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Journal article
Regimes of ion dynamics in current sheets: The machine learning approach
Physical review. E, v 106(6-2), 065205
01 Dec 2022
PMID: 36671165
Abstract
Current sheets are spatially localized almost-one-dimensional (1D) structures with intense plasma currents. They play a key role in storing the magnetic field energy and they separate different plasma populations in planetary magnetospheres, the solar wind, and the solar corona. Current sheets are primary regions for the magnetic field line reconnection responsible for plasma heating and charged particle acceleration. One of the most interesting and widely observed types of 1D current sheets is the rotational discontinuity, which can be force-free or include plasma compression. Theoretical models of such 1D current sheets are based on the assumption of adiabatic motion of ions, i.e., ion adiabatic invariants are conserved. We focus on three current sheet configurations, widely observed in the Earth magnetopause and magnetotail and in the near-Earth solar wind. The magnetic field in such current sheets is supported by currents carried by transient ions, which exist only when there is a sufficient number of invariants. In this paper, we apply a machine learning approach, AI Poincaré, to determine parametrical domains where adiabatic invariants are conserved. For all three current sheet configurations, these domains are quite narrow and do not cover the entire parametrical range of observed current sheets. We discuss possible interpretation of obtained results indicating that 1D current sheets are dynamical rather than static plasma equilibria.
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Details
- Title
- Regimes of ion dynamics in current sheets: The machine learning approach
- Creators
- A S Lukin - Faculty of Physics, National Research University Higher School of Economics, Moscow 101000, RussiaA V Artemyev - Space Research InstituteD L Vainchtein - Drexel University, C. and J. Nyheim Plasma InstituteA A Petrukovich - Space Research Institute
- Publication Details
- Physical review. E, v 106(6-2), 065205
- Publisher
- Cold Spring Harbor Press
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- C. and J. Nyheim Plasma Institute
- Web of Science ID
- WOS:000905291900001
- Scopus ID
- 2-s2.0-85145435322
- Other Identifier
- 991021861195704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Physics, Fluids & Plasmas
- Physics, Mathematical