Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774207
Title: Efficient simulation of rare events in one-dimensional systems using a parallelised cloning algorithm
Author: Brewer, Tobias
ISNI:       0000 0004 7961 4151
Awarding Body: University of Bath
Current Institution: University of Bath
Date of Award: 2019
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Abstract:
We consider the population dynamics that are implemented by the cloning algorithmfor analysis of large deviations of time-averaged quantities. We consider exclusionprocesses acting on particles on one-dimensional lattices such as the simple symmetricexclusion process and the Fredkin Process. We use large deviation theoryto quantify the probabilities of rare events. To achieve this we adapt a numericalalgorithm which employs a combination of biased cloning and simulation of modi-ed dynamics. We establish its accuracy within particular regimes, determine whichcongurations are likely to produce rare events and quantify the convergence of thealgorithm with respect to algorithmic parameters. We investigate the eciency andspeed-up obtained when using dierent parallelisation techniques to implement thealgorithm which involves complex communication patterns between systems.
Supervisor: Clark, Stephen ; Jack, Robert ; Bradford, Russell Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.774207  DOI: Not available
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