Dr Chunrong Feng chunrong.feng@durham.ac.uk
Professor
Dr Chunrong Feng chunrong.feng@durham.ac.uk
Professor
Professor Huaizhong Zhao huaizhong.zhao@durham.ac.uk
Professor
Johnny Zhong
In this paper, we derive a parabolic partial differential equation for the expected exit time of non-autonomous time-periodic non-degenerate stochastic differential equations. This establishes a Feynman–Kac duality between expected exit time of time-periodic stochastic differential equations and time-periodic solutions of parabolic partial differential equations. Casting the time-periodic solution of the parabolic partial differential equation as a fixed point problem and a convex optimisation problem, we give sufficient conditions in which the partial differential equation is well-posed in a weak and classical sense. With no known closed formulae for the expected exit time, we show our method can be readily implemented by standard numerical schemes. With relatively weak conditions (e.g. locally Lipschitz coefficients), the method in this paper is applicable to wide range of physical systems including weakly dissipative systems. Particular applications towards stochastic resonance will be discussed.
Feng, C., Zhao, H., & Zhong, J. (2021). Expected exit time for time-periodic stochastic differential equations and applications to stochastic resonance. Physica D: Nonlinear Phenomena, 417, https://doi.org/10.1016/j.physd.2020.132815
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 7, 2020 |
Online Publication Date | Dec 19, 2020 |
Publication Date | 2021-03 |
Deposit Date | Jan 5, 2021 |
Publicly Available Date | Dec 19, 2021 |
Journal | Physica D: Nonlinear Phenomena |
Print ISSN | 0167-2789 |
Electronic ISSN | 1872-8022 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 417 |
DOI | https://doi.org/10.1016/j.physd.2020.132815 |
Public URL | https://durham-repository.worktribe.com/output/1254306 |
Accepted Journal Article
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Publisher Licence URL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Copyright Statement
© 2021 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
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