Wave-Particle Decomposition for Kinetic Equations I: Theory and Numerics
Abstract
This paper presents a wave-particle decomposition (WPD) for kinetic relaxation equations, formulated around a local evolution timescale and its associated kinetic horizon. By leveraging the characteristic integral solution, we decompose the distribution function into an analytically accumulated wave component and a purely kinetic particle component. The latter is defined by the collisionless transport that survives beyond a prescribed local domain of influence, termed the horizon. This continuous formulation yields a unified wave-particle system valid across the entire Knudsen spectrum, comprising a source-free total conservation law, a wave equation, and a particle equation. The wave operator admits a Chapman--Enskog expansion, whose moments yield Euler and Navier--Stokes fluxes with horizon-dependent coefficients, while the particle equation governs the remaining non-equilibrium kinetic transport. At the algorithmic level, this system is discretized by a conservative macro-micro method. The total conservative variables are advanced by a finite-volume update using the sum of a Navier--Stokes gas-kinetic wave flux and a particle flux computed by either a deterministic discrete-ordinate (SN) method or a Monte Carlo representation. Unlike the global time-step splitting in the unified gas-kinetic wave-particle (UGKWP) method, the present partition is defined at the PDE level and governed by the local ratio of evolution timescale to relaxation time. The particle component is therefore a fractional kinetic population generated by the collisionless factor of the integral solution. Formal analysis establishes the asymptotic-preserving continuum limit, rarefied-regime consistency, and regime-adaptive scaling of active kinetic degrees of freedom. Numerical tests in one, two, and three dimensions validate the accuracy, multiscale capability, and efficiency of the framework.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.