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Nonlinear Equilibrium Structure of Super Thin Current Sheets: Influence of Quasi-Adiabatic Electron Population

JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS. 2023. Vol. 128. No. 6. Article e2023JA031459.
Tsareva O., Leonenko M., Grigorenko E., Malova H., Victor Yu. Popov, Zelenyi L.

Recent MMS observations confirmed the existence of the quasi-stationary electron-scale super-thin current sheets (STCSs) with a half-thickness of few electron gyroradii. STCSs contain the electronpopulation consisting of magnetized and demagnetized particles. To study the role of the demagnetized electrons, we developed a self-consistent combined model of a STCS in which the dynamics of a part of the electron population is described by the quasi-adiabatic approximation, while the motion of the other part is described by the guiding center approximation. Demagnetized ion population can be described in a frame of quasi-adiabatic approach. In the presented model we introduced the weight coefficient of the demagnetized electron plasma density χ depending on the magnetic field normal component Bn/B0 andcompared the characteristic profiles of two STCSs differing by the presence (χ ≠ 0) and absence (χ = 0) of demagnetized electrons. It is shown that the presence of demagnetized electrons makes the current density profile of STCS significantly more intense and narrower. The thickness and intensity of STCS depend on the anisotropy coefficient of magnetized electrons and the incoming drift velocity of demagnetized electrons. The maximum current density continuously increases with the growth of the demagnetized electron population andis controlled by the ratio of the thermal to the incoming drift electron velocities. Thus intense current sheets can be formed even in the absence of strong electron anisotropy, which is confirmed by MMS observations.

Research target: Computer Science Mathematics Physics
Language: English
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Keywords: Current SheetsDemagnetized electronsNonlinear Equilibrium Structure
Publication based on the results of:
Critical phenomena in complex systems: analysis, modeling, detection, forecasting (2023)
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