Utvidet returrett til 31. januar 2025

Symplectic Integration of Stochastic Hamiltonian Systems

Om Symplectic Integration of Stochastic Hamiltonian Systems

This book provides an accessible overview concerning the stochastic numerical methods inheriting long-time dynamical behaviours of finite and infinite-dimensional stochastic Hamiltonian systems. The long-time dynamical behaviours under study involve symplectic structure, invariants, ergodicity and invariant measure. The emphasis is placed on the systematic construction and the probabilistic superiority of stochastic symplectic methods, which preserve the geometric structure of the stochastic flow of stochastic Hamiltonian systems. The problems considered in this book are related to several fascinating research hotspots: numerical analysis, stochastic analysis, ergodic theory, stochastic ordinary and partial differential equations, and rough path theory. This book will appeal to researchers who are interested in these topics.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9789811976698
  • Bindende:
  • Paperback
  • Sider:
  • 312
  • Utgitt:
  • 22. februar 2023
  • Utgave:
  • 23001
  • Dimensjoner:
  • 155x17x235 mm.
  • Vekt:
  • 476 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 22. desember 2024
Utvidet returrett til 31. januar 2025

Beskrivelse av Symplectic Integration of Stochastic Hamiltonian Systems

This book provides an accessible overview concerning the stochastic numerical methods inheriting long-time dynamical behaviours of finite and infinite-dimensional stochastic Hamiltonian systems. The long-time dynamical behaviours under study involve symplectic structure, invariants, ergodicity and invariant measure. The emphasis is placed on the systematic construction and the probabilistic superiority of stochastic symplectic methods, which preserve the geometric structure of the stochastic flow of stochastic Hamiltonian systems.
The problems considered in this book are related to several fascinating research hotspots: numerical analysis, stochastic analysis, ergodic theory, stochastic ordinary and partial differential equations, and rough path theory. This book will appeal to researchers who are interested in these topics.

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