An Evolution and Eruption of the Coronal Magnetic Field through a Data-Driven MHD Simulation

TL;DR

This paper introduces a new data-driven MHD simulation code that accurately reproduces coronal magnetic field evolution and eruptions, validated against ground-truth data from a controlled MHD simulation of sunspot-driven flux rope formation and eruption.

Contribution

The study develops and tests a zero-beta approximation data-driven MHD simulation method capable of reproducing complex coronal phenomena with high fidelity.

Findings

Successfully simulated flux rope formation and eruption

Captured twisted magnetic fields and flux rope dynamics

Validated simulation results against ground-truth data

Abstract

We present a newly developed data-driven magnetohydrodynamics (MHD) simulation code under a zero-beta approximation based on a method proposed by Hayashi et al. 2018 and 2019. Although many data-driven MHD simulations have been developed and conducted, there are not many studies on how accurately those simulations can reproduce the phenomena observed in the solar corona. In this study, we investigated the performance of our data-driven simulation quantitatively using ground-truth data. The ground-truth data was produced by an MHD simulation in which the magnetic field is twisted by the sunspot motions. A magnetic flux rope (MFR) is created by the cancellation of the magnetic flux at the polarity inversion line due to the converging flow on the sunspot, which eventually leads the eruption of the MFR. We attempted to reproduce these dynamics using the data-driven MHD simulation. The coronal magnetic fields are driven by the electric fields, which are obtained from a time-series of the photospheric magnetic field that is extracted from the ground-truth data, on the surface. As a result, the data-driven simulation could capture the subsequent MHD processes, the twisted coronal magnetic field and formation of the MFR, and also its eruption. We report these results and compare with the ground-truth data, and discuss how to improve the accuracy and optimize numerical method.