Energy Conversion and Particle Acceleration in 3D Solar Flare Simulations

ORAL · Invited

Abstract

Recent observations and simulations indicate that solar flares undergo complex 3D evolution, making 3D particle transport models essential for understanding particle acceleration and interpreting flare emissions. Here, we investigate energy conversion and particle acceleration in solar flares using 3D MHD simulations coupled with energetic-particle transport models. The analysis identifies key acceleration regions—including the reconnection current sheet, termination shock, and supra-arcade downflows—as sources of turbulence and nonthermal particle production. Electrons and protons are efficiently accelerated to high energies, forming power-law spectra and exhibiting spatial distributions consistent with recent hard X-ray (HXR) and microwave (MW) observations. By selectively turning particle acceleration on or off in specific regions in controlled simulations, we find that different mechanisms work synergistically to produce a large population of accelerated particles. Our model produces time-dependent particle distributions in the flare region and at footpoints, enabling synthetic emission modeling to compare with observations and improve understanding of particle acceleration in 3D solar flare regions.

Publication: Energy Conversion and Electron Acceleration and Transport in 3D Simulations of Solar Flares, submitted to The Astrophysical Journal.

Presenters

  • Xiaocan Li

    Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)

Authors

  • Xiaocan Li

    Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)

  • Chengcai Shen

    Harvard-Smithsonian Center for Astrophysics

  • Xiaoyan Xie

    Harvard-Smithsonian Center for Astrophysics

  • Fan Guo

    Los Alamos National Laboratory (LANL)

  • Bin Chen

    New Jersey Institute of Technology

  • Ivan Oparin

    New Jersey Institute of Technology

  • Yuqian Wei

    New Jersey Institute of Technology

  • Sijie Yu

    New Jersey Institute of Technology

  • Jeongbhin Seo

    Los Alamos National Laboratory