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Invariant measures for stochastic no...

Hong, Jialin.

Invariant measures for stochastic nonlinear Schrodinger equationsnumerical approximations and symplectic structures /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Invariant measures for stochastic nonlinear Schrodinger equationsby Jialin Hong, Xu Wang.
其他題名:	numerical approximations and symplectic structures /
作者:	Hong, Jialin.
其他作者:	Wang, Xu.
出版者:	Singapore :Springer Singapore :2019.
面頁冊數:	xiv, 220 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Stochastic differential equations.
電子資源:	https://doi.org/10.1007/978-981-32-9069-3
ISBN:	9789813290693$q(electronic bk.)

Invariant measures for stochastic nonlinear Schrodinger equationsnumerical 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 ;2035..

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$q(electronic bk.)

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

185784
Stochastic differential equations.

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

Dewey Class. No.: 519.22

Invariant measures for stochastic nonlinear Schrodinger equationsnumerical approximations and symplectic structures /
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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.
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