Toward a New Kind of Asteroseismic Grid Fitting
M. Gruberbauer, D. B. Guenther, T. Kallinger

TL;DR
This paper introduces a Bayesian approach for asteroseismic model fitting that accounts for systematic errors and improves the comparison of models with high-precision stellar oscillation data, exemplified by a detailed analysis of the Sun.
Contribution
It presents a novel probabilistic method for asteroseismic model fitting that handles systematic errors and prior mode identification, enhancing model-data comparison.
Findings
Estimated solar age of 4.591 billion years with 35 ± 5 million years pre-main sequence phase.
Derived initial element mass fractions consistent with recent studies.
Demonstrated the method's effectiveness through detailed solar analysis.
Abstract
Recent developments in instrumentation (e.g., in particular the Kepler and CoRoT satellites) provide a new opportunity to improve the models of stellar pulsations. Surface layers, rotation, and magnetic fields imprint erratic frequency shifts, trends, and other non-random behavior in the frequency spectra. As our observational uncertainties become smaller, these are increasingly important and difficult to deal with using standard fitting techniques. To improve the models, new ways to compare their predictions with observations need to be conceived. In this paper we present a completely probabilistic (Bayesian) approach to asteroseismic model fitting. It allows for varying degrees of prior mode identification, corrections for the discrete nature of the grid, and most importantly implements a treatment of systematic errors, such as the "surface effects." It removes the need to apply semi-…
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