Bayesian Coronal Seismology

TL;DR

This paper discusses the application of Bayesian analysis to solar atmospheric seismology, enabling inference of plasma and magnetic field properties from wave observations despite incomplete data.

Contribution

It introduces the Bayesian methodology for solar seismology and reviews its current applications and future potential in diagnosing solar atmospheric conditions.

Findings

Bayesian methods improve inference accuracy in solar seismology.

Application of Bayesian analysis has advanced understanding of solar plasma properties.

Future extensions could enhance diagnostic capabilities.

Abstract

In contrast to the situation in a laboratory, the study of the solar atmosphere has to be pursued without direct access to the physical conditions of interest. Information is therefore incomplete and uncertain and inference methods need to be employed to diagnose the physical conditions and processes. One of such methods, solar atmospheric seismology, makes use of observed and theoretically predicted properties of waves to infer plasma and magnetic field properties. A recent development in solar atmospheric seismology consists in the use of inversion and model comparison methods based on Bayesian analysis. In this paper, the philosophy and methodology of Bayesian analysis are first explained. Then, we provide an account of what has been achieved so far from the application of these techniques to solar atmospheric seismology and a prospect of possible future extensions.