A separable and asymptotic-preserving dynamical low-rank method for the Vlasov–Poisson–Fokker–Planck system

We present a dynamical low-rank (DLR) method for the Vlasov–Poisson–Fokker–Planck (VPFP) system. Our main contributions are twofold: (i) a conservative spatial discretization of the Fokker–Planck operator that factors into velocity-only and space-only components, enabling efficient low-rank projection, and (ii) a time discretization within the DLR framework that properly handles stiff collisions. We propose both first-order and second-order low-rank IMEX schemes. For the first-order scheme, we prove an asymptotic-preserving (AP) property when the field fluctuation is small. Numerical experiments demonstrate accuracy, robustness, and AP property at modest ranks.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-08-03
DOI
https://doi.org/10.1051/m2an/2026047/pdf
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A separable and asymptotic-preserving dynamical low-rank method for the Vlasov–Poisson–Fokker–Planck system

Shiheng Zhang, Jingwei Hu
Springer Link (Chiba Institute of Technology)
Tensor decomposition and applications
article

A separable and asymptotic-preserving dynamical low-rank method for the Vlasov–Poisson–Fokker–Planck system

Shiheng Zhang, Jingwei Hu
article en

Abstract

We present a dynamical low-rank (DLR) method for the Vlasov–Poisson–Fokker–Planck (VPFP) system. Our main contributions are twofold: (i) a conservative spatial discretization of the Fokker–Planck operator that factors into velocity-only and space-only components, enabling efficient low-rank projection, and (ii) a time discretization within the DLR framework that properly handles stiff collisions. We propose both first-order and second-order low-rank IMEX schemes. For the first-order scheme, we prove an asymptotic-preserving (AP) property when the field fluctuation is small. Numerical experiments demonstrate accuracy, robustness, and AP property at modest ranks.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 41%
Tensor decomposition and applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.