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.

We present a catalogue of 362 million stellar parameters, distances, and extinctions derived from Gaia’s Early Data Release (EDR3) cross-matched with the photometric catalogues of Pan-STARRS1, SkyMapper, 2MASS, and AllWISE. The higher precision of the Gaia EDR3 data, combined with the broad wavelength coverage of the additional photometric surveys and the new stellar-density priors of the StarHorse code, allows us to substantially improve the accuracy and precision over previous photo-astrometric stellar-parameter estimates. At magnitude G = 14 (17), our typical precisions amount to 3% (15%) in distance, 0.13 mag (0.15 mag) in V-band extinction, and 140 K (180 K) in effective temperature. Our results are validated by comparisons with open clusters, as well as with asteroseismic and spectroscopic measurements, indicating systematic errors smaller than the nominal uncertainties for the vast majority of objects. We also provide distance- and extinction-corrected colour-magnitude diagrams, extinction maps, and extensive stellar density maps that reveal detailed substructures in the Milky Way and beyond. The new density maps now probe a much greater volume, extending to regions beyond the Galactic bar and to Local Group galaxies, with a larger total number density. We publish our results through an ADQL query interface (gaia.aip.de) as well as via tables containing approximations of the full posterior distributions. Our multi-wavelength approach and the deep magnitude limit render our results useful also beyond the next Gaia release, DR3.

We describe two ground‐based observing campaigns aimed at building a grid of approximately 200 spectrophotometric standard stars (SPSS), with an internal ≃1 per cent precision and tied to Vega within ≃3 per cent, for the absolute flux calibration of data gathered by Gaia, the European Space Agency (ESA) astrometric mission. The criteria for the selection and a list of candidates are presented, together with a description of the survey strategy and the adopted data analysis methods. We also discuss a short list of notable rejected SPSS candidates and difficult cases, based on identification problems, literature discordant data, visual companions and variability. In fact, all candidates are also monitored for constancy (within ±5 mmag, approximately). In particular, we report on a CALSPEC standard, 1740346, that we found to be a δ Scuti variable during our short‐term monitoring (1–2 h) campaign.

An unsettled question concerning the formation and distribution of massive stars is whether they must be born in massive clusters and, if found in less dense environments, whether they must have migrated there. With the advent of wide-area digital photometric surveys, it is now possible to identify massive stars away from prominent Galactic clusters without bias. In this study we consider 40 candidate OB stars found in the field around the young massive cluster, Westerlund 2, by Mohr-Smith et al (2017): these are located inside a box of 1.5×1.5 square degrees and are selected on the basis of their extinctions and K magnitudes. We present VLT/X-shooter spectra of two of the hottest O stars, respectively 11 and 22 arcmin from the centre of Westerlund 2. They are confirmed as O4V stars, with stellar masses likely to be in excess of 40 M . Their radial velocities relative to the non-binary reference object, MSP 182, in Westerlund 2 are −29.4±1.7 and −14.4±2.2 km s −1 , respectively. Using Gaia DR2 proper motions we find that between 8 and 11 early O/WR stars in the studied region (including the two VLT targets, plus WR 20c and WR 20aa) could have been ejected from Westerlund 2 in the last one million years. This represents an efficiency of massive-star ejection of up to ∼ 25%. On sky, the positions of these stars and their proper motions show a near N-S alignment. We discuss the possibility that these results are a consequence of prior sub-cluster merging combining with dynamical ejection.

We present a sub-arcsecond cross-match of Gaia DR2 against the INT Photometric Hα Survey of the Northern Galactic Plane Data Release 2 (IPHAS DR2) and the Kepler -INT Survey (KIS). The resulting value-added catalogues (VACs) provide additional precise photometry to the Gaia photometry (r, i and Hα for IPHAS, with additional U and g for KIS). In building the catalogue, proper motions given in Gaia DR2 are wound back to match the epochs of IPHAS DR2, thus ensuring high proper motion objects are appropriately cross-matched. The catalogues contain 7,927,224 and 791,071 sources for IPHAS and KIS, respectively. The requirement of > 5σ parallax detection for every included source means that distances out to 1-1.5 kpc are well covered. We define two additional parameters for each catalogued object: (i) f c , a magnitudedependent tracer of the quality of the Gaia astrometric fit; (ii) f F P , the false-positive rate for parallax measurements determined from astrometric fits of a given quality at a given magnitude. Selection cuts based on these parameters can be used to clean colour-magnitude and colour-colour diagrams in a controlled and justified manner. We provide both full and light versions of the VAC, with VAC-light containing only objects that represent our recommended trade-off between purity and completeness. Uses of the catalogues include the identification of new variable stars in the matched data sets, and more complete identification of Hα-excess emission objects thanks to separation of high-luminosity stars from the main sequence.