Abstract
We perform a comparison of different approaches to star–galaxy classification using the broad-band 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 Milky Way 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 stellar misclassification, contamination can be reduced to the O(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. Reference catalogues used in this work are available at http://des.ncsa.illinois.edu/releases/y1a1.
