Gaia Data Release 2 Variable stars in the colour-absolute magnitude diagram

Context. The ESA Gaia mission provides a unique time-domain survey for more than 1.6 billion sources with G ≲ 21 mag. Aims. We showcase stellar variabilityin the Galactic colour- absolute magnitudediagram (CaMD). We focus on pulsating, eruptive, and cataclysmic variables, as well as on starsthat exhibit variabilitythat is due to rotation and eclipses. Methods. We describe the locations of variable star classes, variableobject fractions, and typical variabilityamplitudes throughout the CaMD and show how variability-related changes in colour and brightness induce “motions”. To do this, we use 22 months of calibrated photometric, spectro-photometric, and astrometric Gaia data of starswith a significant parallax. To ensure that a large variety of variable starclasses populate the CaMD, we crossmatched Gaia sources with known variable stars. We also used the statistics and variabilitydetection modules of the Gaia variabilitypipeline. Corrections for interstellar extinction are not implemented in this article. Results. Gaia enables the first investigation of Galactic variable starpopulations in the CaMD on a similar, if not larger, scale as was previously done in the Magellanic Clouds. Although the observed colours are not corrected for reddening, distinct regions are visible in which variable starsoccur. We determine variable starfractions to within the current detection thresholds of Gaia. Finally, we report the most complete description of variability-induced motion within the CaMD to date. Conclusions. Gaia enables novel insights into variabilityphenomena for an unprecedented number of stars, which will benefit the understanding of stellar astrophysics. The CaMD of Galactic variable starsprovides crucial information on physical origins of variabilityin a way that has previously only been accessible for Galactic star clustersor external galaxies. Future Gaia data releases will enable significant improvements over this preview by providing longer time series, more accurate astrometry, and additional data types (time series BP and RP spectra, RVS spectra, and radial velocities), all for much larger samples of stars.