TL;DR
This paper develops a forward model of Gaia DR3's astrometric binary catalog selection function, enabling better statistical analysis of binary star populations by understanding detection biases and sensitivities.
Contribution
It introduces a method to simulate Gaia's selection function for astrometric binaries, including the effects of scanning law, measurement biases, and quality cuts, validated against actual Gaia data.
Findings
Selection function can be modeled from Gaia scanning law and data processing.
Mock catalog resembles Gaia DR3, validating the model.
Sensitivity drops at high eccentricities, weakly depends on inclination.
Abstract
Astrometry from Gaia DR3 has produced a sample of 170,000 Keplerian orbital solutions, with many more anticipated in the next few years. These data have enormous potential to constrain the population of binary stars, giant planets, and compact objects in the Solar neighborhood. But in order to use the published orbit catalogs for statistical inference, it is necessary to understand their selection function: what is the probability that a binary with a given set of properties ends up in a catalog? We show that such a selection function for the Gaia DR3 astrometric binary catalog can be forward-modeled from the Gaia scanning law, including individual 1D astrometric measurements, the fitting of a cascade of astrometric models, and quality cuts applied in post-processing. We populate a synthetic Milky Way model with binary stars and generate a mock catalog of astrometric orbits. The…
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