English

$\alpha$ Effect and Magnetic Diffusivity $\beta$ in Helical Plasma under Turbulence Growth

Plasma Physics 2025-06-27 v2 Solar and Stellar Astrophysics Space Physics

Abstract

We investigate the transport coefficients α\alpha and β\beta in plasma systems with varying Reynolds numbers while maintaining a unit magnetic Prandtl number. {The α\alpha and β\beta tensors parameterize the turbulent electromotive force (EMF) in terms of the large-scale magnetic field B{\bf \overline{B}} and current density {\bf \overline{}} as follows : u×b=αBβ×B\langle {\bf u}\times {\bf b} \rangle = \alpha {\bf \overline{B}}-\beta {\nabla\times \bf \overline{B}}.} In astrophysical plasmas, high fluid Reynolds numbers (ReRe) and magnetic Reynolds numbers (ReMRe_\mathrm{M}) drive turbulence, where ReRe governs flow dynamics and ReMRe_\mathrm{M} controls magnetic field evolution. The coefficients αsemi\alpha_{\text{semi}} and βsemi\beta_{\text{semi}} are obtained from large-scale magnetic field data as estimates of the α\alpha and β\beta tensors, while βtheo\beta_{\text{theo}} is derived from turbulent kinetic energy data. The reconstructed large-scale field B\overline{B} agrees with simulations, confirming consistency among α\alpha, β\beta, and B\overline{B} in weakly nonlinear regimes. This highlights the need to incorporate magnetic effects under strong nonlinearity. To clarify α\alpha and β\beta, we introduce a field structure model, identifying α\alpha as the electrodynamic induction effect and β\beta as the fluid-like diffusion effect. The agreement between our method and direct simulations suggests that plasma turbulence and magnetic interactions can be analyzed using fundamental physical quantities. Moreover, αsemi\alpha_{\text{semi}} and βsemi\beta_{\text{semi}}, which successfully reproduce the numerically obtained magnetic field, provide a benchmark for future theoretical studies.

Keywords

Cite

@article{arxiv.2410.19232,
  title  = {$\alpha$ Effect and Magnetic Diffusivity $\beta$ in Helical Plasma under Turbulence Growth},
  author = {Kiwan Park},
  journal= {arXiv preprint arXiv:2410.19232},
  year   = {2025}
}

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Published in Universe

R2 v1 2026-06-28T19:35:01.587Z