Abstract
Solar coronal seismology is based on the remote diagnostics of physical conditions in the corona of the Sun by comparison between model predictions and observations of magnetohydrodynamic wave activity. Our lack of direct access to the physical systems of interest makes information incomplete and uncertain so our conclusions are at best probabilities. Bayesian inference is increasingly being employed in the area, following a general trend in the space sciences. In this paper, we first justify the use of a Bayesian probabilistic approach to seismology diagnostics of solar coronal plasmas. Then, we report on recent results that demonstrate its feasibility and advantage in applications to coronal loops, prominences and extended regions of the corona.
Highlights
The aim of this paper is to give a rationale for the use of Bayesian methods in the study of the solar corona and to show recent applications in the area of solar coronal seismology
Bayesian analysis tools are increasingly being used in seismology of the solar corona
They led to the inference of relevant information on the structure of coronal loops or prominence plasmas, such as the magnetic field strength or the plasma density
Summary
The aim of this paper is to give a rationale for the use of Bayesian methods in the study of the solar corona and to show recent applications in the area of solar coronal seismology. The first studies (already 50 years ago) dealt with both technical problems, such as the construction of image restoration algorithms (Richardson, 1972), as well as with procedures for formalising the evaluation of astrophysical hypotheses by comparison between theoretical predictions and observational data (Sturrock, 1973) It took two more decades for the Bayesian approach to be adopted in solar physics. The first study that made use of Bayesian analysis in coronal seismology was by Arregui and Asensio Ramos (2011), who inferred coronal loop physical parameters from observed periods and damping times of their transverse oscillations. Last decade, about 25 studies in coronal seismology have made use of Bayesian techniques They deal with parameter inference, model comparison, and model averaging applications to gain information on the magnetic field and the plasma conditions in structures in the solar corona and in solar prominences.
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