Abstract
We present the results of an analysis aimed at testing the accuracy and precision of the PARSEC v1.2S library of stellar evolution models, in a Bayesian framework, to infer stellar parameters. We mainly employ the online DEBCat catalogue by Southworth, a compilation of detached eclipsing binary systems with published measurements of masses and radii to $\sim$ 2 per cent precision. We select a sample of 318 binary components, with masses between 0.10 and 14.5 Msun, at distances between 1.3 pc and ~ 8 kpc for Galactic objects and ~ 44-68 kpc for extragalactic ones. The Bayesian analysis applied takes as input effective temperature, radius, and [Fe/H], and their uncertainties, returning theoretical predictions for other stellar parameters. From the comparison with dynamical masses, we conclude that the inferred masses are precisely derived for stars on the main-sequence and in the core-helium-burning phase, with uncertainties of 4 per cent and 7 per cent, respectively, on average. Masses for subgiants and red giants are predicted within 14 per cent, and those for early asymptotic giant branch stars within 24 per cent. These results are helpful to further improve the models, in particular for advanced evolutionary stages for which our understanding is limited. We obtain distances and ages for the binary systems and compare them, whenever possible, with precise literature estimates, finding excellent agreement. We discuss evolutionary effects and challenges for inferring stellar ages from evolutionary models. We also provide useful polynomial fittings to theoretical zero-age main-sequence relationships.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.