Hunting for open clusters in Gaia DR2: the Galactic anticentre

Abstract

Context. 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, for instance in the search for unknown stellar structures. Particularly, supervised and unsupervised learning methods combined together significantly improves the detection rate of open clusters. Aims. 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 finding any open clusters that may exist in this region, and fine tuning a previously proposed methodology successfully applied to TGAS data, adapting it to different density regions. Methods. Our methodology uses an unsupervised, density-based, clustering algorithm, DBSCAN, that identifies overdensities in the five-dimensional astrometric parameter space (l, b, , µ α * , µ δ ) that may correspond to physical clusters. The overdensities 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. Results. The method is able to recover more than 75% of the open clusters confirmed in the search area. Moreover, we detected 53 open clusters unknown previous to Gaia DR2, which represents an increase of more than 22% with respect to the already catalogued clusters in this region. Conclusions. We find that the census of nearby open clusters is not complete. Different machine learning methodologies for a blind search of open clusters are complementary to each other; no single method is able to detect 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.

Clusters and mirages: cataloguing stellar aggregates in the Milky Way

“…The excluded entries are: BH 140 and FSR 1758 (that the paper showed to be globular clusters), FSR 1716 (another globular, Minniti et al 2017;Koch et al 2017) that is erroneously included in the study as it is not flagged as such in MWSC, and Harvard 5 (a Article number, page 3 of 24 A&A proofs: manuscript no. mirages duplicate of Collinder 258); e) 46 clusters (including 41 COIN-Gaia clusters) whose members were published in Cantat-Gaudin et al (2019b); f) 57 UBC clusters whose members were published in Castro-Ginard et al (2018) and Castro-Ginard et al (2019); g) three UFMG clusters whose members were published by Ferreira et al (2019); for a total of 1481 objects.…”

Extended stellar systems in the solar neighborhood

“…Recent examples of techniques applied to Gaia astrometry are UPMASK (Krone-Martins & Moitinho 2014) and applications rooted in the popular clustering algorithms DBSCAN (Ester et al 1996) and HDBSCAN (Campello et al 2013;McInnes et al 2017). These algorithms have been used in extensive studies of stellar populations in the Galactic disk, for example, by Cantat-Gaudin et al (2018), Castro-Ginard et al (2019, and Kounkel & Covey (2019), respectively. These methods identify overdensities in the five-dimensional parameter space spanned by on-sky source coordinates (α, δ), proper motions (µ α * , µ δ ), and parallaxes ( ).…”

“…To some extent, photometric information is also used in the identification of distinct structures and membership determination. The applications of these algorithms have led to the identification of several hundred new open clusters in our local kiloparsec (e.g., Castro-Ginard et al 2019, and to the classification of numerous allegedly comoving string-like groups, see Kounkel & Covey (2019).…”

A Catalog of Newly Identified Star Clusters in Gaia DR2

“…They managed to obtain parameters and members for 1229 star clusters (60 of these were new). Recently, Castro-Ginard et al (2019) implemented a density based clustering algorithm, DBSCAN, and applied a supervised learning method (Castro-Ginard et al 2018) to Gaia DR2 data. 53 new OCs were detected in a region along the direction of Galactic anti-centre and the Perseus arm.…”