Painting a portrait of the Galactic disc with its stellar clusters
[Context] The large astrometric and photometric survey performed by the Gaia mission allows for a panoptic view of the Galactic disc and its stellar cluster population. Hundreds of stellar clusters were only discovered after the latest Gaia data release (DR2) and have yet to be characterised. ; [Aims] Here we make use of the deep and homogeneous Gaia photometry down to G = 18 to estimate the distance, age, and interstellar reddening for about 2000 stellar clusters identified with Gaia DR2 astrometry. We use these objects to study the structure and evolution of the Galactic disc. ; [Methods] We relied on a set of objects with well-determined parameters in the literature to train an artificial neural network to estimate parameters from the Gaia photometry of cluster members and their mean parallax. ; [Results] We obtain reliable parameters for 1867 clusters. Our catalogue confirms the relative lack of old stellar clusters in the inner disc (with a few notable exceptions). We also quantify and discuss the variation of scale height with cluster age, and we detect the Galactic warp in the distribution of old clusters. ; [Conclusions] This work results in a large and homogeneous cluster catalogue, allowing one to trace the structure of the disc out to distances of ∼4 kpc. However, the present sample is still unable to trace the outer spiral arm of the Milky Way, which indicates that the outer disc cluster census might still be incomplete. ; We thank the referee for useful suggestions that helped clarify this paper. This work has made use of data from the European Space Agency (ESA) mission Gaia (www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, www.cosmos.esa. int/web/gaia/dpac/consortium). Funding for the DPAC has been provided. This work was supported by the MINECO (Spanish Ministry of Economy) through grant ESP2016-80079-C2-1-R and RTI2018-095076-B-C21 (MINECO/FEDER, UE), and MDM-2014-0369 of ICCUB (Unidad de Excelencia Mar a de Maeztu ). TCG acknowledges support from Juan de la Cierva Formaci n 2015 grant, MINECO (FEDER/UE). FA is grateful for funding from the European Union s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 800502. AM acknowledges the support from the Portuguese Strategic Programme UID/FIS/00099/2019 for CENTRA. AV and AB acknowledge PREMIALE 2015 MITiC. DB is supported in the form of work contract FCT/MCTES through national funds and by FEDER through COMPETE2020 in connection to these grants: UID/FIS/04434/2019; PTDC/FIS-AST/30389/2017 & POCI-01-0145-FEDER-030389. The preparation of this work has made extensive use of Topcat (Taylor 2005), and of NASA s Astrophysics Data System Bibliographic Services, as well as the open-source Python packages Astropy (Astropy Collaboration 2013), NumPy (Van DerWalt et al. 2011), and scikit-learn (Pedregosa et al. 2011). The figures in this paper were produced with Matplotlib (Hunter 2007). Figure 12 was produced with corner (Foreman-Mackey 2016).