Invariant Measures for Stochastic Nonlinear Schroedinger Equations - Numerical Approximations and Symplectic Structures (Paperback, 1st ed. 2019)

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This book provides some recent advance in the study of stochastic nonlinear Schroedinger 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 Schroedinger equations and their numerical approximations, and studies the properties and convergence errors of numerical methods for stochastic nonlinear Schroedinger 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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Product Description

This book provides some recent advance in the study of stochastic nonlinear Schroedinger 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 Schroedinger equations and their numerical approximations, and studies the properties and convergence errors of numerical methods for stochastic nonlinear Schroedinger 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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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Series

Lecture Notes in Mathematics, 2251

Release date

August 2019

Availability

Expected to ship within 10 - 15 working days

First published

2019

Authors

,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

220

Edition

1st ed. 2019

ISBN-13

978-981-3290-68-6

Barcode

9789813290686

Categories

LSN

981-3290-68-4



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