Numerical Approximations of Stochastic Maxwell Equations
via Structure-Preserving Algorithms
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Beschreibung
The stochastic Maxwell equations play an essential role in many fields, including fluctuational electrodynamics, statistical radiophysics, integrated circuits, and stochastic inverse problems.
This book provides some recent advances in the investigation of numerical approximations of the stochastic Maxwell equations via structure-preserving algorithms. It presents an accessible overview of the construction and analysis of structure-preserving algorithms with an emphasis on the preservation of geometric structures, physical properties, and asymptotic behaviors of the stochastic Maxwell equations. A friendly introduction to the simulation of the stochastic Maxwell equations with some structure-preserving algorithms is provided using MATLAB for the reader’s convenience.
The objects considered in this book are related to several fascinating mathematical fields: numerical analysis, stochastic analysis, (multi-)symplectic geometry, large deviations principle, ergodic theory, partial differential equation, probability theory, etc. This book will appeal to researchers who are interested in these topics.
The stochastic Maxwell equations play an essential role in many fields, including fluctuational electrodynamics, statistical radiophysics, integrated circuits, and stochastic inverse problems.
This book provides some recent advances in the investigation of numerical approximations of the stochastic Maxwell equations via structure-preserving algorithms. It presents an accessible overview of the construction and analysis of structure-preserving algorithms with an emphasis on the preservation of geometric structures, physical properties, and asymptotic behaviors of the stochastic Maxwell equations. A friendly introduction to the simulation of the stochastic Maxwell equations with some structure-preserving algorithms is provided using MATLAB for the reader’s convenience.
The objects considered in this book are related to several fascinating mathematical fields: numerical analysis, stochastic analysis, (multi-)symplectic geometry, large deviations principle, ergodic theory, partial differential equation, probability theory, etc. This book will appeal to researchers who are interested in these topics.
Provides the study of intrinsic properties possessed by stochastic Maxwell equations Constructs structure-preserving algorithms of stochastic Maxwell equations Presents the analysis on regularities and error estimates for the stochastic structure-preserving algorithms
Autor*in
Chuchu Chen
Themen in »Numerical Approximations of Stochastic Maxwell Equations«
Stochastic Maxwell equations Stochastic symplectic and multi-symplectic structures Stochastic energy and divergence evolution laws Invariant measure and ergodicity Large deviation principle Stochastic structure-preserving algorithms Stochastic Hamiltonian partial differential equations
Stimmen zu »Numerical Approximations of Stochastic Maxwell Equations«
“This interesting monograph brings a self-contained account of the numerical analysis of the stochastic Maxwell equations. More precisely, it includes the construction and analysis of structure-preserving algorithms with an emphasis on the preservation of geometric structures, physical properties, and asymptotic behavior of the original equations.” (Jaromír Antoch, zbMATH 1542.65001, 2024)
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