Comparing simulated and observed particle energy distributions through magnetic reconnection in Earth’s magnetotail
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Authors
Reisinger, N.
Bacchini, F.
Discipline
Physical sciences
Subject
acceleration of particles
magnetic reconnection
methods: numerical
Audience
Scientific
Date
2026Metadata
Show full item recordDescription
Context. Magnetic reconnection is an explosive process that accelerates particles to high energies in Earth’s magnetosphere, offering a unique natural laboratory to study this phenomenon. Aims. This study investigates how well data-driven fully kinetic simulations can reproduce the ion and electron energy distributions observed during a reconnection event by the Magnetospheric Multiscale (MMS) mission. Methods. We performed fully kinetic 2D simulations initialized with plasma parameters derived from the MMS event and compared the resulting ion and electron energy distributions with observations. Key numerical and physical parameters were systematically varied to assess their influence on the resulting particle spectra. Results. The simulations capture the overall shape and evolution of nonthermal energy distributions for both species, but generally underestimate the very high-energy tail of the electron spectrum. Variations in numerical parameters have negligible effects on the resulting spectra, while the initial upstream temperatures instead play a more pronounced role in reproducing the observed distributions. Conclusions. We present a novel analysis of data-driven fully kinetic simulations of MR, showing that key aspects of particle acceleration can be captured, while also highlighting the limitations of 2D simulations and the need for more realistic (e.g., 3D) setups to reproduce the observed particle energization accurately.
Citation
Reisinger, N.; Bacchini, F. (2026). Comparing simulated and observed particle energy distributions through magnetic reconnection in Earth’s magnetotail. , Astronomy & Astrophysics, Vol. 706, L18, DOI: 10.1051/0004-6361/202558575.Identifiers
url:
Type
Article
Peer-Review
Yes
Language
eng
