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In the new era of large-scale astronomical surveys, automated methods ofanalysis and classification of bulk data are a fundamental tool for fast andefficient production of deliverables. This becomes ever more imminent as weenter the Gaia era. We investigate the potential detectability of eclipsingbinaries with Gaia using a data set of all Kepler eclipsing binaries sampledwith Gaia cadence and folded with the Kepler period. The performance of fittingmethods is evaluated with comparison to real Kepler data parameters and aclassification scheme is proposed for the potentially detectable sources basedon the geometry of the light curve fits. The polynomial chain (polyfit) andtwo-Gaussian models are used for light curve fitting of the data set.Classification is performed with a combination of the t-SNE (t-distrubutedStochastic Neighbor Embedding) and DBSCAN (Density-Based Spatial Clustering ofApplications with Noise) algorithms. We find that approximately 68% of KeplerEclipsing Binary sources are potentially detectable by Gaia when folded withthe Kepler period and propose a classification scheme of the detectable sourcesbased on the morphological type indicative of the light curve, with subclassesthat reflect the properties of the fitted model (presence and visibility ofeclipses, their width, depth, etc.).

Gaia Eclipsing Binary and Multiple Systems. A study of detectability and classification of eclipsing binaries with Gaia