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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.
| Autorius: | Chuchu Chen, Lihai Ji, Jialin Hong, |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2024 |
| Knygos puslapių skaičius: | 304 |
| ISBN-10: | 981996685X |
| ISBN-13: | 9789819966851 |
| Formatas: | 235 x 155 x 17 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Numerical Approximations of Stochastic Maxwell Equations: via Structure-Preserving Algorithms“
