2016 Abstract from Pranav
Big Data Analytics for Identification of Gravitationally Lensed Quasars in the Dark Energy Survey
Pranav Sivakumar, Brian Nord, Liz Buckley-Geer
Abstract
We report results from an automated method to identify lensed quasars from the Dark Energy
Survey using a PSF-difference-based algorithm aimed at identifying close-separation lens
candidates. The PSF-difference algorithm utilizes the difference between PSF magnitude and
model magnitude, as well as image segmentation, to deblend and identify close-separation
candidates. In total, the algorithms identified 156 final lens candidates and also identified a
number of known lensed quasars within the DES footprint, indicating that the method described
in this paper is effective in identifying candidate lensed quasars. Efforts to obtain follow-up
observations for confirmation of the final candidates are ongoing, and constraints on
cosmological parameters will be discussed in future papers.