DMTN-006 False Positive Rates in the LSST Image Differencing Pipeline

An analysis of the false positives in Decam imaging data processed by the LSST pipeline.

View this technote at http://dmtn-006.lsst.io or see a preview of the current version in this repo.

Contents

In addition to the technical note text, several components of the code used for this analysis are also included in this repository. They are

• python/diasource_mosaic.py - Creates a mosaic of postage stamp images (showing science, template, and difference images) for all DIA source detections.
• python/forcePhotDiaSources.py - This script is used to measure force photometry on the science and template images at the locations of all DIA sources detected by the stack's imageDifference.py.
• notebooks/forced_photometry.ipynb - This notebook performs the analysis of the force photometry output.
• notebooks/forced_phot_sql.ipynb - This version of the analysis is better equipped for working on all of the fields at once.
• notebooks/noise_analysis.ipynb - Analysis of the per-pixel noise estimates in the direct (science and template) Decam images.
• notebooks/masked_fraction.ipynb - Estimate of the area lost by excluding small regions around bright stars.
• notebooks/defect_sources.ipynb - Analysis of DIA sources that reoccur at fixed pixel positions in multiple fields.

Build this technical note

You can clone this repository and build the technote locally with Sphinx

git clone https://github.com/lsst-dm/dmtn-006
cd dmtn-006
pip install -r requirements.txt
make html

The built technote is located at _build/html/index.html.

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Copyright 2016 AURA/LSST

This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.