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＜電子ブック＞
Symplectic Integration of Stochastic Hamiltonian Systems / by Jialin Hong, Liying Sun
(Lecture Notes in Mathematics. ISSN:16179692 ; 2314)

版	1st ed. 2022.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2022
本文言語	英語
大きさ	XII, 300 p. 1 illus : online resource
著者標目	*Hong, Jialin author Sun, Liying author SpringerLink (Online service)
件　名	LCSH:Numerical analysis LCSH:Dynamical systems LCSH:Probabilities FREE:Numerical Analysis FREE:Dynamical Systems FREE:Probability Theory
一般注記	Chapter 1 Deterministic Hamiltonian System -- Chapter 2 Stochastic Hamiltonian System -- Chapter 3 Stochastic Structure Preserving Numerical Integrators -- Chapter 4 Stochastic Modified Equation and Its Applications -- Chapter 5 Stochastic Hamiltonian Partial Differential Equation This book provides an accessible overview concerning the stochastic numerical methods inheriting long-time dynamical behaviours of finite and infinite-dimensional stochastic Hamiltonian systems. The long-time dynamical behaviours under study involve symplectic structure, invariants, ergodicity and invariant measure. The emphasis is placed on the systematic construction and the probabilistic superiority of stochastic symplectic methods, which preserve the geometric structure of the stochastic flow of stochastic Hamiltonian systems. The problems considered in this book are related to several fascinating research hotspots: numerical analysis, stochastic analysis, ergodic theory, stochastic ordinary and partial differential equations, and rough path theory. This book will appeal to researchers who are interested in these topics HTTP:URL=https://doi.org/10.1007/978-981-19-7670-4

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