Hunting for open clusters in Gaia DR2: 582 new open clusters in the Galactic disc

Abstract

Context. Open clusters are key targets for both Galaxy structure and evolution and stellar physics studies. Since Gaia DR2 publication, the discovery of undetected clusters has proven that our samples were not complete. Aims. Our aim is to exploit the Big Data capabilities of machine learning to detect new open clusters in Gaia DR2, and to complete the open cluster sample to enable further studies on the Galactic disc. Methods. We use a machine learning based methodology to systematically search in the Galactic disc, looking for overdensities in the astrometric space and identifying them as open clusters using photometric information. First, we use an unsupervised clustering algorithm, DBSCAN, to blindly search for these overdensities in Gaia DR2 (l, b, , µ α * , µ δ ). After that, we use a deep learning artificial neural network trained on colour-magnitude diagrams to identify isochrone patterns in these overdensities, and to confirm them as open clusters. Results. We find 582 new open clusters distributed along the Galactic disc, in the region |b| < 20 • . We can detect substructure in complex regions, and identify the tidal tails of a disrupting cluster UBC 274 of ∼ 3 Gyr located at ∼ 2 kpc. Conclusions. Adapting the methodology into a Big Data environment allows us to target the search driven by physical properties of the open clusters, instead of being driven by its computational requirements. This blind search for open clusters in the Galactic disc increases in a 45% the number of known open clusters.

Star Clusters Near and Far

“…Extensive all-sky star catalogs, such as the ASCC-2.5 bright star catalog (Kharchenko 2001), the two Micron All Sky Survey (2MASS Skrutskie et al 2006), or the Gaia catalog (Prusti et al 2016;Brown et al 2018) are necessary to attempt detecting those star clusters. Various studies, dating back to the 1970s (e.g., Becker and Fenkart 1971;Kharchenko et al 2005bKharchenko et al ,a, 2012Schmeja et al 2014;Scholz et al 2015;Castro-Ginard et al 2020) attempt to collect and classify a complete sample of open star clusters in the Milky Way. Kharchenko et al (2013a) present a sample of 3006 open clusters (see Fig.…”

The star cluster age function in the Galactic disc with Gaia DR2

“…To estimate the second factor, we use the experiment carried out by Castro-Ginard et al (2020). These authors investigated the recovery fraction of their catalogue by comparing the blindsearch detections to the OC list of Cantat-Gaudin et al (2018).…”

“…For that catalogue, the main cluster parameters age, distance modulus, and extinction were computed from the observed Gaia DR2 parallaxes and G versus (G BP −G RP ) colourmagnitude diagrams by a multi-layer-perceptron neural network trained on a set of 347 OCs with well-determined parameters (primarily from Bossini et al 2019). The cluster membership lists were mostly taken from Cantat-Gaudin & Anders (2020) and Castro-Ginard et al (2020). The typical log t uncertainties derived by the neural network amount to 0.15−0.25 for clusters younger than 300 Myr, and 0.1−0.15 for clusters older than that.…”

“…In a nutshell, we take into account two effects. First, to account for undetected clusters, we use the OC recovery experiment performed for the latest Galactic-plane OC search of Castro-Ginard et al (2020) to estimate the detection efficiency of their conservative method as a function of distance, sky region, and age. The second incompleteness effect stems from uncharacterised clusters: it was not possible to infer physical parameters in CGa20 for all Gaia-detected OCs.…”

Cluster membership for the long-period Cepheid calibrator SV Vul

“…After submission of this paper, Castro-Ginard et al (2020) presented the results of a systematic search for clusters, conducted by applying a machine learning methodology to Gaia DR2 data. Among their 245 class A candidate clusters, they find Alicante 13, under the name UBC 130, with centre at RA: 19:52:12.17, Dec: +27:26:42.9.…”