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Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures

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...

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Detalles Bibliográficos
Autores principales: Hong, Jialin, Wang, Xu
Lenguaje:eng
Publicado: Springer 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-32-9069-3
http://cds.cern.ch/record/2691356
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author Hong, Jialin
Wang, Xu
author_facet Hong, Jialin
Wang, Xu
author_sort Hong, Jialin
collection CERN
description 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.
id cern-2691356
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
publisher Springer
record_format invenio
spelling cern-26913562021-04-21T18:19:27Zdoi:10.1007/978-981-32-9069-3http://cds.cern.ch/record/2691356engHong, JialinWang, XuInvariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structuresMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:26913562019
spellingShingle Mathematical Physics and Mathematics
Hong, Jialin
Wang, Xu
Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures
title Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures
title_full Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures
title_fullStr Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures
title_full_unstemmed Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures
title_short Invariant measures for stochastic nonlinear Schrödinger equations: numerical approximations and symplectic structures
title_sort invariant measures for stochastic nonlinear schrödinger equations: numerical approximations and symplectic structures
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-981-32-9069-3
http://cds.cern.ch/record/2691356
work_keys_str_mv AT hongjialin invariantmeasuresforstochasticnonlinearschrodingerequationsnumericalapproximationsandsymplecticstructures
AT wangxu invariantmeasuresforstochasticnonlinearschrodingerequationsnumericalapproximationsandsymplecticstructures