BESTP — An automated Bayesian modeling tool for asteroseismology

Asteroseismic observations are crucial to constrain stellar models with precision. Bayesian Estimation of STellar Parameters (BESTP) is a tool that utilizes statistics and nested sampling Monte Carlo algorithm search for the best match given set classical asteroseismic constraints from observations. The computation evaluation efficiently performed in an automated multi-threaded way. To illustrate capabilities BESTP, we estimate fundamental properties Sun red-giant star HD 222076. In both cases, find consistent We also evaluate improvement precision parameters when oscillation frequencies individual modes included as constraints, compared case only large frequency separation included. For solar case, uncertainties estimated masses, radii ages reduced by 0.7%, 0.3% 8% respectively. 222076, they even more noticeably 2%, 0.5% 4.7%. note 10% age 222076 Gaia parallax constraint constraint.