We construct stochastic pseudo-symplectic methods and analyze their pseudo-symplectic orders for stochastic Hamiltonian systems with additive noises in this paper. All of these methods are explicit so that the numerical implementations become much easier than implicit methods. Through the numerical experiments, we find that these methods have desired properties in accuracy and stability as well as the preservation of the symplectic structure of the systems.
- Explicit Runge–Kutta method
- Pseudo-symplectic method
- Stochastic Hamiltonian system
ASJC Scopus subject areas
- Computer Networks and Communications
- Computational Mathematics
- Applied Mathematics