. Note a similar task has recently been achieved by the Galaxy And Mass Assembly team for a 200 square degree region \citep[see][and http://www/gama-survey.org/]{driver2016a} and can be extended to the full LSST footprint using similar techniques. } ~\\ @@ -75,7 +76,7 @@ \subsection{Panchromatic Imaging within the LSST Footprint} \item Optical from SkyMapper, DES, and Euclid. \item Near-IR from VISTA and Euclid. \item Mid-IR from WISE. -\item Far-IR from IRAS, Herschel, and Spica. +\item Far-IR from IRAS, Herschel, and potential missions like Spica. \item Radio continuum and HI from ASKAP (EMU,WALLABY,DINGO), MeerKAT (LADUMA, MIGHTEE, MeerKLASS), and eventually the SKA. \end{itemize} \item Derived panchromatic photometry (on the fly or pre-processed). @@ -91,8 +92,10 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} % How do galaxies evolve kinematically? The relation between stellar luminosity and rotation for disk galaxies is well known in the local Universe \citep[i.e., the Tully-Fisher or T-F relation, see][]{tully1977a,verheijen2001a} and suspected to evolve as gas and stars form a disk within the dark matter gravitational potential. H\,{\sc{i}} extends throughout the stellar disk and well beyond, its kinematics tracing the galaxy's dark matter potential. -How the T-F relation evolved with cosmic time and redshift is being debated; whether the normalization or the slope or both evolve \cite[][]{weiner2006a,tiley2016a}? -A few major drawback for these studies into the evolution of the T-F are +The potential evolution of the T-F relation, including possible evolution in the normalization, slope, or both, is an area of active research +\cite[][]{weiner2006a,tiley2016a}. +~\\~\\ +A few major drawbacks for these studies into the evolution of the T-F are (a) the kinematic information comes from H$\alpha$ optical data (sometimes redshifted into the infra-red, which does not trace the full rotation curve, (b) adaptive optics for these observations filters out the lower surface brightness features such as the rotating @@ -109,7 +112,7 @@ \subsection{Tully-Fisher Measurements Combining LSST and SKA Pathfinders} There are two main MeerKAT surveys that offer the opportunity for synergy with the LSST galaxy photometry: the MeerKAT International GigaHertz Tiered Extragalactic Exploration \citep[MIGHTEE,][]{jarvis2012a} project and the Looking At the Distant Universe with the MeerKAT Array \citep[LADUMA,][Blyth+ {\em in prep.}]{holwerda2010a,holwerda2011a}. Both target H\,{\sc{i}} observations in the LSST confirmed deep drilling fields and thus offer the opportunity to explore the Tully-Fisher relation out to redshift $z\sim1$ through direct detecton and possibly stacking. MIGHTEE and LADUMA represent the deepest two tiers of the H\,{\sc{i}} survey strategy for the combined pathfinder instruments.\\ ~\\ Two other surveys represent the progressively wider/shallower H\,{\sc{i}} survey tiers with the ASKAP telescope \citep{johnston2007a}: DINGO, a survey of the GAMA fields \citep[][Meyer+ {\em in prep}]{driver2009a,duffy2012a,meyer2015a} and WALLABY, the Southern Sky H\,{\sc{i}} survey \citep[][Koribalski+ {\em in prep}]{duffy2012a}. - A benefit of the MeerKAT and ASKAP radio surveys is that they are conducted commensally: radio continuum and 21 cm emission line (H\,{\sc{i}}) are observed at the same time. The combination + A benefit of the MeerKAT and ASKAP radio surveys is that they are conducted commensally: radio continuum and 21 cm emission line (H\,{\sc{i}}) are observed at the same time. The survey strategy from wide and shallow to single deep field (WALLABY-DINGO-MIGHTEE-LADUMA) is designed to beat down cosmic variance effectively \citep[see e.g.,][]{maddox2016a}. } ~\\ diff --git a/task_lists/clss/clss.tex b/task_lists/clss/clss.tex index 6506e26..11798b8 100644 --- a/task_lists/clss/clss.tex +++ b/task_lists/clss/clss.tex @@ -221,8 +221,8 @@ \subsection{Disentangling Complicated Lines-of-Sight} \begin{task} \label{task:clss:los} \motivation{ -Lines-of-sight through galaxy clusters and groups rank among the most -challenging lines-of-sight along which to measure reliable photometric +Lines-of-sight through galaxy clusters and groups rank among the +most challenging situations for measuring reliable photometric redshifts as crowding of galaxies complicates the basic process of galaxy photometry, and the presence of significant correlated LSS complicates interpretation of any galaxy redshift distribution diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index 430c8eb..d2c0763 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -46,8 +46,8 @@ \subsection{Coordinating Ancillary Observations} } \end{task} -\subsection{Observing Strategy Cadence} -\tasktitle{Observing Strategy Cadence} +\subsection{Observing Strategy and Cadence} +\tasktitle{Observing Strategy and Cadence} \begin{task} \label{task:ddf:cadence} \motivation{ diff --git a/task_lists/galaxies/galaxies.tex b/task_lists/galaxies/galaxies.tex index 2c7f198..7de51c5 100644 --- a/task_lists/galaxies/galaxies.tex +++ b/task_lists/galaxies/galaxies.tex @@ -154,7 +154,7 @@ \subsection{Techniques for Identifying and Deblending Overlapping Galaxies} and (b) model the effects of blending on the sample selection and derivation of redshift and other parameters. These issues critically affect not just galaxy evolution science, but also lensing and large-scale -structure studies. Another example involves the evolution +structure studies. Another example involves the measurement of galaxy morphologies, where the effects of blending and confusion may dominate measurement uncertainties.\\ ~\\ @@ -246,7 +246,7 @@ \subsection{Galaxy Structural Parameters} \motivation{ The image quality provided by the LSST camera (0.2"/pixel) and the wide field coverage (9.6deg$^2$) over 18,000 deg$^2$ in optical and NIR bands promise to provide unique data for studying the evolution of the internal galaxy structure. The full depth of the Wide Fast Deep survey (r $\sim$27.5 coadded) -will allow for the identification dwarf galaxies at $z\sim0.5$, and up to $M_*+2$ galaxies in clusters and field at $z\sim1.5$, and reach deep enough to study the structural parameters (size, Sersic index, ellipticity etc.) of $M_*$ galaxies at $z\sim1.2$ (for seeing$<0.5$"). The LSST data will allow for size, Sersic index, and bulge-to-disk ratio for over a billion galaxies to be correlatedd with mass, color, and other intrinsic properties at different epochs and thereby clarify the mechanisms that drive the galaxy assembly and transformation. +will allow for the identification dwarf galaxies at $z\sim0.5$, and up to $M_*+2$ galaxies in clusters and field at $z\sim1.5$, and reach deep enough to study the structural parameters (size, Sersic index, ellipticity etc.) of $M_*$ galaxies at $z\sim1.2$ (for seeing$<0.5$"). The LSST data will allow for size, Sersic index, and bulge-to-disk ratio for over a billion galaxies to be correlated with mass, color, and other intrinsic properties at different epochs and thereby clarify the mechanisms that drive the galaxy assembly and transformation. } ~\\ \activities{Preparatory work will consist of testing parametric methods for seeing-convolved 2D fitting of the galaxy light distribution on precursor surveys (e.g., HSC or KiDS) and on simulated LSST images, with the aim of providing viable tools for automatic image masking, catalogue extraction, source classification, and 2D galaxy fitting @@ -286,9 +286,9 @@ \subsection{Optimizing Galaxy Mass Profile Measurements} evolution. Such studies have been attempted before in a limited way using LSST precursor surveys. Using 300,000 lens galaxies in the Deep Lens Survey, \citep{choi2012a} studied the mass profile of galaxies in three luminosity bins out to several Mpc. Using -a similar number of lens galaxies in the COSMOS ACS data,\citep{leauthaud2012a} derived +a similar number of lens galaxies in the COSMOS ACS data, \citet{leauthaud2012a} derived constraints on the evolution of the stellar-to-dark matter connection in the context of halo models. -LSST will provide a billion lens galaxies and more accurate photometric redshifts, revolutionizing +LSST will provide a billion lens galaxies with accurate photometric redshifts, revolutionizing this measurement. } ~\\ diff --git a/task_lists/lsb/lsb.tex b/task_lists/lsb/lsb.tex index dc06906..abbcb94 100644 --- a/task_lists/lsb/lsb.tex +++ b/task_lists/lsb/lsb.tex @@ -42,16 +42,16 @@ \subsection{Low Surface Brightness Galaxies} \begin{task} \label{task:lsb:galaxies} \motivation{ -The objective of this task is to investigate objects that have surface brightnesses much less than the background night sky and are typical of the Milky Way galaxy within which we live. Many authors have previously shown how difficult it is to identify LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to our own spiral galaxy. Thus, the universe we perceive may have more to do with the position we are observing it from than its true nature - what would we see if we were able to move our telescopes away from the Sun and out to the very outer edges of the Galaxy?\\ +The objective of this task is to investigate objects that have surface brightnesses much less than the background night sky and are typical of the Milky Way galaxy within which we live. Many authors have previously shown how difficult it is to identify LSB galaxies and, more importantly, that our current observations may be severely biased towards detecting objects that have surface brightnesses very similar to our own spiral galaxy.\\ ~\\ -Additionally, the LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via neutral hydrogen surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies will still be quite easy to detect in LSST images.\\ +The LSB universe includes a large percentage of galaxies representing the low-mass end of the galaxy mass function, which in turn has been a major source of tension for the LCDM cosmological model \citep{kaviraj2017a}. The galaxy mass function at masses less than M$_h\sim 10^{10}$ M$_{\odot}$ systematically departs from the halo mass function in ways that are difficult to reconcile with current models of baryonic feedback. On the observational side, a crucial step towards understanding the discrepancy is to derive a much more complete census of low-mass galaxies in the local universe. For gas-poor galaxies, which includes most dwarfs within the halos of Milky-Way like galaxies, detection via neutral hydrogen surveys or emission-line surveys is nearly impossible. Dwarf galaxies in the Local Group can be found by searching for overdensities of individual stars. At much larger distances, this becomes impossible. However, these galaxies will still be quite easy to detect in LSST images.\\ ~\\ At the other extreme of LSB galaxies, the largest spiral galaxy known since 1987 (called Malin 1), has an extremely LSB disk of stars and an impressive system of spiral arms. The central bulge of the galaxy is prominent, but the stellar disk and spiral arms only revealed itself after sophisticated image processing. Malin 1 was discovered by accident and has for almost thirty years been unique. How many more galaxies with rather prominent central bulges also have extended LSB disks? This issue is very important for understanding the angular momentum distribution of galaxies and where this angular momentum comes from - for its stellar mass Malin 1 has about a factor ten higher angular momentum than typical values. The limiting surface brightness limit of the LSST combined with the large field-of-view make this facility unique for probing the existence of large LSBs similar to Malin 1. There is also an existing problem relating galaxies formed in numerical simulations to those observed. Models with gas, cooling and star formation lose gas and angular momentum making disc galaxies too small. This has already been termed the angular momentum catastrophe and galaxies with giant disks like Malin 1 only make this problem worse. This issue is particularly important as there is increasing evidence that angular momentum plays a large part in determining the morphology of galaxies, a problem that has plagued galaxy formation studies since its inception.\\ ~\\ To quantify the astronomical problem we can give some approximate numbers. The typical sky background at a good dark astronomical site is $\approx22.5~\mathrm{mag}~\mathrm{arcsec}^{-2}$ and that from a space telescope typically an order of magnitude fainter $\approx25.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$. The mean surface brightness (averaged over the half-light radius) of a galaxy like the Milky Way is $\approx23.0~\mathrm{mag}~\mathrm{arcsec}^{-2}$, of order the brightness of the darkest sky background seen from the ground. The mean surface brightness of the giant LSB galaxy Malin 1 is about $\approx28~\mathrm{mag}~\mathrm{arcsec}^{-2}$, some 100 times fainter than that of the Milky Way and that of the sky background. Extreme dwarf galaxies in the Local Group have mean surface brightnesses as faint as $\approx32~\mathrm{mag}~\mathrm{arcsec}^{-2}$, $10^4$ times fainter than the background, but these have only been found because they are resolvable into luminous stars - something that is not currently possible to do from the ground for distances beyond about 5 Mpc. Note that $26~\mathrm{mag}~\mathrm{arcsec}^{-2}$ corresponds to approximately a surface density of about one solar luminosity per sq parsec. Our intention is to explore the universe using LSST to at least a surface brightness level of $30~\mathrm{mag}~\mathrm{arcsec}^{-2}$. } ~\\ -\activities{The key activities for this task include the production of simulated data e.g. from new hydrodynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. Once produce, analysis of simulated images is needed to ensure that LSB galaxies can be accurately detected. This analysis will require the development of new object detection software specifically designed for the detection of LSB galaxies, in particular objects with large size, near or melted with brighter galaxies, and highly irregular and distorted objects. Precursor data sets that can be used to test our methods +\activities{The key activities for this task include the production of simulated data e.g. from new hydrodynamical simulations in cosmological volumes (such as Horizon-AGN, EAGLE, Illustris etc.) that can be passed through the LSST data reduction pipeline. Once produced, analysis of simulated images is needed to ensure that LSB galaxies can be accurately detected. This analysis will require the development of new object detection software specifically designed for the detection of LSB galaxies, in particular objects with large size, near or melted with brighter galaxies, and highly irregular and distorted objects. Precursor data sets that can be used to test our methods will need to be identified. Data generated using numerical simulations can be used to examine the types of galaxies produced that have sufficient angular momentum to become LSB disks. These disks can be quantified and placed within simulated data to test the ability of the pipeline to preserve LSB features. New methods of detecting LSB objects will be engineered, including pixel clustering methods and the labeling of pixels with certain properties, i.e., surface brightness level, SED shape, and proximity to other similar pixels. We will train our methods on other currently available data sets (KIDS, CFHT etc). These analyses will further require the production of realistic simulated LSST images of nearby dwarf galaxies (from high resolution hydrodynamical simulations like New Horizon which has resolutions of tens of parsecs), the @@ -115,7 +115,8 @@ \subsection{Sky Estimation} \activities{ The research program starts with the current best methods, improving sky estimates on all angular scales via new algorithms, and then validation via simulations. The sky model in principle can be built using knowledge of the LSST system, locations of bright objects, the observational data, and statistical summaries of faint galaxy counts from HST. The first step is to detect all objects above a position-variable local sky estimate, masking them, and then growing the masks. The remaining pixels contain undetected galaxies, giving an over-estimate of the sky level around compact objects if left uncorrected. Statistical faint galaxy counts can help in making these corrections. When corrected, the Poisson noise from the remaining sky may be fit with a Gaussian. Even then, 3-$\sigma$ clipping and/or one-sided fitting may be required. This entire process is recursive on every angular scale where there are important sky components. ~\\~\\ -LSST data management are planning novel algorithms of this general sort, and close coordination will be necessary and beneficial. The Dark Energy Science Collaboration (DESC) Science Roadmap\footnote{The DESC Science Roadmap is available at: \url{http://lsst-desc.org/sites/default/files/DESC_SRM_V1_0.pdf}} includes plans for realistic image-based simulations of the LSST sky. In coordination with DESC, the inclusion of faint, large-scale LSB objects in future Data Challenge catalogs and images would benefit all groups involved in testing algorithms and characterizing LSB objects. Improvements we make may be ingested by LSST DM as a Level-3 contribution. LSB ghosts due to reflected bright star light in the camera should also be included. +LSST data management are planning novel algorithms of this general sort, and close coordination will be necessary and beneficial. The Dark Energy Science Collaboration (DESC) Science Roadmap \citep{LSSTDESC} +includes plans for realistic image-based simulations of the LSST sky. In coordination with DESC, the inclusion of faint, large-scale LSB objects in future Data Challenge catalogs and images would benefit all groups involved in testing algorithms and characterizing LSB objects. Improvements we make may be ingested by LSST DM as a Level-3 contribution. LSB ghosts due to reflected bright star light in the camera should also be included. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index 476b49e..ec9f4f4 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -20,7 +20,8 @@ \subsection{Impact of Filter Variations on Galaxy Photometric Redshift Precision Tests of the amplitude of these residuals and their impact on photo-$z$'s, especially for particular object classes of interest, will be important for determining to what degree DM data products can be used directly for galaxies work. If the variations can be calibrated well, they could potentially be used to further improve, rather than degrade, photo-$z$ performance. The variations in filter response can offer up a small amount of extra information on the object SED given the slight variation in effective filter wavelength, particularly for objects with strong narrow features (i.e., emission lines). -Tests of how much information is gained can inform whether or not the extra computational effort required for computing photo-$z$'s that incorporate the effective passband from every individual LSST observation of an object will be superior to estimates incorporating DM measurements corrected to the six fiducial filters of the survey. All topics discussed above are also being examined by the LSST Dark Energy Science Collaboration Photometric Calibration working group, and there are several related tasks described in the DESC Science Roadmap document\footnote{The DESC Science Roadmap is available at: \url{http://lsst-desc.org/sites/default/files/DESC_SRM_V1_0.pdf}}. Communication and coordination with the Photometric Calibration group will be very important to maximize the impact of work on these areas of shared interest. +Tests of how much information is gained can inform whether or not the extra computational effort required for computing photo-$z$'s that incorporate the effective passband from every individual LSST observation of an object will be superior to estimates incorporating DM measurements corrected to the six fiducial filters of the survey. All topics discussed above are also being examined by the LSST Dark Energy Science Collaboration Photometric Calibration working group, and there are several related tasks described in the DESC Science Roadmap document \citep{LSSTDESC}. +Communication and coordination with the Photometric Calibration group will be very important to maximize the impact of work on these areas of shared interest. } ~\\ \activities{ @@ -40,8 +41,8 @@ \subsection{Photometric Redshifts in the LSST Deep Drilling Fields} \begin{task} \label{task:photo_z:ddf} \motivation{ -The LSST Deep Drilling Fields present different challenges than the main survey, including increasing rates of confusion between sources, but they also provide the ability to use subsets of the data to construct higher resolution images due to the large number of repeat observations. These properties allow investigations of galaxies of brightness which are close to the noise floor in the main survey. Having an accurate error model is essential for optimal photo-z performance; the larger number of repeat observations in the Deep Drilling Fields enables empirical checks on the magnitude and flux uncertainties generated by the LSST pipeline, through both higher signal-to-noise stacks and using subsets of the data to model the uncertainties. As LSST imaging data will not be available for several more years, such studies of subset stacks to examine seeing and error properties would have to use pre-existing data sets, e.~g.~HyperSuprimeCam data, when testing such algorithms and putting needed infrastructure in place so that it can be used once LSST data is flowing.\\~\\ -In addition to providing useful information about main-survey photometric redshift quality, the Deep Drilling Fields will pose particular challenges for photometric redshift determination, as spectroscopy for complete samples down to the DDF depth for photo-$z$ training and calibration will be completely infeasible, and the DDF area is likely too small for high-precision calibration by cross-correlation techniques. +The LSST Deep Drilling Fields present different challenges than the main survey, including increasing rates of confusion between sources, but they also provide the ability to use subsets of the data to construct higher resolution images due to the large number of repeat observations. These properties allow investigations of galaxies of brightness which are close to the noise floor in the main survey. Having an accurate error model is essential for optimal photo-z performance; the larger number of repeat observations in the Deep Drilling Fields enables empirical checks on the magnitude and flux uncertainties generated by the LSST pipeline, through both higher signal-to-noise stacks and using subsets of the data to model the uncertainties. As LSST imaging data will not be available for several more years, such studies of subset stacks to examine seeing and error properties would have to use pre-existing data sets, e.~g.~HyperSuprimeCam data, when testing such algorithms and putting needed infrastructure in place so that it can be used once LSST data are flowing.\\~\\ +In addition to providing useful information about main-survey photometric redshift quality, the Deep Drilling Fields will pose particular challenges for photometric redshift determination, as spectroscopy for complete samples down to the DDF depth for photo-$z$ training and calibration will be completely infeasible, and the DDF area may limit high-precision calibration by cross-correlation techniques. } ~\\ \activities{ @@ -68,7 +69,8 @@ \subsection{Multivariate Physical Properties of Galaxies from Photometric Redshi Many recent science analyses have relied upon derived physical properties rather than fluxes and luminosities in the UV, optical and near-IR bands. This is largely a matter of convenience: utilizing tables of derived properties require no redshift (K) corrections or extra dust corrected, as those are effectively applied in the measurement process; they are also closer to the quantities best determined in simulations. However, derived quantities have the disadvantage of the potential for significant systematic errors in measurement, as well as non-uniformity in their definition (e.g., differences in adopted IMF can change stellar masses by $\sim 0.5$ dex). \\~\\ Stellar mass has emerged as a parameter of choice for selecting galaxy samples and attempting to make apples-to-apples comparisons of galaxies at different redshifts. The sSFR (current SFR normalized by stellar mass) provides a measure of a galaxy’s star formation history. Dust attenuation and stellar metallicity can help to probe processes important for understanding galaxy evolution.\\ ~\\ -This Task shares some goals with the Dark Energy Science Collaboration Photometric Redshifts working group, as laid out in their Science Roadmap (see ~\ref{pzfiltervar} footnote for document link), who are also interested in multidimensional probability density functions joint in redshift and stellar mass, star formation rate, and dust content of the galaxies. Coordination on this area with the DESC Photo-z working group will benefit both groups. +This task shares some goals with the Dark Energy Science Collaboration Photometric Redshifts working group, as laid out in their Science Roadmap \citep{LSSTDESC}, +who are also interested in multidimensional probability density functions joint in redshift and stellar mass, star formation rate, and dust content of the galaxies. Coordination on this area with the DESC Photo-z working group will benefit both groups. } ~\\ \activities{ @@ -95,7 +97,7 @@ \subsection{Identifying Spectroscopic Redshift Training Sets for LSST} Accurate photometric redshift estimates require deep spectroscopic redshift data in order to help train algorithms, either directly in the case of machine learning based algorithms, or to train Bayesian priors and adjust zero points, transmission curves, or error models for template-based methods. Representative spectroscopic samples can be used to investigate the accuracy of photo-$z$ algorithms. Obtaining representative training sets is a problem across multiple science tasks, and in fact, across many current and upcoming large surveys. As the telescope resources necessary will be quite extensive, coordination with the other large surveys is essential. A detailed study of spectroscopic training needs and potential spectroscopic instruments that will be available in the coming years was undertaken by \citet[]{newman2015a}. We must now begin our attempts to obtain the necessary samples. We must also identify any needs that are unique to galaxy science that may not be prioritized in the cosmology-focused efforts to date, e.~g.~are faint galaxy populations sampled adequately in the planned spectroscopic samples? } ~\\ -\activities{In coordination with other large surveys, collate existing spectroscopic redshift data over both DDF and wider fields, and assess the biases due to selection and redshift incompleteness for each spectroscopic data set. Assess the robustness of existing data, and determine color spaces where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. This work should become much more efficient once PFS and MOONS become available. +\activities{In coordination with other large surveys and other LSST science collaborations, collate existing spectroscopic redshift data over both DDF and wider fields, and assess the biases due to selection and redshift incompleteness for each spectroscopic data set. Assess the robustness of existing data, and determine color spaces where existing surveys lack statistics. Apply for additional spectroscopy to fill in parameter space not already covered by existing surveys. This work should become much more efficient once PFS and MOONS become available. } ~\\ \deliverables{%Deliverables over the next several years from the activities described above include the following: From c335fbd44b1e212073e479c49c8c272d969e82e1 Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 1 Aug 2017 23:33:01 -0700 Subject: [PATCH 49/64] Cross-links added. Closes #11 --- introduction/introduction.tex | 2 ++ task_lists/ddf/ddf.tex | 3 ++- task_lists/photo_z/photo_z.tex | 3 ++- 3 files changed, 6 insertions(+), 2 deletions(-) diff --git a/introduction/introduction.tex b/introduction/introduction.tex index fd96e3d..cf79356 100644 --- a/introduction/introduction.tex +++ b/introduction/introduction.tex @@ -66,6 +66,8 @@ which provides more details for many of the science investigations. Chapter \ref{ch:task_lists} presents preparatory science tasks for extragalactic science with LSST, organized by science topic. +Cross-references between complementary tasks in different science topics are +noted throughout the document. The science task list content assumes that the work plan of the DESC will be executed and that the resulting software and other data products resulting from the DESC efforts will be made available to the other science collaborations. diff --git a/task_lists/ddf/ddf.tex b/task_lists/ddf/ddf.tex index d2c0763..19232ec 100644 --- a/task_lists/ddf/ddf.tex +++ b/task_lists/ddf/ddf.tex @@ -2,10 +2,11 @@ \section{Deep Drilling Fields}\label{sec:tasks:ddf} {\justify The LSST Deep Drilling Fields (DDF) will have a higher cadence and deeper observations than the Wide-Fast-Deep (WFD) survey. -Many of the details of the observing strategy have yet to be finalized, but four Deep-Drilling fields have been selected. +Many of the details of the observing strategy have yet to be finalized, but four DDFs have been selected. Whether to include any others will be part of a complex trade involving other special projects that depart from the WFD survey strategy. The details of the observing cadence, final depth in each band, and dithering strategy all remain under study at the current time. The tasks outlined in this section will help optimize the LSST DDF observing strategy, gather supporting data, and ensure that the data processing and measurements meet the needs for galaxy evolution science. +The specific task of calculating photometric redshifts in the LSST DDFs is addressed separately in Section \ref{task:photo_z:ddf}. \begin{tasklist}{DDF} diff --git a/task_lists/photo_z/photo_z.tex b/task_lists/photo_z/photo_z.tex index ec9f4f4..fd98e3c 100644 --- a/task_lists/photo_z/photo_z.tex +++ b/task_lists/photo_z/photo_z.tex @@ -6,6 +6,7 @@ \section{Photometric Redshifts}\label{sec:tasks:photo_z} stellar population synthesis models. A major effort within the LSST Dark Energy Science Collaboration (DESC) is focused on the development of photometric redshift algorithms for LSST, including the incorporation of joint probability distributions between redshift and astrophysical parameters of interest for the study of galaxy evolution. Efforts within the Galaxies collaboration should be able to leverage work happening in DESC and build upon it to ensure that photometric redshifts optimized for galaxy science are available. +The related question of determining photometric redshifts for Active Galactic Nuclei is discussed in Section \ref{task:agn:photoz}. \begin{tasklist}{PZ} \subsection{Impact of Filter Variations on Galaxy Photometric Redshift Precision} @@ -120,7 +121,7 @@ \subsection{Simulations with Realistic Galaxy Colors and Physical Properties} } ~\\ \activities{ -The main activity for this task is to develop improved simulation metrics based upon observational studies of both low- and high-redshift galaxies. This will require expertise from the photo-$z$ high-redshift galaxies, AGN, and simulations working groups. In order to test whether mock galaxy populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions.\\ +The main activity for this task is to develop improved simulation metrics based upon observational studies of both low- and high-redshift galaxies. This will require expertise from the photo-$z$, high-redshift galaxies, AGN, and simulations working groups. In order to test whether mock galaxy populations agree with the real Universe, we must have some real data to compare against, even if it is a luminous subsample or only complete in certain redshift intervals. Once such comparison datasets are established, metrics can be developed to determine which simulations and simulation parameters most accurately reproduce the observed galaxy distributions.\\ ~\\ If we then assume that the simulations are valid beyond the test intervals, we can use them as a testbed to develop improved algorithms for a wide variety of applications, e.~g.~selecting specific sub-populations of galaxies. One key aspect of this work is that spectral energy distributions in simulations cannot be generated from discrete templates, but instead must span a continuous range of properties. If only a finite set of restframe SEDs are used in the simulation, the photo-$z$ problem would be unnaturally simplified and falsely strong photometric redshift predictions would result. Thus a method is required that simultaneously reproduces galaxy colors without resorting to a restricted set of SEDs. For example, this could be done by creating complete SEDs based on an extended set of principal components (e.g., extending the $kcorrect$ or EAZY basis set), though in general additional constraints are required with PCA-like techniques to ensure that unphysical spectra are not generated.\\ From 9bfed8b1b8b55d8e9cfcc03729d70292f371d26f Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Wed, 2 Aug 2017 11:00:00 -0700 Subject: [PATCH 50/64] Updating LSB sky estimation section. 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znE?byfRM_ar9I?Q%^IP)GzI@1h;Jk2?tnUGnbGYcQS+_o!fJ(q1Uc_DwAe*vsavXx zW|^a-O0%WLT=OqUj(jzL+-O4WyYzBK+vJsjaj_`+g zllTysPl)a;pk|w!&cTbaIz$ICI$c;3%p;@bm6gBD?n+M7tSuYsObPA)<9gLOgyNMvmdp zD>hfJ3gB6ALLtCi;tCe{P_WMbBa=oDUB+4l0FnwsFj4YDqLWzjB|xqhAnf;~ql%sI zDAggc{WirRr|ZvSYLR^z<;5?KW0-#84Q8+o7TkE}>4P z2443m++5IR#{Or4ka!BWQC$8+U4xbv54MOtAy*2Gw@cV>FKV1ErBArvW5W3x&cGIZXQG0Js;H2371Fn6-kZ-ic>%+UR zc6ft+tmooKz8ZNqgQkSS-^IJ$I9ymx#v09eX$Yb9(j#{7_Zn-z@l_1+3l)2$uNY(d zyG2Ky!;e`9jms!?kGh3?alNR_h5Xo`03WrzlUWBoAY}=(sj;c4iKx0d!O2GS-@M_s A^8f$< diff --git a/exgal_roadmap.tex b/exgal_roadmap.tex index 185a851..48f2ee8 100644 --- a/exgal_roadmap.tex +++ b/exgal_roadmap.tex @@ -64,6 +64,11 @@ \\ \noindent +The LSST Extragalactic Roadmap represents the collective efforts of more than one hundred scientists to define the critical research activities to prepare our field to maximize +the science return of the LSST dataset. We want to thank the LSST Corporation for their +support in developing this Roadmap and for supporting LSST-related science more broadly. +We also wish to thank the LSST Galaxies Science Collaboration members for their efforts +over the years in developing the case for extragalactic science with LSST.\\\\ Inquiries about this report or its content can be addressed to Brant Robertson ({\tt brant@ucsc.edu}). %\newpage diff --git a/science_background/black_holes/black_holes.tex~ b/science_background/black_holes/black_holes.tex~ deleted file mode 100644 index dac874e..0000000 --- a/science_background/black_holes/black_holes.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: black_holes -% First draft by - -\section{XXX}\label{sec:sciback:agn:XXX} - diff --git a/science_background/informatics/informatics.tex~ b/science_background/informatics/informatics.tex~ deleted file mode 100644 index 211febe..0000000 --- a/science_background/informatics/informatics.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: informatics -% First draft by - -\section{XXX}\label{sec:sciback:ai:XXX} - diff --git a/science_background/lss/lss.tex~ b/science_background/lss/lss.tex~ deleted file mode 100644 index 98d1def..0000000 --- a/science_background/lss/lss.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: lss -% First draft by - -\section{XXX}\label{sec:sciback:lss:XXX} - diff --git a/science_background/black_holes/black_holes.tex b/science_background/old/black_holes/black_holes.tex similarity index 100% rename from science_background/black_holes/black_holes.tex rename to science_background/old/black_holes/black_holes.tex diff --git a/science_background/informatics/informatics.tex b/science_background/old/informatics/informatics.tex similarity index 100% rename from science_background/informatics/informatics.tex rename to science_background/old/informatics/informatics.tex diff --git a/science_background/lss/lss.tex b/science_background/old/lss/lss.tex similarity index 100% rename from science_background/lss/lss.tex rename to science_background/old/lss/lss.tex diff --git a/science_background/strong_lensing/strong_lensing.tex b/science_background/old/strong_lensing/strong_lensing.tex similarity index 100% rename from science_background/strong_lensing/strong_lensing.tex rename to science_background/old/strong_lensing/strong_lensing.tex diff --git a/science_background/weak_lensing/weak_lensing.tex b/science_background/old/weak_lensing/weak_lensing.tex similarity index 100% rename from science_background/weak_lensing/weak_lensing.tex rename to science_background/old/weak_lensing/weak_lensing.tex diff --git a/science_background/science_background.tex b/science_background/science_background.tex index c536354..87d8304 100644 --- a/science_background/science_background.tex +++ b/science_background/science_background.tex @@ -11,15 +11,11 @@ \input{science_background/chapterintro.tex} -\input{science_background/black_holes/black_holes.tex} - \input{science_background/galaxies/galaxies.tex} -\input{science_background/informatics/informatics.tex} - -\input{science_background/lss/lss.tex} - -\input{science_background/strong_lensing/strong_lensing.tex} - -\input{science_background/weak_lensing/weak_lensing.tex} +%\input{science_background/black_holes/black_holes.tex} +%\input{science_background/informatics/informatics.tex} +%\input{science_background/lss/lss.tex} +%\input{science_background/strong_lensing/strong_lensing.tex} +%\input{science_background/weak_lensing/weak_lensing.tex} diff --git a/science_background/strong_lensing/strong_lensing.tex~ b/science_background/strong_lensing/strong_lensing.tex~ deleted file mode 100644 index d817d4e..0000000 --- a/science_background/strong_lensing/strong_lensing.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: strong_lensing -% First draft by - -\section{XXX}\label{sec:sci:sl:XXX} - diff --git a/science_background/weak_lensing/weak_lensing.tex~ b/science_background/weak_lensing/weak_lensing.tex~ deleted file mode 100644 index d28e2a5..0000000 --- a/science_background/weak_lensing/weak_lensing.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: science_background -% Section: weak_lensing -% First draft by - -\section{XXX}\label{sec:wl:XXX} - diff --git a/task_lists/black_holes/black_holes.tex~ b/task_lists/black_holes/black_holes.tex~ deleted file mode 100644 index c1c96e7..0000000 --- a/task_lists/black_holes/black_holes.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: task_lists -% Section: black_holes -% First draft by - -\section{XXX}\label{sec:tasks:agn:XXX} - diff --git a/task_lists/informatics/informatics.tex~ b/task_lists/informatics/informatics.tex~ deleted file mode 100644 index 79ae1d9..0000000 --- a/task_lists/informatics/informatics.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: task_lists -% Section: informatics -% First draft by - -\section{XXX}\label{sec:ai:XXX} - diff --git a/task_lists/lss/lss.tex~ b/task_lists/lss/lss.tex~ deleted file mode 100644 index f53456d..0000000 --- a/task_lists/lss/lss.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: task_lists -% Section: lss -% First draft by - -\section{XXX}\label{sec:lss:XXX} - diff --git a/task_lists/black_holes/black_holes.tex b/task_lists/old/black_holes/black_holes.tex similarity index 100% rename from task_lists/black_holes/black_holes.tex rename to task_lists/old/black_holes/black_holes.tex diff --git a/task_lists/informatics/informatics.tex b/task_lists/old/informatics/informatics.tex similarity index 100% rename from task_lists/informatics/informatics.tex rename to task_lists/old/informatics/informatics.tex diff --git a/task_lists/lss/lss.tex b/task_lists/old/lss/lss.tex similarity index 100% rename from task_lists/lss/lss.tex rename to task_lists/old/lss/lss.tex diff --git a/task_lists/strong_lensing/strong_lensing.tex b/task_lists/old/strong_lensing/strong_lensing.tex similarity index 100% rename from task_lists/strong_lensing/strong_lensing.tex rename to task_lists/old/strong_lensing/strong_lensing.tex diff --git a/task_lists/weak_lensing/weak_lensing.tex b/task_lists/old/weak_lensing/weak_lensing.tex similarity index 100% rename from task_lists/weak_lensing/weak_lensing.tex rename to task_lists/old/weak_lensing/weak_lensing.tex diff --git a/task_lists/strong_lensing/strong_lensing.tex~ b/task_lists/strong_lensing/strong_lensing.tex~ deleted file mode 100644 index 89abfa4..0000000 --- a/task_lists/strong_lensing/strong_lensing.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: task_lists -% Section: strong_lensing -% First draft by - -\section{XXX}\label{sec:sl:XXX} - diff --git a/task_lists/task_lists.tex b/task_lists/task_lists.tex index 5c3e1f3..f71f35d 100644 --- a/task_lists/task_lists.tex +++ b/task_lists/task_lists.tex @@ -14,7 +14,7 @@ %\input{task_lists/weak_lensing/weak_lensing.tex} \input{task_lists/agn/agn.tex} +\input{task_lists/galaxies/galaxies.tex} \input{task_lists/high_z/high_z.tex} \input{task_lists/lsb/lsb.tex} \input{task_lists/photo_z/photo_z.tex} -%\input{task_lists/galaxies/galaxies.tex} diff --git a/task_lists/weak_lensing/weak_lensing.tex~ b/task_lists/weak_lensing/weak_lensing.tex~ deleted file mode 100644 index dbb7ab8..0000000 --- a/task_lists/weak_lensing/weak_lensing.tex~ +++ /dev/null @@ -1,8 +0,0 @@ - -% LSST Extragalactic Roadmap -% Chapter: task_lists -% Section: weak_lensing -% First draft by - -\section{XXX}\label{sec:wl:XXX} - From 5daff1d81c7b07bf087d09070e07f2cc7f4465ab Mon Sep 17 00:00:00 2001 From: Brant Robertson Date: Tue, 20 Dec 2016 22:26:12 -0800 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zIyYMX*X15MFZNy_MtvJN1sI+SzTH}!RGei6=MhN6aeKagynfunNt|jWHg?Uv%dyMR zY%G2j&MArvTsORwEmv+Zbf znm=n!Br474wOOhDYE(W+Z2GIM#CiS?q`oqC<9b1l>TlEL(v{?q>Zg8y6pGrr Date: Tue, 20 Dec 2016 22:29:12 -0800 Subject: [PATCH 09/64] Updated GitHub readme. --- README.md | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 0a6f8a6..f41dac7 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,8 @@ # LSST Extragalactic Science Roadmap -Planning the investigation of dark matter, galaxies, and black holes with LSST. - -The Galaxies, AGN, Supernovae, Weak Lensing and Strong Lensing Science Collaborations are writing a white paper outlining the key extragalactic astronomy analyses that we anticipate carrying out in the 2020s, and working through what needs to be done between now and then to prepare for it. +The Galaxies Science Collaboration has been organizing the development of a whitepaper to identify critical science tasks in preparation for LSST. This document provides some science background in the general area of extragalactic astrophysics with LSST and provides lists of the important preparatory research tasks. ### Contact +* Brant Robertson (UCSC) * Harry Ferguson (STScI) - -### Accreditation - -This is work in progress; all content is Copyright 2014 by the authors. If you would like to cite the Extragalactic Science Roadmap in your work, please use "(LSST Science Collaborations, in prep.)". 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