Towards a Quantitative Comparison of Magnetic Field Extrapolations and Observed Coronal Loops

TL;DR

This study systematically compares different magnetic field extrapolation methods against observed coronal loops, finding NLFF models generally perform better than potential models, with small differences among the NLFF approaches.

Contribution

It provides a quantitative assessment of how well various magnetic field extrapolation techniques match observed coronal loops using a large dataset.

Findings

NLFF models outperform potential models in matching loops

Typical misalignment angles are 5-12 degrees

Distance metrics are around 1-2 arcseconds

Abstract

It is widely believed that loops observed in the solar atmosphere trace out magnetic field lines. However, the degree to which magnetic field extrapolations yield field lines that actually do follow loops has yet to be studied systematically. In this paper we apply three different extrapolation techniques - a simple potential model, a NLFF model based on photospheric vector data, and a NLFF model based on forward fitting magnetic sources with vertical currents - to 15 active regions that span a wide range of magnetic conditions. We use a distance metric to assess how well each of these models is able to match field lines to the 12,202 loops traced in coronal images. These distances are typically 1-2". We also compute the misalignment angle between each traced loop and the local magnetic field vector, and find values of 5-12$^\circ$. We find that the NLFF models generally outperform the potential extrapolation on these metrics, although the differences between the different extrapolations are relatively small. The methodology that we employ for this study suggests a number of ways that both the extrapolations and loop identification can be improved.