Guiding Nonlinear Force-Free Modeling Using Coronal Observations: First Results Using a Quasi Grad-Rubin Scheme

TL;DR

This paper introduces a novel algorithm that integrates coronal loop observations with photospheric magnetic data to improve nonlinear force-free magnetic field modeling in the solar corona, addressing limitations of existing methods.

Contribution

The authors develop and test a quasi Grad-Rubin scheme that incorporates coronal loop images into NLFFF extrapolations, enhancing the accuracy of coronal magnetic field models.

Findings

The method successfully models coronal magnetic fields using combined coronal and photospheric data.

It outperforms existing techniques that rely solely on photospheric boundary conditions.

The approach is validated on analytical and solar-like magnetic field models.

Abstract

Presently, many models of the coronal magnetic field rely on photospheric vector magnetograms but these data have been shown to be problematic as the sole boundary information for nonlinear force-free field (NLFFF) extrapolations. Magnetic fields in the corona manifest themselves in high-energy images (X-rays and EUV) in the shapes of coronal loops, providing an additional constraint that at present is not used due to the mathematical complications of incorporating such input into numerical models. Projection effects and the limited number of usable loops further complicate the use of coronal information. We develop and test an algorithm to use images showing coronal loops in the modeling of the solar coronal magnetic field. We first fit projected field lines with field lines of constant-\als force-free fields to approximate the three-dimensional distribution of currents in the corona along a sparse set of trajectories. We then apply a Grad-Rubin-like iterative technique to obtain a volume-filling nonlinear force-free model of the magnetic field, modifying method presented in \citet{Wheatland2007}. We thoroughly test the technique on known analytical and solar-like model magnetic fields previously used for comparing different extrapolation techniques \citep{Schrijver2006, Schrijver2008} and compare the results with those obtained by presently available methods that rely only on the photospheric data. We conclude that we have developed a functioning method of modeling the coronal magnetic field by combining the line-of-sight component of photospheric magnetic field with information from coronal images. Vector magnetograms over the full or partial photospheric boundary of the numerical domain could optionally be used.