collaborators

10 papers

physics.plasm-ph2026

Extending the Numerical Flow Iteration to the multi-species Vlasov-Maxwell system through Hamiltonian Splitting

Rostislav-Paul Wilhelm, Fabio Bacchini, Sebastian Schöps +3

The Numerical Flow Iteration (NuFI) method has recently been proposed as a memory-slim while accurate in phase-space method for the electro-static Vlasov--Poisson system. It stores…

math.AP2026

Well-Posedness of the Linear Regularized 13-Moment Equations Using Tensor-Valued Korn Inequalities

Peter Lewintan, Lambert Theisen, Manuel Torrilhon

In this paper, we finally prove the well-posedness of the linearized R13 moment model, which describes, e.g., rarefied gas flows. As an extension of the classical fluid equations,…

physics.comp-ph2026

Moment-preserving particle merging via non-negative least squares

Georgii Oblapenko, Manuel Torrilhon

A novel particle merging algorithm for rarefied gas dynamics simulations is proposed that can conserve arbitrary velocity and spatial moments of the particle distribution via solvi…

math.NA2026

Volume Term Adaptivity for Discontinuous Galerkin Schemes

Daniel Doehring, Jesse Chan, Hendrik Ranocha +3

We introduce the concept of volume term adaptivity for high-order discontinuous Galerkin (DG) schemes solving time-dependent partial differential equations. Termed v-adaptivity, we…

math.NA2026

Variance Reduction in the Fokker-Planck Particle Method for Rarefied Gases using Quasi-Random Numbers

Lukas Netterdon, Veronica Montanaro, Manuel Torrilhon +1

The Fokker-Planck (FP) particle method accelerates rarefied-gas simulations by replacing the binary collisions of the commonly used Direct Simulation Monte Carlo (DSMC) method with…

physics.plasm-ph2025

Simulation of multi-species kinetic instabilities with the Numerical Flow Iteration

Rostislav-Paul Wilhelm, Manuel Torrilhon

Kinetic instabilities are one of the most challenging aspects in computational plasma physics. Accurately capturing their onset and evolution requires fine resolution of the high-d…