Informing the Cataclysmic Variable Donor Sequence from Gaia DR2 Color-Magnitude and Inferred Variability Metrics
Nov 24, 2020Citations per year
Abstract: (arXiv)
Short-period cataclysmic variables (spCVs), with orbital periods below the period gap ( < 2 hr), offer insight into the evolutionary models of CVs and can serve as strong emitters of gravitational waves (GWs). To identify new spCV candidates, we crossmatch a catalog of known CVs to sources with robust parallaxes in the Gaia second data release (DR2). We uncover and fit an apparently monotonic relationship between the color--absolute-magnitude diagram (CMD) position and of these CVs, revealed in DR2. To supplement this relation, we develop a method for identifying sources with large photometric variability, a characteristic trait of spCVs. Using all available Gaia light curves, we construct a machine-learned regression model to predict variability metrics for sources in the CMD locus of known spCVs based solely on time-averaged covariates present in DR2. Using this approach we identify 3,253 candidate spCVs, of which 95% are previously unknown. Inspection of archival SDSS spectra of these candidates suggests that 82% are likely to be spCVs: a noticeably higher recovery rate than previous light curve searches, which bias toward active systems. We obtain optical spectra of 9 new systems at Lick Observatory and confirm that all objects are CV systems. We measure for 7 systems using archival Gaia and Palomar Transient Factory light curves, 3 of which do not have previous measurements. We use the CMD- relation to infer the detectability of these systems to the upcoming LISA mission, and find that six sources may be coherent LISA verification binaries, with an estimated SNR > 5 in the 4 yr mission. This paper demonstrates that the time-averaged Gaia catalog is a powerful tool in the methodical discovery and characterization of time-varying objects, making it complementary to missions like ZTF, TESS, and the Vera Rubin LSST.Note:
- 35 pages, 24 figures. Submitted to AAS Journals
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