The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists

Abstract The Transiting Exoplanet Survey Satellite (TESS) has surveyed nearly the entire sky in full-frame image mode with a time resolution of 200 s to 30 minutes and a temporal baseline of at least 27 days. In addition to the primary goal of discovering new exoplanets, TESS is exceptionally capable at detecting variable stars, and in particular short-period eclipsing binaries, which are relatively common, making up a few percent of all stars, and represent powerful astrophysical laboratories for deep investigations of stellar formation and evolution. We combed Sectors 1–82 of the TESS full-frame image data searching for eclipsing binary stars using a neural network that identified ∼1.2 million stars with eclipse-like features. Of these, we have performed an in-depth analysis on ∼60,000 targets using automated methods and manual inspection by citizen scientists. Here we present a catalog of 10,001 uniformly vetted and validated eclipsing binary stars that passed all our ephemeris and photocenter tests, as well as complementary visual inspection. Of these, 7936 are new eclipsing binaries while the remaining 2065 are known systems for which we update the published ephemerides. We outline the detection and analysis of the targets, discuss the properties of the sample, and highlight potentially interesting systems. Finally, we also provide a list of ∼900,000 unvetted and unvalidated targets for which the neural network found eclipse-like features with a score higher than 0.9, and for which there are no known eclipsing binaries within a sky-projected separation of a TESS pixel (≈21″).