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Effective Resistivity in Collisionless Magnetic Reconnection.

Z W Ma1, T Chen2, H W Zhang2

  • 1Institute for Fusion Theory and Simulation, Department of Physics, Zhejiang University, Hangzhou, 310027, China. zwma@zju.edu.cn.

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|July 14, 2018
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Summary
This summary is machine-generated.

A new effective resistivity model for collisionless magnetic reconnection (MR) in plasma is introduced. This model, validated by particle-in-cell simulations, explains MR across diverse environments and can enhance magnetohydrodynamic simulations.

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Area of Science:

  • Plasma Physics
  • Astrophysics
  • Space Physics

Background:

  • Collisionless magnetic reconnection (MR) is a fundamental plasma process.
  • Existing models often struggle to accurately represent MR in collisionless plasmas.
  • Understanding MR is crucial for phenomena from solar flares to laboratory fusion.

Purpose of the Study:

  • To present a novel effective resistivity model for collisionless MR.
  • To validate this model using advanced simulation techniques.
  • To demonstrate its applicability across a wide range of plasma environments.

Main Methods:

  • Developing an effective resistivity based on electron pitch angle scattering in the diffusion region.
  • Utilizing collisionless particle-in-cell (PIC) simulations for validation.
  • Comparing simulation results with observational data from various astrophysical and laboratory plasmas.

Main Results:

  • An effective resistivity scaling law was derived, dependent on local plasma and magnetic field parameters.
  • PIC simulations confirmed the validity of the proposed effective resistivity.
  • The model showed excellent agreement with MR data from intergalactic to laboratory fusion plasmas.

Conclusions:

  • The derived effective resistivity provides a robust framework for understanding collisionless MR.
  • This scaling law can be integrated into existing magnetohydrodynamic codes for improved simulations.
  • The findings offer guidance for future theoretical investigations into collisionless MR processes.