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<p>Astrophysical plasmas ubiquitously exhibit turbulent behavior, underpinning the conversion of large-scale mechanical and magnetic energies into heat across an extensive range of scales. This review critically examines the mechanisms underlying turbulent energy dissipation in magnetohydrodynamic (MHD) systems, with special emphasis on the enigmatic heating of the solar corona. We synthesize and evaluate classical phenomenological frameworks, such as the Iroshnikov–Kraichnan extension of Kolmogorov’s turbulence theory and contrast these with modern theories of strong turbulence as articulated in Goldreich–Sridhar’s critical balance model. The discussion extends to incorporate contemporary insights into the roles of dynamic alignment and intermittency, which serve to refine energy cascade descriptions in both incompressible (IMHD) and compressible (CMHD) regimes. The multifaceted effects of compressibility, including shock dynamics and mode decomposition, are also discussed, especially in the context of solar coronal heating where density variations cannot be neglected. Finally, emerging methodologies such as physics-informed neural networks (PINNs) are reviewed for their potential to integrate data-driven modeling with fundamental plasma theory. This comprehensive account not only reconciles diverse theoretical perspectives but also highlights unresolved challenges, thereby charting a course for future research into the turbulent processes that govern energy conversion in astrophysical environments.</p>

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A Critical Review on Turbulent Energy Dissipation Mechanism in Solar Corona to Astrophysical Systems and a Physics-Informed Neural Network Approach

  • 期刊论文

  • 发表日期：

    2025年12月8日

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  • Bivek Pradhan,
  • Utpal Deka,
  • Gobinda Chandra Mishra

摘要

Astrophysical plasmas ubiquitously exhibit turbulent behavior, underpinning the conversion of large-scale mechanical and magnetic energies into heat across an extensive range of scales. This review critically examines the mechanisms underlying turbulent energy dissipation in magnetohydrodynamic (MHD) systems, with special emphasis on the enigmatic heating of the solar corona. We synthesize and evaluate classical phenomenological frameworks, such as the Iroshnikov–Kraichnan extension of Kolmogorov’s turbulence theory and contrast these with modern theories of strong turbulence as articulated in Goldreich–Sridhar’s critical balance model. The discussion extends to incorporate contemporary insights into the roles of dynamic alignment and intermittency, which serve to refine energy cascade descriptions in both incompressible (IMHD) and compressible (CMHD) regimes. The multifaceted effects of compressibility, including shock dynamics and mode decomposition, are also discussed, especially in the context of solar coronal heating where density variations cannot be neglected. Finally, emerging methodologies such as physics-informed neural networks (PINNs) are reviewed for their potential to integrate data-driven modeling with fundamental plasma theory. This comprehensive account not only reconciles diverse theoretical perspectives but also highlights unresolved challenges, thereby charting a course for future research into the turbulent processes that govern energy conversion in astrophysical environments.