Bayesian approach for g-mode detection, or how to restrict our imagination

TL;DR

This paper advocates for a Bayesian approach to g-mode detection in helioseismology, aiming to broaden the scope beyond traditional methods constrained by prior assumptions, and provides initial examples to encourage further development.

Contribution

It introduces the concept of applying Bayesian inference to spectral analysis for gravity mode detection, highlighting its potential to expand the possibilities in helioseismic studies.

Findings

Bayesian methods can be applied to spectral analysis.

Initial examples demonstrate potential for gravity mode detection.

Encourages further development of Bayesian approaches in helioseismology.

Abstract

Nowadays, g-mode detection is based upon a priori theoretical knowledge. By doing so, detection becomes more restricted to what we can imagine. De facto, the universe of possibilities is made narrower. Such an approach is pertinent for Bayesian statisticians. Examples of how Bayesian inferences can be applied to spectral analysis and helioseismic power spectra are given. Our intention is not to give the full statistical framework (much too ambitious) but to provide an appetizer for going further in the direction of a proper Bayesian inference, especially for detecting gravity modes.