Identifying RR Lyrae Stars in the Dark Energy Survey

Abstract

RR Lyrae are evolved variable stars which act as powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its deep and wide coverage (g ∼ 24.3 mag in a single exposure; over 5000 deg²) provides a rich opportunity to search for substructures out to the edge of the Milky Way halo. However, the sparse and unevenly sampled multiband light curves from the DES wide-field survey pose a challenge for traditional techniques used to detect RRL. We present an empirically motivated and computationally efficient template fitting method to identify these variable stars in sparsely sampled multiband data. We apply this technique to light curves from two DES data releases and identify thousands of RRL. We then search the RRL catalog for groups of spatially nearby RRL in our catalog and recover multiple previously identified stellar overdensities, demonstrating the efficacy of this method to trace Galactic substructures. We make the resultant RRL catalogs and the template fitting methods available for use in other sparse multiband data sets.