Structure-Preserving Numerical Methods for a Class of Stochastic Poisson Systems

Structure-Preserving Numerical Methods for a Class of Stochastic Poisson Systems

Year:    2022

Author:    Yuchao Wang, Lijin Wang, Yanzhao Cao

International Journal of Numerical Analysis and Modeling, Vol. 19 (2022), Iss. 2-3 : pp. 194–219

Abstract

We propose a type of numerical methods for a class of stochastic Poisson systems with invariant energy. The proposed numerical methods preserve both the energy and the Casimir functions of the systems. In addition, we provide a new approach of constructing stochastic Poisson integrators which respect the Poisson structure and the Casimir functions of stochastic Poisson systems based on coordinate transformations on the midpoint method. Numerical tests are performed to demonstrate our theoretical analysis.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2022-IJNAM-20477

International Journal of Numerical Analysis and Modeling, Vol. 19 (2022), Iss. 2-3 : pp. 194–219

Published online:    2022-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    26

Keywords:    stochastic Poisson systems structure-preserving algorithms Poisson structure Casimir functions Poisson integrators.

Author Details

Yuchao Wang

Lijin Wang

Yanzhao Cao