Star–galaxy classification in the Dark Energy Survey Y1 data set. Issue 4 (21st September 2018) - Sevilla-Noarbe, I; Hoyle, B; Marchã, M J; Soumagnac, M T; Bechtol, K; Drlica-Wagner, A; Abdalla, F; Aleksić, J; Avestruz, C; Balbinot, E; Banerji, M; Bertin, E; et al.
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 .