Scale statistics of current sheets in relativistic collisionless plasma turbulence

We analyse distributions of the spatial scales of coherent intermittent structures – current sheets – obtained from fully kinetic, two-dimensional simulations of relativistic turbulence in a collisionless pair plasma using unsupervised machine-learning data dissection. We find that the distribution functions of sheet length $\ell$ (longest scale of the analysed structure in the direction perpendicular to the dominant guide field) and curvature $r_c$ (radius of a circle fitted to the structures) can be well-approximated by power-law distributions, indicating self-similarity of the structures. The distribution for the sheet width $w$ (shortest scale of the structure) peaks at the kinetic scales and decays exponentially at larger values. The data shows little or no correlation between $w$ and $\ell$ , as expected from theoretical considerations. The typical $r_c$ depends linearly on $\ell$ , which indicates that the sheets all have a similar curvature relative to their sizes. We find a weak correlation between $r_c$ and $w$ . Our results can be used to inform realistic magnetohydrodynamic subgrid models for plasma turbulence in high-energy astrophysics.