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We present a novel code, named SIESTA (Statistical matchIng between rEal and Synthetic sTellar popuLations), designed for performing statistical isochrone fitting to colour–magnitude diagrams (CMDs) of single stellar populations by leveraging comparisons between the observed stellar distribution and predictions from synthetic populations, simulated on top of a grid of isochrones. These synthetic populations encompass determinant factors such as the cluster's initial mass function (IMF), the presence of non-resolved binaries, as well as the expected photometric errors, and observational completeness (or the observed luminosity function). Employing Markov Chain Monte Carlo within a Bayesian framework, SIESTA allows for the determination of a cluster's age, metallicity, distance, colour excess, and binary fraction (with masses exceeding a certain ratio). In this study, we rigorously benchmark the SIESTA code utilizing synthetic populations and evaluate its performance against observations from the VISCACHA Survey in the Small Magellanic Cloud, focusing on five star clusters: Lindsay 114, NGC 152, Lindsay 91, Lindsay 113, and NGC 121. These clusters were chosen for their diverse age range, spanning from 0.04 to 10 Gyr. Our findings demonstrate the capability of the SIESTA code to accurately represent the observed CMDs of these clusters. Furthermore, we compare the results obtained with SIESTA to previous characterizations of these clusters, highlighting the consistency between the derived metallicity and spectroscopic determinations from various sources. [ABSTRACT FROM AUTHOR]

Estimates of interstellar extinction are essential in a broad range of astronomical research. In the last decades, several maps and models of the large-scale interstellar extinction in the Galaxy have been published. However, these maps and models have been developed in different programming languages, with different user interfaces and input/output formats, which makes using and comparing results from these maps and models difficult. To address this issue, we have developed a tool called GALE xtin (http://www.galextin.org), which estimates interstellar extinction based on both available 3D models/maps and 2D maps. The user only needs to provide a list with coordinates (and distance) and to choose a model/map. GALE xtin will then provide an output list with extinction estimates. It can be implemented in any other portal or model that requires interstellar extinction estimates. Here, a general overview of GALE xtin is presented, along with its capabilities, validation, performance and some results. [ABSTRACT FROM AUTHOR]

Globular clusters (GCs) are the most ancient stellar systems in the Milky Way. Therefore, they play a key role in the understanding of the early chemical and dynamical evolution of our Galaxy. Around 40 per cent of them are placed within ∼4 kpc from the Galactic centre. In that region, all Galactic components overlap, making their disentanglement a challenging task. With Gaia Data Release 2, we have accurate absolute proper motions for the entire sample of known GCs that have been associated with the bulge/bar region. Combining them with distances, from RR Lyrae when available, as well as radial velocities from spectroscopy, we can perform an orbital analysis of the sample, employing a steady Galactic potential with a bar. We applied a clustering algorithm to the orbital parameters apogalactic distance and the maximum vertical excursion from the plane, in order to identify the clusters that have high probability to belong to the bulge/bar, thick disc, inner halo, or outer halo component. We found that |$\sim 30{{\ \rm per\ cent}}$| of the clusters classified as bulge GCs based on their location are just passing by the inner Galaxy, they appear to belong to the inner halo or thick disc component, instead. Most GCs that are confirmed to be bulge GCs are not following the bar structure and are older than the epoch of the bar formation. [ABSTRACT FROM AUTHOR]