Modelling the Autocovariance of the Power Spectrum of a Solar-Type Oscillator
T. L. Campante, C. Karoff, W. J. Chaplin, Y. P. Elsworth, R. Handberg,, S. Hekker

TL;DR
This paper introduces an automated method to model and fit the autocovariance of the power spectrum of solar-type stars, enabling objective extraction of seismic parameters crucial for asteroseismology, especially useful for large datasets from missions like Kepler.
Contribution
The paper presents a novel automated procedure for modeling the autocovariance of stellar power spectra, reducing subjective bias in seismic parameter estimation.
Findings
Successfully applied to solar simulations with different magnitudes
Accurately retrieves mean small frequency separation and rotational splitting
Provides insights into precision and accuracy for Kepler-like observations
Abstract
Asteroseismology is able to conduct studies on the interiors of solar-type stars from the analysis of stellar acoustic spectra. However, such an analysis process often has to rely upon subjective choices made throughout. A recurring problem is to determine whether a signal in the acoustic spectrum originates from a radial or a dipolar oscillation mode. In order to overcome this problem, we present a procedure for modelling and fitting the autocovariance of the power spectrum which can be used to obtain global seismic parameters of solar-type stars, doing so in an automated fashion without the need to make subjective choices. From the set of retrievable global seismic parameters we emphasize the mean small frequency separation and, depending on the intrinsic characteristics of the power spectrum, the mean rotational frequency splitting. Since this procedure is automated, it can serve as…
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