Hunting for open clusters in \textit{Gaia} DR2: the Galactic anticentre

A. Castro-Ginard, C. Jordi, X. Luri, T. Cantat-Gaudin, L. Balaguer-Núñez

Published 2019-05-15Version 1

The Gaia Data Release 2 (DR2) provided an unprecedented volume of precise astrometric and excellent photometric data. In terms of data mining the Gaia catalogue, machine learning methods have shown to be a powerful tool to, for instance, search for hitherto unknown stellar structures. Particularly, supervised and unsupervised learning methods combined together allow to significantly improve the detection of open clusters. We systematically scan Gaia DR2 in a region covering the Galactic anticentre and the Perseus arm (120<=l<=205 and -10<=b<=10), with the goal of populating this region with open clusters and fine tuning the methodology, proposed in arXiv:1805.03045v2 and successfully applied to TGAS data, adapting it to different density regions. Our methodology uses an unsupervised, density based, clustering algorithm, DBSCAN, that identifies over-densities in the five dimensional astrometric parameter space (l,b,\varpi,\mu_{\alpha^*},\mu_{\delta}) that may correspond to physical clusters. The over-densities are separated into physical clusters (open clusters) or random statistical clusters using an artificial neural network to recognise the isochrone pattern that open clusters show in a colour magnitude diagram. The method is able to recover more than 75% of the open clusters confirmed in the search area. Moreover, we are able to detect 58 open clusters unknown previous to Gaia DR2, which represent an increase of around 25% with respect to the already catalogued ones in this region. We find that the census of nearby open clusters is not complete. Different machine learning based methodologies for a blind search of open clusters are complementary to each other, with no single method being able to detect the 100% of the existing groups. Our methodology has shown to be a reliable tool for the automatic detection of open clusters, designed to be applied to the full Gaia DR2 catalogue.