Plasmoid identification and statistics in two-dimensional Harris sheet and GRMHD simulations

TL;DR

This paper introduces a new algorithm for identifying and analyzing plasmoids in magnetohydrodynamical simulations of black hole accretion disks and Harris sheets, revealing similar size distributions and higher occurrence rates in resistive GRMHD.

Contribution

The authors developed a novel plasmoid identification algorithm and applied it to both black hole accretion simulations and Harris sheets, uncovering key statistical properties and correlations.

Findings

Plasmoid size distribution follows a power-law in both simulation types.

Resistive GRMHD simulations show higher plasmoid occurrence rates than ideal MHD.

Largest plasmoids are consistent with observational assumptions.

Abstract

Magnetic reconnection is a ubiquitous phenomenon for magnetized plasmas and leads to the rapid reconfiguration of magnetic field lines. During reconnection events, plasma is heated and accelerated until the magnetic field lines enclose and capture the plasma within a circular configuration. These plasmoids could therefore observationally manifest themselves as hot spots that are associated with flaring behavior in supermassive black hole systems, such as Sagittarius A$^\ast$. We have developed a novel algorithm for identifying plasmoid structures, which incorporates watershed and custom closed contouring steps. From the identified plasmoids, we determine the plasma characteristics and energetics in magnetohydrodynamical simulations. The algorithm's performance is showcased for a high-resolution suite of axisymmetric ideal and resistive magnetohydrodynamical simulations of turbulent accretion discs surrounding a supermassive black hole. For validation purposes, we also evaluate several Harris current sheets that are well-investigated in the literature. Interestingly, we recover the characteristic power-law distribution of plasmoid sizes for both the black hole and Harris sheet simulations. This indicates that while the dynamics are vastly different, with different dominant plasma instabilities, the plasmoid creation behavior is similar. Plasmoid occurrence rates for resistive general relativistic magnetohydrodynamical simulations are significantly higher than for the ideal counterpart. Moreover, the largest identified plasmoids are consistent with sizes typically assumed for semi-analytical interpretation of observations. We recover a positive correlation between the plasmoid formation rate and a decrease in black-hole-horizon-penetrating magnetic flux. The developed algorithm has enabled an extensive quantitative analysis of plasmoid formation in black hole accretion simulations.