X. Pérez-Couto | Searcharxiv

arXiv2026

3I/ATLAS: In Search of the Witnesses to Its Voyage

3I/ATLAS is the third interstellar object discovered to date, following 1I/'Oumuamua and 2I/Borisov. Its unusually high excess velocity and active cometary nature make it a key probe of the Galactic population of icy planetesimals. Understanding its origin requires tracing its past trajectory through the Galaxy and assessing the possible role of stellar encounters, both as a potential origin and a perturber to its orbit. We integrated the orbit of 3I/ATLAS backward in time for 10 Myr, together with a sample of Gaia DR3 stars with high-quality astrometry and radial velocities, to identify close passages within 2 pc. We identify 93 nominal encounters, 62 of which are significant at the $2σ$ level. However, none of these encounters produced any meaningful perturbation. The strongest perturber Gaia DR3 6863591389529611264 at 0.30 pc and with a relative velocity of 35 km s$^{-1}$, imparted only a velocity change of $|Δv| \simeq 5\times10^{-4}$ km s$^{-1}$ to the orbit of 3I/ATLAS. Our results indicate that no stellar flybys within the past 10 Myr and 500 pc contained in Gaia DR3 can account for the present trajectory of 3I/ATLAS or be associated with its origin. We further show that 3I/ATLAS is kinematically consistent with a thin-disk population, despite its large peculiar velocity.

astro-ph.EP↗

arXiv2026

Detection of hot subdwarf binaries and sdB stars using machine learning methods and a large sample of Gaia XP spectra

Hot subdwarfs (hot sds) are compact, evolved stars near the Extreme Horizontal Branch (EHB) and are key to understanding stellar evolution and the ultraviolet excess in galaxies. We extend our previous analysis of Gaia XP spectra of hot subdwarf stars to a much larger sample, enabling a comprehensive study of their physical and binary properties. Our goal is to identify patterns in Gaia XP spectra, investigate binarity, and assess the influence of parameters such as temperature, helium abundance, and variability. We analyse approximately 20000 hot subdwarf candidates selected from the literature, combining Gaia XP data with published parameters. We apply Uniform Manifold Approximation and Projection (UMAP) to the XP coefficients, which represent the Gaia XP spectra in a compact, feature-based form, to construct a similarity map. We then use self-organizing maps (SOMs) and convolutional neural networks (CNNs) to classify spectra as binaries or singles, and as cool and helium-poor or hot and helium-rich. The spectra are normalised using asymmetric least squares baseline fitting to emphasise individual spectral features. The BP-RP colour dominates the similarity map, with additional influence from temperature, helium abundance, and variability. Most binaries, identified via the Virtual Observatory SED Analyser (VOSA), cluster in two filaments linked to main sequence companions. CNN classification suggests a strong correlation between variability and binarity, with binary fractions exceeding 60 percent for active hot subdwarfs. Gaia XP spectra combined with dimensionality reduction and machine learning effectively reveal patterns in hot subdwarf properties. Our findings indicate that binarity and environmental density strongly shape the evolutionary paths of hot subdwarfs, and we identify possible contamination by main sequence and cataclysmic variable stars in the base sample.

astro-ph.SR↗