Strategies for particle resampling in PIC simulations

TL;DR

This paper discusses methods to efficiently manage particle numbers in PIC simulations affected by quantum electrodynamics phenomena, focusing on merging and thinning techniques to maintain sampling quality.

Contribution

It introduces and analyzes particle resampling strategies like merging and thinning to optimize PIC simulations under quantum electrodynamics effects.

Findings

Merging reduces particle count while preserving distribution accuracy.

Thinning selectively removes particles to control computational load.

Approaches are suitable for high-density particle scenarios.

Abstract

In particle-in-cell simulations, excessive or even unfeasible computational demands can be caused by the growth of the number of particles in the course of prolific ionization or cascaded pair production due to the effects of quantum electrodynamics. Here we discuss how one can organize a dynamic rearrangement of the ensemble to reduce the number of macroparticles, while maintaining acceptable sampling of an arbitrary particle distribution. The approaches of merging and thinning as well as their variants are discussed and the aspects of use are considered.