From Galactic Clusters to Plasmas in a Single Monte Carlo: Branching Paths Statistics for Poisson-Vlasov/Boltzmann

TL;DR

This paper introduces new probabilistic path-space representations and branching Monte Carlo algorithms for Poisson-Vlasov and Poisson-Boltzmann systems, enabling efficient simulations of plasmas and gravitational clusters.

Contribution

It presents novel propagator representations and branching backward Monte Carlo algorithms for mesoscopic plasma and gravitational systems.

Findings

Benchmarking on gravitational clusters demonstrates accuracy.

New algorithms improve simulation efficiency.

Path-space representations facilitate complex plasma modeling.

Abstract

Recent advances have allowed to tackle path-space probabilistic representations of mesoscopic Boltzmann transport nonlinearly coupled to a sub-model of the force-field by step forward approaches in terms of continuous branching stochastic processes. In this work, path-space probabilistic representations of free-space Poisson-Vlasov and Poisson-Boltzmann systems are exhibited. This yields novel propagator representations and opens new routes for efficient and reference simulations by use of new branching backward Monte Carlo algorithms. Subsequent statistical estimator are benchmarked on gravitational clusters and plasmas dynamics.