Volume 602, June 2017
|Number of page(s)||9|
|Section||Numerical methods and codes|
|Published online||22 June 2017|
Gaia eclipsing binary and multiple systems. A study of detectability and classification of eclipsing binaries with Gaia
1 University of Ljubljana, Deptartment of Physics, Jadranska 19, 1000 Ljubljana, Slovenia
2 University of Geneva, Department of Astronomy, Chemin des Maillettes 51, 1290 Versoix, Switzerland
3 Villanova University, Department of Astrophysics and Planetary Science, 800 Lancaster Ave, Villanova, PA 19085, USA
4 University of Geneva, Department of Astronomy, Chemin d’Ecogia 16, 1290 Versoix, Switzerland
Received: 25 October 2016
Accepted: 26 March 2017
Context. In the new era of large-scale astronomical surveys, automated methods of analysis and classification of bulk data are a fundamental tool for fast and efficient production of deliverables. This becomes ever more important as we enter the Gaia era.
Aims. We investigate the potential detectability of eclipsing binaries with Gaia using a data set of all Kepler eclipsing binaries sampled with Gaia cadence and folded with the Kepler period. The performance of fitting methods is evaluated in comparison to real Kepler data parameters and a classification scheme is proposed for the potentially detectable sources based on the geometry of the light curve fits.
Methods. The polynomial chain (polyfit) and two-Gaussian models are used for light curve fitting of the data set. Classification is performed with a combination of the t-distributed stochastic neighbor embedding (t-SNE) and density-based spatial clustering of applications with noise (DBSCAN) algorithms.
Results. We find that ~68% of the Kepler Eclipsing Binary Catalog sources are potentially detectable by Gaia when folded with the Kepler period; we propose a classification scheme of the detectable sources based on the morphological type indicative of the light curve with subclasses that reflect the properties of the fitted model (presence and visibility of eclipses, their width, depth, etc.).
Key words: binaries: eclipsing / surveys / methods: numerical / methods: data analysis
© ESO, 2017
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