Identifying Candidate Optical Variables Using Gaia Data Release 2

TL;DR

This paper demonstrates a method to identify candidate variable stars in Gaia Data Release 2 by analyzing photometric uncertainties, resulting in a catalog of approximately 9.3 million potential variables and insights into their amplitude of variability.

Contribution

The study introduces a novel approach to detect variable stars using photometric uncertainties in Gaia DR2, expanding the catalog of candidate variables without requiring epoch photometry.

Findings

Identified about 9.3 million candidate variable stars.

Photometric uncertainties encode information about variability amplitude.

Method effectively distinguishes variables based on expected uncertainties.

Abstract

Gaia is undertaking a deep synoptic survey of the Galaxy, but photometry from individual epochs has, as of yet, only been released for a minimal number of sources. We show that it is possible to identify variable stars in Gaia Data Release 2 by selecting stars with unexpectedly large photometric uncertainties given their brightness and number of observations. By comparing our results to existing catalogs of variables, we show that information on the amplitude of variability is also implicitly present in the Gaia photometric uncertainties. We present a catalog of about 9.3 million candidate variable stars, and discuss its limitations and prospects for future tests and extensions.