Mon. Not. R. Astron. Soc., 479, 4416-4431 (2018/October-0)
Surface correction of main-sequence solar-like oscillators with the Kepler LEGACY sample.
COMPTON D.L., BEDDING T.R., BALL W.H., STELLO D., HUBER D., WHITE T.R. and KJELDSEN H.
Abstract (from CDS):
Poor modelling of the surface regions of solar-like stars causes a systematic discrepancy between the observed and model pulsation frequencies. We aim to characterize this frequency discrepancy for main-sequence solar-like oscillators for a wide range of initial masses and metallicities. We fit stellar models to the observed mode frequencies of the 67 stars, including the Sun, in the Kepler LEGACY sample, using three different empirical surface corrections. The three surface corrections we analyse are a frequency power-law, a cubic frequency term divided by the mode inertia and a linear combination of an inverse and cubic frequency term divided by the mode inertia. We construct a grid of stellar evolution models using the stellar evolution code MESA and calculate mode frequencies using GYRE. We scale the frequencies of each stellar model by an empirical calculated homology coefficient, which greatly improves the robustness of our grid. We calculate stellar parameters and surface corrections for each star using the average of the best-fitting models from each evolutionary track, weighted by the likelihood of each model. The resulting model stellar parameters agree well with an independent reference, the BASTA pipeline. However, we find that the adopted physics of the stellar models has a greater impact on the fitted stellar parameters than the choice of correction method. We find that scaling the frequencies by the mode inertia improves the fit between the models and observations. The inclusion of the inverse frequency term produces substantially better model fits to lower surface gravity stars.
© 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society
asteroseismology - stars: oscillations - stars: fundamental parameters
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