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Stochastic Poisson integrators based on Padé approximations for linear stochastic Poisson systems

  • WANG Pengjun ,
  • WANG Lijin
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  • School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2019-04-04

  Revised date: 2019-07-26

  Online published: 2021-03-15

Supported by

Supported by the National Natural Science Foundation of China (11471310,11071251)

Abstract

We propose a class of stochastic Poisson integrators based on Padé approximations for linear stochastic Poisson systems. The root mean-square convergence orders of the schemes are analyzed, and the structure preserving properties are investigated. Numerical tests are performed to verify the theoretical results and illustrate the numerical behavior of the proposed methods.

Cite this article

WANG Pengjun , WANG Lijin . Stochastic Poisson integrators based on Padé approximations for linear stochastic Poisson systems[J]. Journal of University of Chinese Academy of Sciences, 2021 , 38(2) : 160 -170 . DOI: 10.7523/j.issn.2095-6134.2021.02.002

References

[1] Hong J L, Ruan J L, Sun L Y, et al. Structure-preserving numerical methods for stochastic Poisson systems[J]. Communications in Computational Physics, 2021,29(3):802-830.
[2] Milstein G N, Repin Y M, Tretyakov M V. Symplectic integration of Hamiltonian systems with additive noise[J]. SIAM Journal on Numerical Analysis, 2002,39(6):2066-2088.
[3] Milstein G N, Repin Y M, Tretyakov M V. Numerical methods for stochastic systems preserving symplectic structure[J]. SIAM Journal on Numerical Analysis, 2002, 40(4):1583-1604.
[4] Ruan J L, Wang L J. A Lie algebraic approach for a class of highly oscillatory stochastic Hamiltonian systems[J]. Journal of University of Chinese Academy of Sciences, 2019,36(1):5-10.
[5] Feng K, Qin M Z. Symplectic geometric algorithms for Hamiltonian systems[M]. Berlin:Springer Science & Business Media, 2010.
[6] Hairer E, Lubich C, Wanner G. Geometric numerical integration[M]. Berlin:Springer Science & Business Media, 2006.
[7] Zhu W J, Qin M Z. Poisson schemes for Hamiltonian systems on Poisson manifolds[J]. Computers & Mathematics with Applications, 1994, 27(12):7-16.
[8] Cohen D, Dujardin G. Energy-preserving integrators for stochastic Poisson systems[J]. Communications in Mathematical Sciences, 2014, 12(8):1523-1539.
[9] Hong J L, Ji L H, Wang X. Stochastic K-symplectic integrators for stochastic non-canonical Hamiltonian systems and applications to the Lotka-Volterra model[EB/OL]. arXiv:1711.03258v1[math.NA] (2017-11-09)[2019-07-02]. https://arxiv.org/abs/1711.03258.
[10] Feng K, Wu H M, Qin M Z. Symplectic difference schemes for linear Hamiltonian canonical systems[J]. Journal of Computational Mathematics, 1990, 8(4):371-380.
[11] Sun L Y, Wang L J. Stochastic symplectic methods based on the Padé approximations for linear stochastic Hamiltonian systems[J]. Journal of Computational and Applied Mathematics, 2017, 311:439-456.
[12] Aboanber A E, Nahla A A. On Padé approximations to the exponential function and application to the point kinetics equations[J]. Progress in Nuclear Energy, 2004, 44(4):347-368.
[13] Milstein G N. Numerical integration of stochastic differential equations[M]. Berlin:Springer Science & Business Media, 1995.
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