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

## TL;DR

This study assesses Gaia's ability to detect and classify eclipsing binary stars by analyzing Kepler data simulated with Gaia's observational cadence, proposing a classification scheme based on light curve morphology.

## Contribution

It introduces a method to evaluate Gaia's detectability of eclipsing binaries and develops a classification scheme using light curve fitting and clustering algorithms.

## Key findings

- Approximately 68% of Kepler eclipsing binaries are potentially detectable by Gaia.
- A classification scheme based on light curve morphology is proposed.
- Light curve fitting with polynomial and Gaussian models effectively characterizes sources.

## Abstract

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 imminent as we enter the Gaia era. 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 with 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. 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-SNE (t-distrubuted Stochastic Neighbor Embedding) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithms. We find that approximately 68% of Kepler Eclipsing Binary sources are potentially detectable by Gaia when folded with the Kepler period and 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.).