Star–galaxy classification in the Dark Energy Survey Y1 data set

Abstract

We perform a comparison of different approaches to star–galaxy classification using the broadband photometric data from Year 1 of the Dark Energy Survey. This is done by performing a wide range of tests with and without external ‘truth’ information, which can be ported to other similar data sets. We make a broad evaluation of the performance of the classifiers in two science cases with DES data that are most affected by this systematic effect: large-scale structure and MilkyWay studies. In general, even though the default morphological classifiers used for DES Y1 cosmology studies are sufficient to maintain a low level of systematic contamination from stellarmisclassification, contamination can be reduced to theO(1 per cent) level by using multi-epoch and infrared information from external data sets. For Milky Way studies, the stellar sample can be augmented by ~20 per cent for a given flux limit.