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Positivity-preserving symplectic methods for the stochastic Lotka-Volterra predator-prey model

文献类型：期刊论文

作者Hong, Jialin1,2; Ji, Lihai3; Wang, Xu1,2; Zhang, Jingjing4
刊名BIT NUMERICAL MATHEMATICS
出版日期2021-09-06
页码28
关键词Stochastic Lotka-Volterra predator-prey model Positivity Stochastic symplecticity Structure-preserving methods Convergence order conditions
ISSN号0006-3835
DOI10.1007/s10543-021-00891-y
英文摘要In this paper, positivity-preserving symplectic numerical approximations are investigated for the 2d-dimensional stochastic Lotka-Volterra predator-preymodel driven by multiplicative noises, which plays an important role in ecosystem. The model is shown to possess both a unique positive solution and a stochastic symplectic geometric structure, and hence can be interpreted as a stochastic Hamiltonian system. To inherit the intrinsic biological characteristic of the original system, a class of stochastic Runge-Kutta methods is presented, which is proved to preserve positivity of the numerical solution and possess the discrete stochastic symplectic geometric structure as well. Uniform boundedness of both the exact solution and the numerical one are obtained, which are crucial to derive the conditions for convergence order one in the L-1(Omega)-norm. Numerical examples illustrate the stability and structure-preserving property of the proposed methods over long time.
资助项目National Natural Science Foundation of China[11601032] ; National Natural Science Foundation of China[11971458] ; National Natural Science Foundation of China[12171047]
WOS研究方向Computer Science ; Mathematics
语种英语
WOS记录号WOS:000692962500001
出版者SPRINGER
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/59245]  
专题中国科学院数学与系统科学研究院
通讯作者Wang, Xu
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
3.Inst Appl Phys & Computat Math, Beijing 100094, Peoples R China
4.East China Jiaotong Univ, Sch Sci, Nanchang 330013, Jiangxi, Peoples R China
推荐引用方式
GB/T 7714		 Hong, Jialin,Ji, Lihai,Wang, Xu,et al. Positivity-preserving symplectic methods for the stochastic Lotka-Volterra predator-prey model[J]. BIT NUMERICAL MATHEMATICS,2021:28.
APA Hong, Jialin,Ji, Lihai,Wang, Xu,&Zhang, Jingjing.(2021).Positivity-preserving symplectic methods for the stochastic Lotka-Volterra predator-prey model.BIT NUMERICAL MATHEMATICS,28.
MLA Hong, Jialin,et al."Positivity-preserving symplectic methods for the stochastic Lotka-Volterra predator-prey model".BIT NUMERICAL MATHEMATICS (2021):28.

入库方式： OAI收割

来源：数学与系统科学研究院

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