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The Asteroid Terrestrial-impact Last Alert System (ATLAS) carries out itsprimary planetary defense mission by surveying about 13000 deg^2 at least fourtimes per night. The resulting data set is useful for the discovery of variablestars to a magnitude limit fainter than r~18, with amplitudes down to 0.01 magfor bright objects. Here we present a Data Release One catalog of variablestars based on analyzing 142 million stars measured at least 100 times in thefirst two years of ATLAS operations. Using a Lomb-Scargle periodogram and othervariability metrics, we identify 4.7 million candidate variables which weanalyze in detail. Through Space Telescope Science Institute, we publiclyrelease lightcurves for all of them, together with a vector of 169classification features for each star. We do this at the level of unconfirmedcandidate variables in order to provide the community with a large set ofhomogeneously analyzed photometry and avoid pre-judging which types of objectsothers may find most interesting. We use machine learning to classify thecandidates into fifteen different broad categories based on lightcurvemorphology. About 10% (430,000 stars) pass extensive tests designed to screenout spurious variability detections: we label these as `probable' variables. Ofthese, 230,000 receive specific classifications as eclipsing binaries,pulsating, Mira-type, or sinusoidal variables: these are the `classified'variables. New discoveries among the probable variables number more than300,000, while 150,000 of the classified variables are new, including about10,000 pulsating variables, 2,000 Mira stars, and 70,000 eclipsing binaries.

A First Catalog of Variable Stars Measured by the Asteroid Terrestrial-impact Last Alert System (ATLAS)