Work

Symplectic model reduction methods for the Vlasov equation

Year: 2022

Type: article

Abstract: Particle‐based simulations of the Vlasov equation typically require a large number of particles, which leads to a high‐dimensional system of ordinary differential equations. Solving such systems is computationally very expensive, especially when simulations for many different values of input parameters are desired. In this work, we compare several model reduction techniques and demonstrate their applicability to numerical simulations of the Vlasov equation. The necessity of symplectic model reduction algorithms is illustrated with a simple numerical experiment.

Source: Contributions to Plasma Physics

DOI: 10.1002/ctpp.202200046

Authors: Tomasz M. Tyranowski, Michael Kraus

Institutions: Max Planck Society, Max Planck Institute for Plasma Physics, Technical University of Munich

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,350

Funder: Helmholtz-Gemeinschaft