A self-consistent nonlinear force-free solution for a solar active region magnetic field

TL;DR

This paper introduces a Bayesian iterative method to reconcile boundary magnetic field data with nonlinear force-free models of solar active regions, ensuring self-consistent solutions that improve modeling accuracy.

Contribution

A novel Bayesian approach to modify boundary current data for consistent nonlinear force-free magnetic field solutions in solar active regions.

Findings

Method successfully applied to Hinode/SOT data of NOAA active region 10953.

Produces self-consistent magnetic field solutions from inconsistent boundary data.

Enhances the reliability of coronal magnetic field modeling.

Abstract

Nonlinear force-free solutions for the magnetic field in the solar corona constructed using photospheric vector magnetic field boundary data suffer from a basic problem: the observed boundary data are inconsistent with the nonlinear force-free model. Specifically, there are two possible choices of boundary conditions on vertical current provided by the data, and the two choices lead to different force-free solutions. A novel solution to this problem is described. Bayesian probability is used to modify the boundary values on current density, using field-line connectivity information from the two force-free solutions and taking into account uncertainties, so that the boundary data are more consistent with the two nonlinear force-free solutions. This procedure may be iterated until a set of self-consistent boundary data (the solutions for the two choices of boundary conditions are the same) is achieved. The approach is demonstrated to work in application to Hinode/SOT observations of NOAA active region 10953.