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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.
The ESA space mission Gaia, planned to be launched at the end of 2013, will make astrometric, photometric and spectroscopic measurements of about 1 billion sources in our Galaxy. Amongst these sources will be numerous multiple systems. In the processing chain eclipsing binaries (EBs) will be detected and, if possible, their period and characteristics determined. Here we summarize the various steps that are foreseen to automatically classify and characterise these EBs.
We started a systematic search for periodic variable-star candidates in the EROS-2 database in the context of preparatory work for the Gaia satellite mission. The goal is to evaluate different classification tools and strategies, and to identify a large sample of variable candidates. In this paper we present the results of an assessment study of a three-step identification and classification process. In the study we took a sample of about 80,000 stars from one of the LMC EROS fields.
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