A Deep Dive into the Distribution Function: Understanding Phase Space Dynamics with Continuum Vlasov-Maxwell Simulations

TL;DR

This paper introduces a novel discontinuous Galerkin algorithm for solving the Vlasov-Maxwell-Fokker-Planck system, enabling high-fidelity plasma distribution function analysis while conserving physical laws.

Contribution

It presents a new, accurate, and alias-free DG-based numerical method for kinetic plasma simulations that preserves key physical properties.

Findings

The method conserves energy and entropy in simulations.

It provides detailed insights into plasma energization mechanisms.

The algorithm outperforms traditional approaches in accuracy and stability.

Abstract

In collisionless and weakly collisional plasmas, the particle distribution function is a rich tapestry of the underlying physics. However, actually leveraging the particle distribution function to understand the dynamics of a weakly collisional plasma is challenging. The equation system of relevance, the Vlasov-Maxwell-Fokker-Planck (VM-FP) system of equations, is difficult to numerically integrate, and traditional methods such as the particle-in-cell method introduce counting noise into the distribution function. In this thesis, we present a new algorithm for the discretization of VM-FP system of equations for the study of plasmas in the kinetic regime. Using the discontinuous Galerkin (DG) finite element method for the spatial discretization and a third order strong-stability preserving Runge-Kutta for the time discretization, we obtain an accurate solution for the plasma's distribution function in space and time. We both prove the numerical method retains key physical properties of the VM-FP system, such as the conservation of energy and the second law of thermodynamics, and demonstrate these properties numerically. These results are contextualized in the history of the DG method. We discuss the importance of the algorithm being alias-free, a necessary condition for deriving stable DG schemes of kinetic equations so as to retain the implicit conservation relations embedded in the particle distribution function, and the computational favorable implementation using a modal, orthonormal basis in comparison to traditional DG methods applied in computational fluid dynamics. Finally, we demonstrate how the high fidelity representation of the distribution function, combined with novel diagnostics, permits detailed analysis of the energization mechanisms in fundamental plasma processes such as collisionless shocks.