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Invariant measures for stochastic no...

Hong, Jialin.

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Invariant measures for stochastic nonlinear Schrodinger equations = numerical approximations and symplectic structures /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Invariant measures for stochastic nonlinear Schrodinger equations/ by Jialin Hong, Xu Wang.
Reminder of title:	numerical approximations and symplectic structures /
Author:	Hong, Jialin.
other author:	Wang, Xu.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	xiv, 220 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Invariant measures and ergodicity -- Invariant measures for stochastic differential equations -- Invariant measures for stochastic nonlinear Schrodinger equations -- Geometric structures and numerical schemes for nonlinear Schrodinger equations -- Numerical invariant measures for damped stochastic nonlinear Schrodinger equations -- Approximation of ergodic limit for conservative stochastic nonlinear Schrodinger equations.
Contained By:	Springer Nature eBook
Subject:	Stochastic differential equations. -
Online resource:	https://doi.org/10.1007/978-981-32-9069-3
ISBN:	9789813290693

Invariant measures for stochastic nonlinear Schrodinger equations = numerical approximations and symplectic structures /
Hong, Jialin.

Invariant measures for stochastic nonlinear Schrodinger equationsnumerical approximations and symplectic structures /[electronic resource] :by Jialin Hong, Xu Wang. - Singapore :Springer Singapore :2019. - xiv, 220 p. :ill. (some col.), digital ;24 cm. - Lecture notes in mathematics,v.22510075-8434 ;. - Lecture notes in mathematics ;v.2251..

Invariant measures and ergodicity -- Invariant measures for stochastic differential equations -- Invariant measures for stochastic nonlinear Schrodinger equations -- Geometric structures and numerical schemes for nonlinear Schrodinger equations -- Numerical invariant measures for damped stochastic nonlinear Schrodinger equations -- Approximation of ergodic limit for conservative stochastic nonlinear Schrodinger equations.

This book provides some recent advance in the study of stochastic nonlinear Schrodinger 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 Schrodinger equations and their numerical approximations, and studies the properties and convergence errors of numerical methods for stochastic nonlinear Schrodinger equations. This book will appeal to researchers who are interested in numerical analysis, stochastic analysis, ergodic theory, partial differential equation theory, etc.

ISBN: 9789813290693

Standard No.: 10.1007/978-981-32-9069-3doiSubjects--Topical Terms:

621860
Stochastic differential equations.

LC Class. No.: QA274.23 / .H65 2019

Dewey Class. No.: 519.22

Invariant measures for stochastic nonlinear Schrodinger equations = numerical approximations and symplectic structures /
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245 1 0 $a Invariant measures for stochastic nonlinear Schrodinger equations $h [electronic resource] : $b numerical approximations and symplectic structures / $c by Jialin Hong, Xu Wang.
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300 $a xiv, 220 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in mathematics, $x 0075-8434 ; $v v.2251
505 0 $a Invariant measures and ergodicity -- Invariant measures for stochastic differential equations -- Invariant measures for stochastic nonlinear Schrodinger equations -- Geometric structures and numerical schemes for nonlinear Schrodinger equations -- Numerical invariant measures for damped stochastic nonlinear Schrodinger equations -- Approximation of ergodic limit for conservative stochastic nonlinear Schrodinger equations.
520 $a This book provides some recent advance in the study of stochastic nonlinear Schrodinger 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 Schrodinger equations and their numerical approximations, and studies the properties and convergence errors of numerical methods for stochastic nonlinear Schrodinger equations. This book will appeal to researchers who are interested in numerical analysis, stochastic analysis, ergodic theory, partial differential equation theory, etc.
650 0 $a Stochastic differential equations. $3 621860
650 1 4 $a Probability Theory and Stochastic Processes. $3 891080
650 2 4 $a Numerical Analysis. $3 892626
650 2 4 $a Dynamical Systems and Ergodic Theory. $3 891276
650 2 4 $a Partial Differential Equations. $3 890899
700 1 $a Wang, Xu. $3 1028898
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in mathematics ; $v v.2251. $3 3503187
856 4 0 $u https://doi.org/10.1007/978-981-32-9069-3
950 $a Mathematics and Statistics (SpringerNature-11649)