Seminars

"Catalogue of Asteroseismically Calibrated Ages for APOGEE DR17"

Thibault Boulet (Institute of Astrophysics and Space Sciences, University of Porto, Portugal)

Understanding the Milky Way's formation and evolution requires precise stellar age determination across its components. Recent advances in asteroseismology, spectroscopy, stellar modeling, and machine learning, along with all-sky surveys, have provided reliable stellar age estimates. We aim to furnish accurate age assessments for the Main Red Star Sample within the APOGEE DR17 catalogue. Leveraging asteroseismic age constraints, we employ machine learning to achieve this goal. We explore optimal non-asteroseismic stellar parameters, including Teff​, L, [C/N], [Mg/Ce], [α/Fe], U(LSR), and 'Z' vertical height from the Galactic plane, to predict ages via categorical gradient boost decision trees. Our model, trained on merged samples from TESS and APOKASC-2 catalogs, achieves a median fractional age error of 20.8%, with a relative difference between the learning curves of 4.77%. For stars older than 3 Gyr, the error ranges from 7% to 23%; for those between 1 and 3 Gyr, it is 26% to 28%; and for stars younger than 1 Gyr, it is 43%. Applied to 125,445 stars, our analysis confirms the flaring of the young Galactic disc and reveals an age gradient among the youngest Galactic plane stars. We also identify two groups of metal-poor ([Fe/H] < -1 dex) and young (Age < 2 Gyr) stars exhibiting peculiar chemical abundances and halo kinematics. One of these groups is likely a remnant of the third gas infall episode that started around 2.7 Gyr ago.