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dc.contributor.authorZhang, S
dc.contributor.authorChong, A
dc.contributor.authorHughes, BD
dc.date.available2020-01-16T02:03:12Z
dc.date.issued2019-10-30
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000493459700005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=d4d813f4571fa7d6246bdc0dfeca3a1c
dc.identifierARTN 042415
dc.identifier.citationZhang, S., Chong, A. & Hughes, B. D. (2019). Persistent exclusion processes: Inertia, drift, mixing, and correlation. PHYSICAL REVIEW E, 100 (4), https://doi.org/10.1103/PhysRevE.100.042415.
dc.identifier.issn2470-0045
dc.identifier.urihttp://hdl.handle.net/11343/233844
dc.description.abstractIn many biological systems, motile agents exhibit random motion with short-term directional persistence, together with crowding effects arising from spatial exclusion. We formulate and study a class of lattice-based models for multiple walkers with motion persistence and spatial exclusion in one and two dimensions, and use a mean-field approximation to investigate relevant population-level partial differential equations in the continuum limit. We show that this model of a persistent exclusion process is in general well described by a nonlinear diffusion equation. With reference to results presented in the current literature, our results reveal that the nonlinearity arises from the combination of motion persistence and volume exclusion, with linearity in terms of the canonical diffusion or heat equation being recovered in either the case of persistence without spatial exclusion, or spatial exclusion without persistence. We generalize our results to include systems of multiple species of interacting, motion-persistent walkers, as well as to incorporate a global drift in addition to persistence. These models are shown to be governed approximately by systems of nonlinear advection-diffusion equations. By comparing the prediction of the mean-field approximation to stochastic simulation results, we assess the performance of our results. Finally, we also address the problem of inferring the presence of persistence from simulation results, with a view to application to experimental cell-imaging data.
dc.languageEnglish
dc.publisherAMER PHYSICAL SOC
dc.titlePersistent exclusion processes: Inertia, drift, mixing, and correlation
dc.typeJournal Article
dc.identifier.doi10.1103/PhysRevE.100.042415
melbourne.affiliation.departmentSchool of Mathematics and Statistics
melbourne.source.titlePHYSICAL REVIEW E
melbourne.source.volume100
melbourne.source.issue4
melbourne.identifier.arcDP140100339
melbourne.elementsid1422762
melbourne.contributor.authorHughes, Barry
dc.identifier.eissn2470-0053
melbourne.identifier.fundernameidAUST RESEARCH COUNCIL, DP140100339
melbourne.accessrightsOpen Access


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