Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise

Burrage, Pamela & Burrage, Kevin (2014) Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise. Numerical Algorithms, 65(3), pp. 519-532.

View at publisher


There has been considerable recent work on the development of energy conserving one-step methods that are not symplectic. Here we extend these ideas to stochastic Hamiltonian problems with additive noise and show that there are classes of Runge-Kutta methods that are very effective in preserving the expectation of the Hamiltonian, but care has to be taken in how the Wiener increments are sampled at each timestep. Some numerical simulations illustrate the performance of these methods.

Impact and interest:

3 citations in Scopus
3 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

117 since deposited on 05 May 2014
23 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 64187
Item Type: Journal Article
Refereed: Yes
Keywords: stochastic Hamiltonian problems, Runge-Kutta methods, symplecticity
DOI: 10.1007/s11075-013-9796-6
ISSN: 1017-1398
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > NUMERICAL AND COMPUTATIONAL MATHEMATICS (010300)
Divisions: Current > Institutes > Institute for Future Environments
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Springer
Deposited On: 05 May 2014 22:54
Last Modified: 07 May 2014 08:05

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page