oai:arXiv.org:2501.14494
sciences : astrophysique
2025
12/02/2025
White dwarf-main sequence (WDMS) 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 WDMS binaries using Gaia DR3's low-resolution BP/RP (XP) spectra.
Our approach integrates a model-independent neural network for spectral modelling with Gaussian Process Classification to accurately identify WDMS binaries among over 10 million stars within 1 kpc.
This study identify approximately 30,000 WDMS binary candidates, including ~1,700 high-confidence systems confirmed through spectral fitting.
Our technique is shown to be effective at detecting systems where the main-sequence star dominates the spectrum - cases that have historically challenged conventional methods.
Validation using GALEX photometry reinforces the reliability of our classifications: 70\% of candidates with an absolute magnitude $M_{G} > 7$ exhibit UV excess, a characteristic signature of white dwarf companions.
Our all-sky catalog of WDMS binaries expands the available dataset for studying binary evolution and white dwarf physics and sheds light on the formation of WDMS.
;Comment: 30 pages, 12 figures, Submitted to ApJS
Li, Jiadong,Ting, Yuan-Sen,Rix, Hans-Walter,Green, Gregory M.,Hogg, David W.,Ren, Juan-Juan,Müller-Horn, Johanna,Seeburger, Rhys, 2025, Identification of 30,000 White Dwarf-Main Sequence binaries candidates from Gaia DR3 BP/RP(XP) low-resolution spectra