Gaia colour-magnitude diagrams of young open clusters - Identification in the UBC catalogue and comparison between manual and automated analyses

Abstract

Context. Automated analyses of Gaia astrometric data have led to the discovery of many new high-quality open cluster candidates. When a good determination of their parameters is available, these objects become excellent tools for investigating the properties of our Galaxy. Aims. We explore whether young open clusters can be readily identified from Gaia data alone by studying the properties of their Gaia colour-magnitude diagrams. We also want to compare the results of a traditional cluster analysis with those of automated methods. Methods. We selected three young open cluster candidates from the UBC catalogue, ranging from a well-populated object with a well-defined sequence to a poorly populated and poorly defined candidate. We obtained classification spectra for the brightest stars in each. We redetermined members based on EDR3 data and fitted isochrones to derive the age, distance, and reddening. Results. All three candidates are real clusters with ages below 100 Ma. UBC 103 is a moderately populous cluster, with an age around 70 Ma. At a distance of ∼3 kpc, it forms a binary cluster with nearby NGC 6683. UBC 114 is a relatively proximal (∼1.5 kpc) poorly populated cluster containing two early-B stars. UBC 587 is a dispersed and very young (≤10 Ma) cluster located at ∼3 kpc, behind the Cygnus X region, which may be a valuable tracer of the Orion arm. Conclusions. The OCfinder methodology for the identification of new open clusters is extremely effective, with even poor candidates resulting in interesting detections. The presence of an almost vertical photometric sequence in the Gaia colour-magnitude diagram is a safe way to identify young open clusters. Automated methods for the determination of cluster properties give approximate solutions, but these are still subject to difficulties. There is some evidence suggesting that artificial intelligence systems may systematically underestimate extinction, which may impact in the age determination.