570 new open clusters in the Galactic disc

Since the Gaia data release 2 (DR2), the discovery of undetected clusters has shown that previous surveys were incomplete. 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 of the Galactic disc.

We use a machine-learning based methodology to systematically search the Galactic disc for overdensities in the astrometric space and identify the open clusters using photometric information. First, we used an unsupervised clustering algorithm, DBSCAN, to blindly search for these overdensities in Gaia DR2 (l, b, varpi, mu_alpha_*, mu_delta_), then we used 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.