Numerical simulations of fast and slow coronal mass ejections

TL;DR

This paper uses numerical simulations to demonstrate that both fast and slow coronal mass ejections can be described within a unified flux-rope model driven by torus instability, depending on the magnetic field decay rate.

Contribution

It confirms through simulations that a single flux-rope CME model can account for both fast and slow CMEs based on magnetic field decay profiles, challenging the idea of two distinct CME types.

Findings

Fast CMEs are associated with rapid magnetic field decrease.

Slow CMEs correspond to gentle magnetic field decrease.

Complex active regions produce the fastest CMEs.

Abstract

Solar coronal mass ejections (CMEs) show a large variety in their kinematic properties. CMEs originating in active regions and accompanied by strong flares are usually faster and accelerated more impulsively than CMEs associated with filament eruptions outside active regions and weak flares. It has been proposed more than two decades ago that there are two separate types of CMEs, fast (impulsive) CMEs and slow (gradual) CMEs. However, this concept may not be valid, since the large data sets acquired in recent years do not show two distinct peaks in the CME velocity distribution and reveal that both fast and slow CMEs can be accompanied by both weak and strong flares. We present numerical simulations which confirm our earlier analytical result that a flux-rope CME model permits describing fast and slow CMEs in a unified manner. We consider a force-free coronal magnetic flux rope embedded in the potential field of model bipolar and quadrupolar active regions. The eruption is driven by the torus instability which occurs if the field overlying the flux rope decreases sufficiently rapidly with height. The acceleration profile depends on the steepness of this field decrease, corresponding to fast CMEs for rapid decrease, as is typical of active regions, and to slow CMEs for gentle decrease, as is typical of the quiet Sun. Complex (quadrupolar) active regions lead to the fastest CMEs.