Stochastic acceleration by multi-island contraction during turbulent magnetic reconnection
Nicolas Bian, Eduard Kontar

TL;DR
This paper presents a stochastic model of particle acceleration during turbulent magnetic reconnection, highlighting the roles of both systematic and random compression effects in energizing particles.
Contribution
It introduces a combined first and second-order Fermi acceleration model that accounts for statistical fluctuations in compression rates during multi-island reconnection.
Findings
Second-order stochastic acceleration can dominate systematic acceleration when compression rate variance is large.
The model explains features observed in numerical simulations of particle energization.
Both Eulerian and Lagrangian properties influence acceleration efficiency.
Abstract
The acceleration of charged particles in magnetized plasmas is considered during turbulent multi-island magnetic reconnection. The particle acceleration model is constructed for an ensemble of islands which produce adiabatic compression of the particles. The model takes into account the statistical fluctuations in the compression rate experienced by the particles during their transport in the acceleration region. The evolution of the particle distribution function is described as a simultaneous first and second-order Fermi acceleration process. While the efficiency of the first-order process is controlled by the average rate of compression, the second order process involves the variance in the compression rate. Moreover, the acceleration efficiency associated with the second-order process involves both the Eulerian properties of the compression field and the Lagrangian properties of the…
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