A million binaries from Gaia eDR3: sample selection and validation of Gaia parallax uncertainties
Kareem El-Badry, Hans-Walter Rix, and Tyler M. Heintz

TL;DR
This paper creates a large catalog of binary stars within 1 kpc using Gaia eDR3 data, and uses it to validate and calibrate Gaia's parallax uncertainties, revealing underestimations especially for brighter stars and those with close companions.
Contribution
It provides a comprehensive binary star catalog and an empirical calibration for Gaia parallax uncertainties, improving the reliability of stellar distance measurements.
Findings
Gaia parallax uncertainties are reliable for faint stars ($G extgreater 18$).
Uncertainties are underestimated for bright stars and those with close companions.
Empirical correction functions are provided to adjust Gaia parallax errors.
Abstract
We construct from Gaia eDR3 an extensive catalog of spatially resolved binary stars within 1 kpc of the Sun, with projected separations ranging from a few au to 1 pc. We estimate the probability that each pair is a chance alignment empirically, using the Gaia catalog itself to calculate the rate of chance alignments as a function of observables. The catalog contains 1.3 (1.1) million binaries with >90% (>99%) probability of being bound, including 16,000 white dwarf -- main sequence (WD+MS) binaries and 1,400 WD+WD binaries. We make the full catalog publicly available, as well as the queries and code to produce it. We then use this sample to calibrate the published Gaia DR3 parallax uncertainties, making use of the binary components' near-identical parallaxes. We show that these uncertainties are generally reliable for faint stars (), but are underestimated…
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