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Invariant Measures for Stochastic Nonlinear Schrodinger Equations : Numerical Approximations and Symplectic Structures - 2019 ed.

By: (Author) Jialin Hong , (Author) Xu Wang

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Ksh 8,100.00

Format: Paperback / Softback

ISBN-10: 9813290684

ISBN-13: 9789813290686

Edition: 2019 ed.

Series: Lecture Notes in Mathematics

Publisher: Springer Verlag, Singapore

Imprint: Springer Verlag, Singapore

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Aug 23rd, 2019

Print length: 220 Pages

Weight: 378 grams

Dimensions (height x width x thickness): 15.50 x 23.40 x 1.50 cms

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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.
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.

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