DECam Community Science Workshop 2018: Science Highlights, Coming Opportunities, LSST Synergies
May 21-22, 2018 • Tucson, Arizona
Mitigation of Photometric Systematics in Galaxy Clustering Measurements with Artificial Intelligence [2.6 MB PDF]
In order to get a robust measurement of clustering of large scale structures, it is crucial to understand imaging systematics and mitigate for the effects. In my talk, I would like to present our idea of using Neural Networks, using DECam DR5, to learn how galaxy density (in particular Emission Line Galaxies) depends on imaging systematics such as galactic extinction. This approach will be beneficial to large galaxy surveys and complementary to other typical approaches of correcting systematic effects like linear/quadratic regression.
Authors: Mehdi Rezaie