A Sampling-Based Adaptive Rank Approach to the Wigner-Poisson System
Andrew Christlieb, Sining Gong, Jing-Mei Qiu, Nanyi Zheng

TL;DR
This paper introduces a mass-conserving, adaptive-rank solver for the 1D1V Wigner-Poisson system, enabling efficient high-dimensional quantum plasma simulations relevant to inertial confinement fusion.
Contribution
It develops a novel adaptive-rank semi-Lagrangian solver with structure preservation and $O(N)$ complexity for the Wigner-Poisson system, improving computational efficiency and accuracy.
Findings
Low rank structure observed for moderate to high Planck constants.
Adaptive-rank solver matches full-rank solutions visually and quantitatively.
Achieves mass conservation and momentum accuracy with reduced computational cost.
Abstract
We develop a mass-conserving, adaptive-rank solver for the 1D1V Wigner-Poisson system. Our work is motivated by applications to the study of the stopping power of particles at the National Ignition Facility (NIF). In this regime, electrons are in a warm dense state, requiring more than a standard kinetic model. They are hot enough to neglect Pauli exclusion, yet quantum enough to require accounting for uncertainty. The Wigner-Poisson system captures these effects but presents challenges due to its nonlocal nature. Based on a second-order Strang splitting method, we first design a full-rank solver with a structure-preserving Fourier update that ensures the intermediate solutions remain real-valued (up to machine precision), improving upon previous methods. Simulations demonstrate that the solutions exhibit a low rank structure for moderate to high dimensionless Planck constants…
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Taxonomy
TopicsStochastic processes and financial applications
