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dc.contributor.authorDobramysl, U
dc.contributor.authorHolcman, D
dc.date.accessioned2018-06-08T12:14:13Z
dc.date.available2018-06-08T12:14:13Z
dc.date.issued2018-02-15
dc.identifier.issn0021-9991
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/276776
dc.description.abstractIs it possible to recover the position of a source from the steady-state fluxes of Brownian particles to small absorbing windows located on the boundary of a domain? To address this question, we develop a numerical procedure to avoid tracking Brownian trajectories in the entire infinite space. Instead, we generate particles near the absorbing windows, computed from the analytical expression of the exit probability. When the Brownian particles are generated by a steady-state gradient at a single point, we compute asymptotically the fluxes to small absorbing holes distributed on the boundary of half-space and on a disk in two dimensions, which agree with stochastic simulations. We also derive an expression for the splitting probability between small windows using the matched asymptotic method. Finally, when there are more than two small absorbing windows, we show how to reconstruct the position of the source from the diffusion fluxes. The present approach provides a computational first principle for the mechanism of sensing a gradient of diffusing particles, a ubiquitous problem in cell biology.
dc.format.mediumPrint
dc.languageeng
dc.publisherElsevier BV
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleMixed analytical-stochastic simulation method for the recovery of a Brownian gradient source from probability fluxes to small windows.
dc.typeArticle
prism.endingPage36
prism.publicationDate2018
prism.publicationNameJ Comput Phys
prism.startingPage22
prism.volume355
dc.identifier.doi10.17863/CAM.24068
dcterms.dateAccepted2017-10-30
rioxxterms.versionofrecord10.1016/j.jcp.2017.10.058
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-02
dc.contributor.orcidDobramysl, Ulrich [0000-0001-9363-654X]
dc.identifier.eissn1090-2716
rioxxterms.typeJournal Article/Review
pubs.funder-project-idWellcome Trust (105602/Z/14/Z)
cam.issuedOnline2017-11-10


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International