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＜電子ブック＞
Invariant Measures for Stochastic Nonlinear Schrödinger Equations : Numerical Approximations and Symplectic Structures / by Jialin Hong, Xu Wang
(Lecture Notes in Mathematics. ISSN:16179692 ; 2251)

版	1st ed. 2019.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2019
大きさ	XIV, 220 p. 14 illus., 13 illus. in color : online resource
著者標目	*Hong, Jialin author Wang, Xu author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Numerical analysis LCSH:Dynamical systems LCSH:Differential equations FREE:Probability Theory FREE:Numerical Analysis FREE:Dynamical Systems FREE:Differential Equations
一般注記	Invariant measures and ergodicity -- Invariant measures for stochastic differential equations -- Invariant measures for stochastic nonlinear Schrödinger equations -- Geometric structures and numerical schemes for nonlinear Schrödinger equations -- Numerical invariant measures for damped stochastic nonlinear Schrödinger equations -- Approximation of ergodic limit for conservative stochastic nonlinear Schrödinger equations This book provides some recent advance in the study of stochastic nonlinear Schrödinger equations and their numerical approximations, including the well-posedness, ergodicity, symplecticity and multi-symplecticity. It gives an accessible overview of the existence and uniqueness of invariant measures for stochastic differential equations, introduces geometric structures including symplecticity and (conformal) multi-symplecticity for nonlinear Schrödinger equations and their numerical approximations, and studies the properties and convergence errors of numerical methods for stochastic nonlinear Schrödinger equations. This book will appeal to researchers who are interested in numerical analysis, stochastic analysis, ergodic theory, partial differential equation theory, etc HTTP:URL=https://doi.org/10.1007/978-981-32-9069-3

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