Astrometric Identification of Nearby Binary Stars I: Predicted Astrometric Signals
Zephyr Penoyre, Vasily Belokurov, N. Wyn Evans

TL;DR
This paper investigates how astrometric data from Gaia can be used to identify binary stars by analyzing errors and deviations, providing methods to detect binaries even before full data release.
Contribution
It introduces a new approach to detect binary systems from partial Gaia data using astrometric error metrics and provides criteria for identifying astrometric binaries.
Findings
80-90% of simulated binaries show detectable deviations
UWE and PMA peak near the survey's baseline period
Detection sensitivity depends on binary period and system properties
Abstract
We examine the capacity to identify binary systems from astrometric errors and deviations alone. Until the release of the fourth Gaia data release we lack the full astrometric time series that the satellite records, but as we show can still infer the presence of binaries from the best fit models, and their error, already available. We generate a broad catalog of simulated binary systems within 100 pc, and examine synthetic observations matching the Gaia survey's scanning law and astrometric data processing routine. We show how the Unit Weight Error (UWE) and Proper Motion Anomaly (PMA) vary as a function of period, and the properties of the binary. Both UWE and PMA peak for systems with a binary period close to the time baseline of the survey. Thus UWE can be expected to increase or remain roughly constant as we observe the same system over a longer baseline, and we suggest…
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