Relativistic Magnetic Reconnection in Astrophysical Plasmas: A Powerful Mechanism of Nonthermal Emission

TL;DR

This review discusses recent advances in understanding relativistic magnetic reconnection in astrophysical plasmas, highlighting its role in nonthermal particle acceleration and high-energy emissions near compact objects.

Contribution

It summarizes recent kinetic simulation results, explores radiative reconnection physics, and connects reconnection processes to global high-energy astrophysical phenomena.

Findings

Kinetic simulations elucidate plasma heating and nonthermal acceleration.

Radiative reconnection involves complex photon-particle interactions.

Relativistic reconnection influences large-scale astrophysical high-energy sources.

Abstract

Magnetic reconnection -- a fundamental plasma physics process, where magnetic field lines of opposite polarity annihilate -- is invoked in astrophysical plasmas as a powerful mechanism of nonthermal particle acceleration, able to explain fast-evolving, bright high-energy flares. Near black holes and neutron stars, reconnection occurs in the ``relativistic'' regime, in which the mean magnetic energy per particle exceeds the rest mass energy. This review reports recent advances in our understanding of the kinetic physics of relativistic reconnection: (1) Kinetic simulations have elucidated the physics of plasma heating and nonthermal particle acceleration in relativistic reconnection; (2) The physics of radiative relativistic reconnection, with its self-consistent interplay between photons and reconnection-accelerated particles -- a peculiarity of luminous, high-energy astrophysical sources -- is the new frontier of research; (3) Relativistic reconnection plays a key role in global models of high-energy sources, both in terms of global-scale layers, as well as of reconnection sites generated as a byproduct of local magnetohydrodynamic instabilities. We summarize themes of active investigation and future directions, emphasizing the role of upcoming observational capabilities, laboratory experiments, and new computational tools.