Time series path integral expansions for stochastic processes

Greenman, Chris D. (2022) Time series path integral expansions for stochastic processes. Journal of Statistical Physics, 187 (3). ISSN 0022-4715

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A form of time series path integral expansion is provided that enables both analytic and numerical temporal effect calculations for a range of stochastic processes. All methods rely on finding a suitable reproducing kernel associated with an underlying representative algebra to perform the expansion. Birth–death processes can be analysed with these techniques, using either standard Doi-Peliti coherent states, or the su(1 , 1) Lie algebra. These result in simplest expansions for processes with linear or quadratic rates, respectively. The techniques are also adapted to diffusion processes. The resulting series differ from those found in standard Dyson time series field theory techniques.

Item Type: Article
Uncontrolled Keywords: birth–death process,doi peliti,path integral,time series expansion,statistical and nonlinear physics,mathematical physics ,/dk/atira/pure/subjectarea/asjc/3100/3109
Faculty \ School: Faculty of Science > School of Computing Sciences
Faculty of Science > School of Natural Sciences
UEA Research Groups: Faculty of Science > Research Groups > Computational Biology
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 24 Mar 2022 14:37
Last Modified: 21 Apr 2023 01:28
URI: https://ueaeprints.uea.ac.uk/id/eprint/84258
DOI: 10.1007/s10955-022-02912-8


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