Author: Qian Xia and Valentina Zharkova at Northumbria University, Newcastle.
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Introduction
Coronal mass ejections (CMEs) are explosive solar events that involve enormous ejections of plasma and magnetic flux, which drive interplanetary dynamics. CMEs are often associated with a filament channel, in the form of a twisted flux rope or sheared arcade, that stores the required large amount of free magnetic energy. The structures can be destabilised by reconnection or by an ideal process (e.g., torus or kink instability) leading to consequent eruption.
In the magnetic breakout model [1], the energy buildup in the filament channel deforms a coronal nullpoint above the system. It forms the breakout current sheet (CS), as shown in Fig. (1). This CS eventually reconnects, removing the flux overlaying the filament channel, disrupting the force balance, and triggering the eruption onset. A generic vertical flare CS forms beneath the erupting filament and reconnects and drives explosive CME acceleration.
Observations show that a significant fraction of the total released magnetic energy is transferred to high-energy electrons and ions. Energetic electrons in flares can be observed through bremsstrahlung hard X-ray, as illustrated in Fig. (2), and gyrosynchrotron microwave emission from the solar corona and chromosphere. At the same time, a fraction of energetic particles escapes to interplanetary space as solar energetic particles that can be detected by in situ observations. The strong particle energisation during solar flares may be driven by various mechanisms associated with a magnetic reconnection process [3]. By studying particle energisation in different breakout and flare CSs occurring during a CME’s evolution, we can understand the energy release by magnetic field restructuring in these events and the energy transfer to energetic particles, and, thus, determine the properties of the high-energy particles produced.
Numerical approaches
Current computing power is unable to resolve the particle characteristic scale (e.g., proton gyroradius ~ 102 m) in an observable hydrodynamic domain (flare current sheets ~ 106m) [3]. Due to the kinetic effects of particle acceleration, many kinetic simulation codes have been developed, such as hybrid and particle-in-cell approaches. The simulation domains are simplified and restricted to the most interesting area, such as the magnetic reconnection sites or the shock fronts, targeting a single specific process. On the other hand, the test-particle approach implements passively moving particles into magnetohydrodynamic (MHD) simulations (their motion would not change the electromagnetic fields). It allows scientists to access the larger hydrodynamic scale. In this nugget, we outline recent progress with this method, which explores multiple particle acceleration regions simultaneously in a single CME eruption model.
Results and discussion
The ideal MHD code, ARMS, is adaptively refined. The non-uniform grid size becomes smaller near the discontinuities (such as current sheets, shocks) due to the steeper gradients (Fig. 3). This ultra-high-resolution code can produce fine structures, such as magnetic islands in the breakout and flare current sheets.
A large number of test particles are initialised randomly in the green regions of Fig. 4 [5]. The particle acceleration sites identified by the most accelerated particles include the single X-nullpoint, the magnetic islands, and the flare loop-top regions, which are consistent with previous localised kinetic studies. Furthermore, particle re-acceleration in different regions (the blue line in Fig. 4 (3) and (6)) is shown for the first time.
When we look at the particle distributions, we first notice that the protons and electrons are ejected from the X-nullpoint asymmetrically, consistent with the previous kinetic (particle-in-cell) results [6]. After the particles are accelerated, the flare current sheets are more efficient at accelerating particles than the breakout current sheets. What is the reason behind them? Can they contribute to different acceleration mechanisms?
To answer these questions, we adopt the particle drift equations and the fluid description of magnetic field energy changes. These analyses ignore the single-particle motions and instead, focus on the macro scale. For example, the betatron acceleration is related to the change of magnetic field strength, and the first-order Fermi acceleration is related to the shortening of magnetic field lines. The results indicate that different mechanisms dominate different acceleration sites (e.g., 1st-order Fermi acceleration is important in the magnetic islands, the compression of the magnetic field does the trick in the flare loop top, etc.). The amplitudes of the energisation terms explain the different efficiency of acceleration sources. If we look into the change of particle energy distributions, we find that the peak of the distribution starts higher than the loop top and then moves downwards to the flare loop. The transition is consistent with the hard X-ray emissions in the impulsive phase of an X8.2 (a giant explosion) flare event matching the standard CME eruption model. On the other hand, the decrease of particle acceleration efficiency in the decaying phase of the flare is accompanied by the fading of the magnetic guiding field after the impulsive phase.
The numerical studies presented have calculated particle acceleration for a “realistic” CME eruption system rather than a preassumed current sheet. The combination of MHD and test-particle simulation assists the prediction of maximum energy gains of particles in different magnetic configurations, and different phases of the flares. Our model could distinguish the different particle energization mechanisms operating on these macro-scales.
References
- [1] Antiochos, S. K., Dahlburg, R. B., & Klimchuk, J. A. 1994, ApJL, 420, L41
- [2] Karpen, J. T., Antiochos, S. K., & DeVore, C. R. 2012, ApJ, 760, 81
- [3] Zharkova, V. V., Arzner, K., Benz, A. O., et al. 2011, SSRv, 159, 357
- [4] Masson, S., Antiochos, S. K., DeVore, C.R. 2013, ApJ, 771, 82
- [5] Xia, Q., Dahlin, J. T., Zharkova, V. V., Antiochos, S. K. 2020, ApJ, 894, 2
- [6] Siversky, T. V., & Zharkova, V. V. 2009, J. Plasma Phys., 75, 619