Related papers: Machine Learning Regression of extinction in the s…
This paper is the second in a series, implementing a classification system for Gaia observations of unresolved galaxies. Our goals are to determine spectral classes and estimate intrinsic astrophysical parameters via synthetic templates.…
The discovery of exoplanets has expanded our understanding of planetary systems and opened new avenues for astronomical research. In this study, we present a machine learning (ML) framework for exoplanet identification using a time-series…
A new method for the determination of the extinction in our Galaxy is proposed. The method uses surface brightnesses of external galaxies in the B and R bands. The observational data have been taken from the ESO-LV galaxy catalogue. As a…
The third Gaia Data Release has provided the astronomical community with astrometric data of more than 1.8 billion sources, and low resolution spectra for 220 million. Such a large amount of data is difficult to handle by means of visual…
We present a catalogue of 362 million stellar parameters, distances, and extinctions derived from Gaia's early third data release (EDR3) cross-matched with the photometric catalogues of Pan-STARRS1, SkyMapper, 2MASS, and AllWISE. The higher…
Aims:The Gaia astrometric survey mission will, as a consequence of its scanning law, obtain low resolution optical (330-1000 nm) spectrophotometry of several million unresolved galaxies brighter than V=22. We present the first steps in a…
Gaia DR3 contains 1.8 billion sources with G-band photometry, 1.5 billion of which with BP and RP photometry, complemented by positions on the sky, parallax, and proper motion. The median number of field-of-view transits in the three…
Astronomy is entering an unprecedented era of Big Data science, driven by missions like the ESA's Gaia telescope, which aims to map the Milky Way in three dimensions. Gaia's vast dataset presents a monumental challenge for traditional…
Accurate distance measurements to supernova remnants (SNRs) are essential for determining their physical parameters, such as size, age, explosion energy, and for constraining the properties of associated neutron stars (NSs). We present an…
We present new three-dimensional (3D) interstellar extinction maps in the $V$ and Gaia $G$ filters within 2 kpc of the Sun, a 3D differential extinction (dust spatial distribution density) map along the lines of sight in the same space, a…
The statistical characteristics of double main-sequence (MS) binaries are essential for investigating star formation, binary evolution, and population synthesis. Our previous study proposed a machine learning-based method to identify MS…
Asteroseismology has become widely accepted as a benchmark for accurate and precise fundamental stellar properties. It can therefore be used to validate and calibrate stellar parameters derived from other approaches. Meanwhile, one can…
Context. While Gaia enables to probe in great detail the extended local neighbourhood, the thin disk structure at larger distances remains sparsely explored. Aims. We aim here to build a non-parametric 3D model of the thin disc structures…
The third Gaia data release (DR3) contains $\sim$170\,000 astrometric orbit solutions of two-body systems located within $\sim$500 pc of the Sun. Determining component masses in these systems, in particular of stars hosting exoplanets,…
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)…
In this first paper we simulate the population of disc Red Clump stars to be observed by Gaia. We generate a set of test particles and we evolve it in a 3D barred Milky Way like galactic potential. We assign physical properties of the Red…
The second data release (DR2) of Gaia provides mean photometry in three bands for $\sim$1.4 billion sources, but light curves and variability properties are available for only $\sim$0.5 million of them. Here, we provide a census of…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
Observational astronomy has undergone a significant transformation driven by large-scale surveys, such as the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) Survey, the Sloan Digital Sky Survey (SDSS), and the Gaia…
Gaia Data Release 3 (DR3) provides extensive information on the astrophysical properties of stars, such as effective temperature, surface gravity, metallicity, and luminosity, for over 470 million objects. However, as Gaia's stellar…