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. 
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