Bayesian analysis of ages, masses, and distances to cool stars with non-LTE spectroscopic parameters
Aldo Serenelli (1), Maria Bergemann (2), Gregory Ruchti (3), Luca, Casagrande (4) ((1) Institute of Space Sciences (CSIC-IEEC), (2) Max Planck, for Astrophysics, (3) Lund Observatory, (4) Research School of Astronomy,, Mount Stromlo)

TL;DR
This study employs Bayesian methods with non-LTE spectroscopic parameters to accurately determine ages, masses, and distances of cool stars, revealing systematic biases in LTE-based estimates and implications for Galactic evolution research.
Contribution
It introduces a Bayesian approach using non-LTE parameters for stellar characterization, improving accuracy over traditional LTE methods and highlighting potential biases in previous surveys.
Findings
LTE-based ages are underestimated by 10-30%.
Distances, especially for metal-poor giants, are significantly biased.
Systematic differences suggest LTE spectra limitations affect stellar parameter estimates.
Abstract
For studies of Galactic evolution, the accurate characterization of stars in terms of their evolutionary stage and population membership is of fundamental importance. A standard approach relies on extracting this information from stellar evolution models but requires the effective temperature, surface gravity, and metallicity of a star obtained by independent means. In previous work, we determined accurate effective temperatures and non-LTE logg and [Fe/H] (NLTE-Opt) for a large sample of metal-poor stars, -3<[Fe/H]<-0.5, selected from the RAVE survey. As a continuation of that work, we derive here their masses, ages, and distances using a Bayesian scheme and GARSTEC stellar tracks. For comparison, we also use stellar parameters determined from the widely-used 1D LTE excitation-ionization balance of Fe (LTE-Fe). We find that the latter leads to systematically underestimated stellar…
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