Gaia Data Release 2

Abstract

Context. More than half a million of the 1.69 billion sources in Gaia Data Release 2 (DR2) are published with photometric time series that exhibit light variations during the 22 months of observation. Aims. An all-sky classification of common high-amplitude pulsators (Cepheids, long-period variables, δ Scuti/SX Phoenicis, and RR Lyrae stars) is provided for stars with brightness variations greater than 0.1 mag in G band. Methods. A semi-supervised classification approach was employed, firstly training multi-stage random forest classifiers with sources of known types in the literature, followed by a preliminary classification of the Gaia data and a second training phase that included a selection of the first classification results to improve the representation of some classes, before the improved classifiers were applied to the Gaia data. Dedicated validation classifiers were used to reduce the level of contamination in the published results. A relevant fraction of objects were not yet sufficiently sampled for reliable Fourier series decomposition, consequently classifiers were based on features derived from statistics of photometric time series in the G, GBP, and GRP bands, as well as from some astrometric parameters. Results. The published classification results include 195 780 RR Lyrae stars, 150 757 long-period variables, 8550 Cepheids, and 8882 δ Scuti/SX Phoenicis stars. All of these results represent candidates whose completeness and contamination are described as a function of variability type and classification reliability. Results are expressed in terms of class labels and classification scores, which are available in the vari_classifier_result table of the Gaia archive.

Catalogue of new Herbig Ae/Be and classical Be stars

“…A variety of them have been used so far for similar matters. For example: random forests (Hedges et al 2018;Marton et al 2019;Rimoldini et al 2019), support vector machines (Małek et al 2013;Marton et al 2016;…”

Empirical completeness assessment of the Gaia DR2, Pan-STARRS 1, and ASAS-SN-II RR Lyrae catalogues

“…The second data release of Gaia (DR2) included 550 737 variables stars (Holl et al 2018) amongst which 228 904 are RRL stars. These RRLs were published in two partially overlapping outputs: (i) 195 780 sources in the variables classifier (VC, see Rimoldini et al 2019) which contains a label and classification score for each source, and (ii) 140 784 in the RRL Specific Object Studies (SOS, see Clementini et al 2019), which contains a large amount of detailed parameters including period, Fourier fitting parameters and photometric metallicity estimates. The overlap between the VC and SOS is 107 660 stars.…”

“…• VC: vari_classifier_result table with results from the variable classifier (Rimoldini et al 2019), contains 195 780 RRLs (with best_class_name: RRAB, RRC, RRD, ARRD),…”

“…The Gaia mission in its Second Data Release (DR2 Gaia Collaboration et al 2018) has provided what is currently the largest, deepest, all-sky catalogue of RR Lyrae (RRL) stars (Clementini et al 2019;Rimoldini et al 2019), reaching even highly crowded regions in the disc and bulge. The superb astrometry provided by Gaia DR2 combined with the power of using RRL stars as standard candles to measure precise distances beyond the reach of Gaia's parallaxes, are offering an unprecedented view of the structure and kinematics of the old populations ( 10 Gyr) of our Galaxy traced by RRLs.…”

“…In Section 2 we describe the three RRL catalogues used: Gaia DR2, PS1 and ASAS-SN-II. Gaia DR2 published two partially overlapping catalogues containing stars identified as RRLs based solely on their Gaia photometry: the Specific Objects Study (SOS, Clementini et al 2019) and VariClassifier (VC, Rimoldini et al 2019) catalogues, produced by two different pipelines and based on data with different characteristics (Holl et al 2018). Here we will combine them into a single RRL catalogue VC+SOS.…”