A Stellar Model-fitting Pipeline for Solar-like Oscillations

TL;DR

This paper introduces an automated stellar model-fitting pipeline utilizing a parallel genetic algorithm to analyze solar-like oscillations, aiming to improve the extraction of asteroseismic data from stellar observations.

Contribution

The paper presents a novel, objective pipeline for fitting stellar models to asteroseismic data, enhancing analysis accuracy and automation compared to previous methods.

Findings

Successfully applied to Sun data, accurately reproducing solar properties.

Demonstrated the pipeline's potential for analyzing data from Kepler and other missions.

Provides a foundation for analyzing a large number of Sun-like stars.

Abstract

Over the past two decades, helioseismology has revolutionized our understanding of the interior structure and dynamics of the Sun. Asteroseismology will soon place this knowledge into a broader context by providing structural data for hundreds of Sun-like stars. Solar-like oscillations have already been detected from the ground in several stars, and NASA's Kepler mission is poised to unleash a flood of stellar pulsation data. Deriving reliable asteroseismic information from these observations demands a significant improvement in our analysis methods. We report the initial results of our efforts to develop an objective stellar model-fitting pipeline for asteroseismic data. The cornerstone of our automated approach is an optimization method using a parallel genetic algorithm. We describe the details of the pipeline and we present the initial application to Sun-as-a-star data, yielding an optimal model that accurately reproduces the known solar properties.