Geometric Integrators for Differential Equations with Highly Oscillatory Solutions
Sep 2021 · Springer Nature
Ebook
499
Pages
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About this ebook
The idea of structure-preserving algorithms appeared in the 1980's. The new paradigm brought many innovative changes. The new paradigm wanted to identify the long-time behaviour of the solutions or the existence of conservation laws or some other qualitative feature of the dynamics. Another area that has kept growing in importance within Geometric Numerical Integration is the study of highly-oscillatory problems: problems where the solutions are periodic or quasiperiodic and have to be studied in time intervals that include an extremely large number of periods. As is known, these equations cannot be solved efficiently using conventional methods. A further study of novel geometric integrators has become increasingly important in recent years. The objective of this monograph is to explore further geometric integrators for highly oscillatory problems that can be formulated as systems of ordinary and partial differential equations.
Facing challenging scientific computational problems, this book presents some new perspectives of the subject matter based on theoretical derivations and mathematical analysis, and provides high-performance numerical simulations. In order to show the long-time numerical behaviour of the simulation, all the integrators presented in this monograph have been tested and verified on highly oscillatory systems from a wide range of applications in the field of science and engineering. They are more efficient than existing schemes in the literature for differential equations that have highly oscillatory solutions.
This book is useful to researchers, teachers, students and engineers who are interested in Geometric Integrators and their long-time behaviour analysis for differential equations with highly oscillatory solutions.
Facing challenging scientific computational problems, this book presents some new perspectives of the subject matter based on theoretical derivations and mathematical analysis, and provides high-performance numerical simulations. In order to show the long-time numerical behaviour of the simulation, all the integrators presented in this monograph have been tested and verified on highly oscillatory systems from a wide range of applications in the field of science and engineering. They are more efficient than existing schemes in the literature for differential equations that have highly oscillatory solutions.
This book is useful to researchers, teachers, students and engineers who are interested in Geometric Integrators and their long-time behaviour analysis for differential equations with highly oscillatory solutions.
About the author
Xinyuan Wu, a Professor in Department of Mathematics, Nanjing University. His research interests focus on geometric algorithms for differential equations, numerical methods for stiff problems and numerical methods for algebraic systems. In 2017, Wu was awarded with the highest distinction of “Honorary Fellowship” from European Society of Computational Methods in Science and Engineering for the outstanding contribution in the fields of Numerical Analysis and Applied Mathematics. Wu attended the school of Mathematics at the University of Tübingen for study and research from Janurary 19th 2002 to Janurary 20th 2003.
Bin Wang, a Professor in Department of Mathematics and Statistics, Xi'an Jiaotong University. His research interests focus on various structure-preserving algorithms as well as numerical methods for differential equation, especially the numerical computation and analysis of Hamilton ordinary differential equation and partial differential equation. Wang was awarded by Alexander von Humboldt Foundation (2017–2019).
Bin Wang, a Professor in Department of Mathematics and Statistics, Xi'an Jiaotong University. His research interests focus on various structure-preserving algorithms as well as numerical methods for differential equation, especially the numerical computation and analysis of Hamilton ordinary differential equation and partial differential equation. Wang was awarded by Alexander von Humboldt Foundation (2017–2019).
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