A power-spectrum autocorrelation technique to detect global asteroseismic parameters

TL;DR

This paper introduces a moving-window autocorrelation method for analyzing asteroseismic power spectra to automatically determine key stellar oscillation parameters and infer stellar inclination and rotation characteristics.

Contribution

The paper presents a novel autocorrelation technique that efficiently extracts multiple asteroseismic parameters from Fourier spectra, improving automation and accuracy over previous methods.

Findings

Successfully applied to CoRoT and Kepler data

Accurately detects p-mode frequency and separations

Effective with artificial data simulations

Abstract

This article describes a moving-windowed autocorrelation technique which, when applied to an asteroseismic Fourier power spectrum, can be used to automatically detect the frequency of maximum p-mode power, large and small separations, mean p-mode linewidth, and constrain the stellar inclination angle and rotational splitting. The technique is illustrated using data from the CoRoT and Kepler space telescopes and tested using artificial data.