A Hybrid Method with Deviational Particles for Spatial Inhomogeneous Plasma

TL;DR

This paper introduces a hybrid simulation method combining grid-based fluid models and particle methods for inhomogeneous plasma, improving efficiency especially near fluid regimes.

Contribution

It presents a novel hybrid approach with deviational particles and resampling techniques, enhancing simulation efficiency over existing PIC-MCC methods.

Findings

Significant efficiency improvement over PIC-MCC methods.

Effective handling of both positive and negative deviational particles.

Enhanced simulation speed near fluid regimes.

Abstract

In this work we propose a Hybrid method with Deviational Particles (HDP) for a plasma modeled by the inhomogeneous Vlasov-Poisson-Landau system. We split the distribution into a Maxwellian part evolved by a grid based fluid solver and a deviation part simulated by numerical particles. These particles, named deviational particles, could be both positive and negative. We combine the Monte Carlo method proposed in \cite{YC15}, a Particle in Cell method and a Macro-Micro decomposition method \cite{BLM08} to design an efficient hybrid method. Furthermore, coarse particles are employed to accelerate the simulation. A particle resampling technique on both deviational particles and coarse particles is also investigated and improved. The efficiency is significantly improved compared to a PIC-MCC method, especially near the fluid regime.