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Rare event simulation for stochastic dynamics in continuous time

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Angeli, Letizia, Grosskinsky, Stefan, Johansen, Adam M. and Pizzoferrato, Andrea (2019) Rare event simulation for stochastic dynamics in continuous time. Journal of Statistical Physics, 176 . pp. 1185-1210. doi:10.1007/s10955-019-02340-1 ISSN 0022-4715.

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Official URL: https://doi.org/10.1007/s10955-019-02340-1

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Abstract

Large deviations for additive path functionals of stochastic dynamics and related numerical approaches have attracted significant recent research interest. We focus on the question of convergence properties for cloning algorithms in continuous time, and establish connections to the literature of particle filters and sequential Monte Carlo methods. This enables us to derive rigorous convergence bounds for cloning algorithms which we report in this paper, with details of proofs given in a further publication. The tilted generator characterizing the large deviation rate function can be associated to non-linear processes which give rise to several representations of the dynamics and additional freedom for associated numerical approximations. We discuss these choices in detail, and combine insights from the filtering literature and cloning algorithms to compare different approaches and improve efficiency.

Item Type: Journal Article
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Faculty of Science, Engineering and Medicine > Science > Mathematics
Journal or Publication Title: Journal of Statistical Physics
Publisher: Springer New York LLC
ISSN: 0022-4715
Official Date: September 2019
Dates:
DateEvent
September 2019Published
18 June 2019Available
11 June 2019Accepted
Volume: 176
Page Range: pp. 1185-1210
DOI: 10.1007/s10955-019-02340-1
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 12 June 2019
Date of first compliant Open Access: 3 July 2019
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDAlan Turing Institutehttp://dx.doi.org/10.13039/100012338
EP/N510129/1 EPSRCUNSPECIFIED
UNSPECIFIEDLloyds Register Foundation Programme UNSPECIFIED
GNFM-INdAMNational Group of Mathematical Physics UNSPECIFIED
UNSPECIFIEDData Science Institute UNSPECIFIED
4500902397-3408Thomson-Reuters UNSPECIFIED
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