Finding Quasars behind the Galactic Plane. IV. Candidate Selection from Chandra with Random Forest

Abstract Quasar samples remain severely incomplete at low Galactic latitudes because of strong extinction and source confusion. We conduct a systematic search for quasars behind the Galactic plane using X-ray sources from the Chandra Source Catalog (CSC), combined with optical data from Gaia Data Release 3 and mid-infrared data from CatWISE2020. Using spectroscopically confirmed quasars and stellar-type objects from datasets including DESI, the Sloan Digital Sky Survey, and LAMOST, we apply a random forest classifier to identify quasar candidates, with stellar contaminants suppressed using Gaia proper-motion constraints. Photometric redshifts are estimated for the candidates using a random forest regression model. Applying this framework to previously unclassified CSC sources, we identify 7570 quasar candidates, including 1060 Galactic plane quasar (GPQ) candidates at ∣ b ∣ < 20°, of which 551 are high-confidence candidates. Relative to the previously known GPQ sample, our selected GPQs reach lower optical and X-ray fluxes, improving sensitivity to low-flux GPQs. In addition, both the GPQ candidates and known GPQs display harder X-ray spectra than the all-sky quasar sample, consistent with increased absorption through the Galactic plane. Pilot spectroscopy confirms two high-confidence GPQ candidates as quasars at spectroscopic redshifts of z = 1.2582 and z = 1.1313, and further spectroscopic follow-up of the GPQ sample is underway. This work substantially improves the census of GPQs and provides a valuable target sample for future spectroscopic follow-up, enabling the use of GPQs to refine the reference frames for astrometry and probe the Milky Way interstellar and circumgalactic media with the absorption features of GPQs.