Regimes of charged particle dynamics in current sheets: the machine learning approach

TL;DR

This paper uses machine learning to identify the parameter ranges where adiabatic invariants are conserved in current sheets, revealing their dynamic nature rather than static equilibrium.

Contribution

It introduces a novel machine learning method, AI Poincaré, to analyze the conservation of invariants in current sheets across different configurations.

Findings

Conservation domains are narrow and do not cover all observed current sheets.

Current sheets are likely dynamic rather than static plasma equilibria.

Machine learning effectively identifies invariant conservation regions.

Abstract

Current sheets are spatially localized almost-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 type of 1D current sheets is the rotational discontinuity, that 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. 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 novel machine learning approach, AI Poincar'e, 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.