4 papers
A homogeneous three-dimensional view of Molecular Cloud kinematics out to 2.5 kpc. Using Young Stellar Objects and Open Clusters as complementary tracers
Xabier Pérez-Couto, Santiago Torres, Nuria Miret-Roig +4
Understanding the large-scale dynamics of molecular clouds (MCs) is crucial for constraining the processes that govern star formation and the structure and evolution of the Galaxy.…
Detection of hot subdwarf binaries and sdB stars using machine learning methods and a large sample of Gaia XP spectra
M. Ambrosch, C. Viscasillas Vázquez, E. Solano +10
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. W…
Finding White Dwarfs' Hidden Companions using an Unsupervised Machine Learning Technique
Xabier Pérez-Couto, Minia Manteiga, Eva Villaver
White dwarfs (WD) with main-sequence (MS) companions are crucial probes of stellar evolution. However, due to the significant difference in their luminosities, the WD is often outs…
Disentangling stellar atmospheric parameters in astronomical spectra using Generative Adversarial Neural Networks
Minia Manteiga, Raúl Santoveña, Marco A. Ãlvarez +4
A method based on Generative Adversaria! Networks (GANs) is developed for disentangling the physical (effective temperature and gravity) and chemical (metallicity, overabundance of…