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92 changes: 92 additions & 0 deletions Week_1/Log/Day 1.md
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#ICTS #may2024
6 - 5 - 2024

This is my first day at ICTS in bangalore
Job shadow program

**10:15**
Reached and had breakfast

**10:30 to 11:30**
Downloaded & setup vsc and tested anaconda and linux vm (wget <link>)

**11:30 to 1**
attending a lecture on bayesian procedure
(notes in notebook)

SpEC
Spectral Einstein code
https://www.black-holes.org/code/SpEC.html

**1:15 to 2** - Lunch

**2 to 2:30**
working on assignment given by vaishak
learn arrays in python
![[WhatsApp Image 2024-05-06 at 16.04.03_5faf9ce0.jpg]]

plot a graph
![[Pasted image 20240506150028.png]]


**2:30 to 4**
Lecture on Linear Algebra 1

Linear vector space
- closure under addition, associativity of addition
- associativity of scalar multiplicatiojn
- distributivity

R is a real vector space of real scalars
R^n is real vector space of n vector

Properties of <. , .>
1) <x, y> > 0 Vx not equal to 0 = positive definite
2) <x, y> = <y, x> - symmetry
Operation on vectors in R^n

Vector can be measured in different scales
1) Euclidean / 2 - norm
2) Manhattan / 1 - norm
3) Chebyshev / infinity norm
4) Minkowski / p - norm
5) Energy Norm

![[Pasted image 20240506150418.png]]

Unit sphere: locus of points at unit distance from origin

Functionals
Let V be a vector space
Any function that maps V into R: f: V -> R is called a functional
f is called linear functional if
f(x1 + x2) = f(x1) + f(x2) -> additive
f(ax) = af(x) = homogenous

Example
1) ||x|| is a nonlinear functional

Cauchy Schwarz inequality (CS)

Span of a set of vectors
orthogonal vectors
linearly independent vectors in 2 dimensions - infinite number possible

**4:00**
more messing around with numpy

make the y scale logarithmic

Damped sinusoid equations
![[Pasted image 20240507190413.png]]
Made a jupyter notebook which contains all python activities from day 1


**Reflection**

- ICTS is a nice and open place, I could go around and be wherever I wanted, which was good. Gave me a sense of freedom I guess
- I am thinking that the outcomes of this job shadow program could be
- writeup on what other researchers do in the astrophysics and relativity group
- github repository with the python notebooks of each day's python work


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#ICTS #may2024
8 - 5 - 2024

**10:30 to 11:15**

In the bus learned about normal distributions and probability contours. Probability contours are ellipses that show the distribution of a two-dimensional probability density function.

A chi-squared test, or Khi2 test, is a statistical hypothesis test that compares the observed distribution of data to an expected distribution.

**11:30**
Supercomputer at ICTS

"sonic"
https://it.icts.res.in/
14 nodes
HPC - high performance computing
has to communicate data through the nodes
HTC - high throughput computing
does not need to communicate data through different nodes

AMD Epyc 7413
2 socket per node
24 cores per socket = 48 cores per node, 96 threads in total
256 gb ram on signing nodes
384 gb on the computing nodes
running centos

Recently acquired 2x
Nvidia A40 gpu with 48gb vram

data analysis
uses gpu and the HTCs


**12:00 to 1:00**

Group meeting/discussion on interesting paper found on Arxiv
[Members of Astrophysics Relativity Group at ICTS](https://www.icts.res.in/research/astrorel/members)

- [Alorika Kar] talked about "Quick recipes for gravitational-wave selection effects
- https://arxiv.org/abs/2404.16930
- https://arxiv.org/pdf/2404.16930

- [Ankur Barsode] talked about "Lens Stochastic Diffraction: A signature of compact structures in gravitational wave data"
- https://arxiv.org/pdf/2404.17405
- if you have single lens - 2 images
- you can have multiple lenses but the fainter images are all going to overlap on each other and you are going to get a stochastic signal and it will come from the same location as the main image.
- multiple images from multiple lenses all overlapping with each other
- Questions
- How many lenses
- probably 10 - 15 is what he is using
- There should be a threshold
- didnt go that much into the details
- why is it important
- you can use non detection to constrain blackholes??
- [Prasad R] talked about "Dynamical ejecta from binary neutron star mergers: Impact of residual eccentricity and equation of state implementation"
- https://arxiv.org/pdf/2404.18674
- ejected mass is whatever is remaining after neutron stars merge
- ejecta is ejected more if neutron star is spinning more
- Concerned about
- accuracy of simulation
- internal reactions
- keeping everything fixed and see how it reacts
- [Prasad R] also talked about "Black hole-neutron star mergers with massive neutron stars in numerical relativity"
- https://arxiv.org/pdf/2404.18714
- [Krishnendu N V] talked about "Numerical parameterization of stationary axisymmetric black holes in a theory agnostic framework"
- https://arxiv.org/pdf/2404.17055
- [Vaishak P] "NOTES ON THE PRACTICAL APPLICATION OF NESTED SAMPLING: MULTINEST, (NON)CONVERGENCE, AND RECTIFICATION"
- https://arxiv.org/pdf/2404.16928
- [Koustav Narayan Maity] "Neutron stars and the cosmological constant problem"
- https://arxiv.org/pdf/2404.19012

Mainly the PHD fellows were the ones discussing and asking questions and answering each other's doubts on each of the research papers.

After lunch, **2:00**

worked on python notebook, extracting original parameters from noise of a damped sinusoid wave.

refer "Day 2_assgt.ipynb for more info"

**EOS**
- should consider installing and learning docker, so i can use vsc and develop inside a linux environment
- vaishak likes using powerful computer resources to find solutions to problems that need answering, not like google and microsoft who use supercomputers to give users better ads
-
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#ICTS #may2024
9 - 5 - 2024

mainly python stuff
dynesty

Enter some stuff about LIGO detectors



physics of it
gravitational waves
LIGO detectors
they are what observe the time series data
binary black hole mergers
waveform generation
numerical relativity**

computational challenges in brief and then exapnd on it in more detail

data analysis and parameter
minimization - maximum likelihood estimation - chisquared
bayesian inference
gravitational wave data analysis
matched filter (understanding of it)

Research ICTS
operational structure
usual week
group activities
computational resources
people in ASTROPHYSICAL RELATIVITY group



Covariance matrix
Read up on vector spaces because it is matrices and all
fourier transform

noise sensitivity curve
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#ICTS #may2024
13 - 5 - 2024
- Setup [WSL](https://learn.microsoft.com/en-us/windows/wsl/)
- Ubuntu is running well
- Installed software
- anaconda
- git
- VScode extensions to ssh from wsl to windows machine
- Gui apps (firefox, x11, nautilus)
- Can access files from both within linux and shows up as a separate location in windows
- ![[Pasted image 20240514121747.png]]
- ![[Pasted image 20240514124825.png]]
- Looked through [Parameter estimation](https://gitlab.com/vaishakp/parameter-estimation)
- Read through some of the links
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>ICTS Job Shadow Index</title>
<style>
body {
font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
color: #b31d0f;
background-color: #fafafa;
margin: 0;
padding: 0;
}
.container {
max-width: 800px;
margin: 0 auto;
padding: 20px;
}
h1, h2 {
color: #b31d0f;
}
p {
margin-bottom: 20px;
}
button {
color: #fafafa;
background-color: #b31d0f;
}

</style>
</head>
<body>
<div class="container">
<header>
<h1>Week 1 Activities at ICTS </h1>
<nav>
<button onclick="window.location.href='../index.html'">Index</button>
</nav>
</header>
<main>
<section id="Week 1">
<h2>Week 1</h2>
<p>Python notebooks and Markdown files of activities of Week 1</p>
</section>
<!-- Add your portfolio items here -->
</section>
</main>
<footer>
<!-- Add footer content if needed -->
</footer>
</div>
</body>
</html>
55 changes: 55 additions & 0 deletions Week_2/Log/Day 4.md
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#ICTS #may2024
15 - 5 - 2024
**10:40**
- Trying out [Parameter estimation](https://gitlab.com/vaishakp/parameter-estimation) in WSL

**11:00 to 12:00**
- working on the final document on overleaf

**12:00 to 1:00**

Group meeting/discussion on interesting paper found on Arxiv
[Members of Astrophysics Relativity Group at ICTS](https://www.icts.res.in/research/astrorel/members)

- https://arxiv.org/abs/2405.02197
- dont seem to address any numerical sources, only physical sources
- nrv sources
- listed possible reasons and does not go into that much of detail
- there are no figures in the document by choice
- not about physics but more about physical sources
- https://arxiv.org/abs/2405.05318
- it is a convoluted way to write
- whether they really did it from the masses
- only the sky location and time and brightness of the flares and the brightness should also be related to the mass
- brightness related to mass and gas
- if the black hole is more massive then there is more gas
- systematic more flare activity if the black hole is massive
- AGN flares
- https://arxiv.org/abs/2405.05884
- https://arxiv.org/abs/2405.05094
- https://arxiv.org/abs/2405.04690
- publically available data set from LISA
- catalog of possible sources
- dont know parameters
- analysing real LISA data and can be used for simulations
- used for software development
- markov chain monte carlo implemented on gpu
- fold the data which you get from LISA
- have they compared cpu vs gpu
- NERYN
- used nvidia a100 and 12 cpu
- dont think there is any machine learning like training over here
- https://lisa-ldc.lal.in2p3.fr/challenge2a
- https://arxiv.org/abs/2405.03841
- formation channel of neutron stars (factcheck)
- redefining many events
- surprised that they can claim which one formed first
- how do they decide what came first
- prior and then posterior estimation
- one object is a neutron star and another is black hole do we use information to construct priors using ()
- https://arxiv.org/abs/2405.03607
- when spins are gravitationally oriented, the radiation is not symmetric.
- this is also motivated by fact that equal mass binaries form largest kicks
- however asymmetric mass binaries form largest kicks
- equal mass binaries largest kicks is wrong so it is either a typo or something is not understood fully

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#ICTS #may2024
16 - 5 - 2024

**10:30 to 11:30**

Learned linux terminal commands and how to append a directory to PYTHONPATH
![[Pasted image 20240516132244.png]]
![[Pasted image 20240516132412.png]]
^appended directories to $PYTHONPATH

![[Pasted image 20240516132459.png]]
creating new environment for yumcee package testing
"-n" is the tag to name the env
"-c" is the tag to specify the repository of packages, in this case it is [conda-forge](https://conda-forge.org/)

"env" is a command to display current environment in linux


**11:30 to 1:00**

Learned the basics of Linear algebra
![[WhatsApp Image 2024-05-16 at 13.31.20_b56691a7.jpg]]
![[WhatsApp Image 2024-05-16 at 13.31.21_23955639.jpg]]
![[WhatsApp Image 2024-05-16 at 13.31.23_11818b52.jpg|330]]
Identity matrix is a diagonal matrix with all its diagonal elements equal to 1 , and zeroes everywhere else. [Newcastle University](https://www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/core-mathematics/pure-maths/matrices/matrix-arithmetic.html#:~:text=An%20identity%20matrix%2C%20sometimes%20called,1%20%2C%20and%20zeroes%20everywhere%20else.)


a(x) = x; where a (scalar) multiplying x (vector)

Rotation and Translation of matrix []

Look through this book when bored so I can learn more about Linear Algebra. Teaches it in a physics point of view. [Linear Algebra Klaus Janich.pdf](file:///C:%5CUsers%5Cdrpro%5CDownloads%5CLinear%20Algebra%20Klaus%20Janich.pdf)

- also figured out how to resize picture in obsidian, have to add a " | " and a number after image, eg. !["[sample.jpg|330]"]


Working on showing Autocorrelation code and understanding covariance matrix



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