Related papers: Deep learning interpretability analysis for carbon…
3D maps of interstellar dust are crucial for understanding the structure of the Milky Way interstellar medium to apply correction to astrophysical observations affected by dust. We aim at providing new extinction estimates in the Gaia BP/RP…
Context. Gaia has been in operations since 2014. The third Gaia data release expands from the early data release (EDR3) in 2020 by providing 34 months of multi-epoch observations that allowed us to probe, characterise and classify…
While Gaia has observed the phase space coordinates of over a billion stars in the Galaxy, in the overwhelming majority of cases it has only obtained five of the six coordinates, the missing dimension being the radial (line-of-sight)…
The determination of chemical abundances constitutes a fundamental requirement for obtaining a complete picture of a star. Particularly in massive stars, CNO abundances are of prime interest, due to the nuclear CNO-cycle and various mixing…
In this study, we present an interpretable deep learning framework for the early detection of breast cancer using quantitative features extracted from digitized fine needle aspirate (FNA) images of breast masses. Our deep neural network,…
Tidally stripped galaxy nuclei and luminous globular clusters (GCs) are important tracers of the halos and assembly histories of nearby galaxies, but are difficult to reliably identify with typical ground-based imaging data. In this paper…
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine…
We present near-IR spectroscopy of the massive intermediate age star cluster W3 in the merger remnant galaxy NGC 7252, obtained with the NTT telescope. This cluster has an age when the integrated near-IR properties of a stellar population…
We develop and test a method for the estimation of metallicities ([Fe/H]) and carbon abundance ratios ([C/Fe]) for carbon-enhanced metal-poor (CEMP) stars, based on application of artificial neural networks, regressions, and synthesis…
Nowadays, it is broadly recognized in the power system community that to meet the ever expanding energy sector's needs, it is no longer possible to rely solely on physics-based models and that reliable, timely and sustainable operation of…
A new classification system for carbon-rich stars is presented based on an analysis of 51 AGB carbon stars through the most relevant classifying indices available. The extension incorporated, that also represents the major advantage of this…
Gaia Data Release 3 will contain more than a billion sources with positions, parallaxes, and proper motions. In addition, for hundreds of millions of stars, it will include low-resolution blue photometer (BP) and red photometer (RP)…
Machine learning has become a popular tool to help us make better decisions and predictions, based on experiences, observations and analysing patterns within a given data set without explicitly functions. In this paper, we describe an…
With the unprecedented increase of known star clusters, quick and modern tools are needed for their analysis. In this work, we develop an artificial neural network trained on synthetic clusters to estimate the age, metallicity, extinction,…
Based on data from the ESA Gaia Data Release 2 (DR2) and several ground-based, multi-band photometry surveys we compiled an all-sky catalogue of $39\,800$ hot subluminous star candidates selected in Gaia DR2 by means of colour, absolute…
In this letter, we have carried out an independent validation of the Gaia EDR3 photometry using about 10,000 Landolt standard stars from Clem & Landolt (2013). Using a machine learning technique, the UBVRI magnitudes are converted into the…
Context. Planetary nebulae (PNe) are a brief but important phase of stellar evolution. The study of Galactic PNe has historically been hampered by uncertain distances, but the parallaxes of PN central stars (CSPNe) measured by Gaia are…
Airborne light detection and ranging (LiDAR) plays an increasingly significant role in urban planning, topographic mapping, environmental monitoring, power line detection and other fields thanks to its capability to quickly acquire…
This paper describes the identification of Gaia counterparts of a sample of oxygen-rich AGB stars with OH maser emission as a first step towards the compilation of a general Gaia Catalogue of Galactic AGB stars. With this catalogue, tests…
Large-scale spectroscopic surveys have collectively observed millions of stars across the Milky Way, but each derives stellar labels using independent pipelines with distinct modelling assumptions, introducing systematic offsets that…