Bayesian mass and age estimates for transiting exoplanet host stars
P. F. L. Maxted (1), A. M. Serenelli (2), J. Southworth (1) ((1) Keele, University, UK, (2) CSIC-IEEC, Spain)

TL;DR
This paper presents a Bayesian method to accurately estimate the mass and age of transiting exoplanet host stars using their density, temperature, metallicity, and luminosity, validated against stellar models and binary systems.
Contribution
It introduces a Bayesian framework with a dense grid of stellar models and MCMC sampling to derive posterior distributions for stellar mass and age, improving accuracy and robustness.
Findings
Masses are recovered within 5% in 90% of cases.
Age estimates are accurate within 25%.
Method is validated against binary star data.
Abstract
The mean density of a star transited by a planet, brown dwarf or low mass star can be accurately measured from its light curve. This measurement can be combined with other observations to estimate its mass and age by comparison with stellar models. Our aim is to calculate the posterior probability distributions for the mass and age of a star given its density, effective temperature, metallicity and luminosity. We computed a large grid of stellar models that densely sample the appropriate mass and metallicity range. The posterior probability distributions are calculated using a Markov-chain Monte-Carlo method. The method has been validated by comparison to the results of other stellar models and by applying the method to stars in eclipsing binary systems with accurately measured masses and radii. We have explored the sensitivity of our results to the assumed values of the mixing-length…
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