Automated eclipsing binary detection: applying the Gaia CU7 pipeline to Hipparcos

TL;DR

This paper evaluates the Gaia CU7 pipeline's ability to detect eclipsing binaries by applying it to Hipparcos data, achieving high detection accuracy and period identification success.

Contribution

It demonstrates the pipeline's effectiveness in identifying eclipsing binaries and accurately determining their periods using Hipparcos data.

Findings

89% detection rate in confirmed eclipsing binaries

80% correct period identification

6% double or half period detection

Abstract

We demonstrate the eclipsing binary detection performance of the Gaia variability analysis and processing pipeline using Hipparcos data. The automated pipeline classifies 1,067 (0.9%) of the 118,204 Hipparcos sources as eclipsing binary candidates. The detection rate amounts to 89% (732 sources) in a subset of 819 visually confirmed eclipsing binaries, with the period correctly identified for 80% of them, and double or half periods obtained in 6% of the cases.