Identification of 30,000 White Dwarf–Main-sequence Binary Candidates from Gaia DR3 BP/RP (XP) Low-resolution Spectra

Abstract White dwarf–main-sequence (WD–MS) binary systems are essential probes for understanding binary stellar evolution and play a pivotal role in constraining theoretical models of various transient phenomena. In this study, we construct a catalog of WD–MS binaries using Gaia DR3’s low-resolution BP/RP (XP) spectra. Our approach integrates a model-independent neural network for spectral modeling with Gaussian process classification to accurately identify WD–MS binaries among over 10 million stars within 1 kpc. This study identifies approximately 30,000 WD–MS binary candidates, including 1700 high-confidence systems confirmed through spectral fitting. Our technique is shown to be effective at detecting systems where the MS star dominates the spectrum—cases that have historically challenged conventional methods. Validation using Galaxy Evolution Explorer photometry reinforces the reliability of our classifications: 70% of candidates with an absolute magnitude M G > 7 exhibit UV excess, a characteristic signature of WD companions. Our all-sky catalog of WD–MS binaries expands the available data set for studying binary evolution and WD physics and sheds light on the formation of WD–MS binaries.