Please use this identifier to cite or link to this item: http://hdl.handle.net/2289/6365
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dc.contributor.authorSabhapandit, Sanjib-
dc.contributor.authorDhar, Abhishek-
dc.date.accessioned2015-12-21T13:27:13Z-
dc.date.available2015-12-21T13:27:13Z-
dc.date.issued2015-07-
dc.identifier.citationJournal of Statistical Mechanics: Theory and Experiment, 2015, P07024en_US
dc.identifier.issn1742-5468 (Online)-
dc.identifier.urihttp://hdl.handle.net/2289/6365-
dc.descriptionRestricted Access. An open-access version is available at arXiv.org (one of the alternative locations)en_US
dc.description.abstractWe consider a gas of point particles moving on the one-dimensional line with a hard-core inter-particle interaction that prevents particle crossings—this is usually referred to as single-file motion. The individual particle dynamics can be arbitrary and they only interact when they meet. Starting from initial conditions such that particles are uniformly distributed, we observe the displacement of a tagged particle at time t, with respect to the initial position of another tagged particle, such that their tags differ by r. For r   =   0, this is the usual well studied problem of the tagged particle motion. Using a mapping to a non-interacting particle system we compute the exact probability distribution function for the two-tagged particle displacement, for general single particle dynamics. As by-products, we compute the large deviation function, various cumulants and, for the case of Hamiltonian dynamics, the two-particle velocity auto-correlation function.en_US
dc.language.isoenen_US
dc.publisherIOP Publishing for SISSAen_US
dc.relation.urihttp://arxiv.org/abs/1506.01824en_US
dc.relation.urihttp://dx.doi.org/10.1088/1742-5468/2015/07/P07024en_US
dc.relation.urihttp://adsabs.harvard.edu/abs/2015JSMTE..07..024Sen_US
dc.rights2015 IOP Publishing and SISSA Medialab srlen_US
dc.titleExact probability distribution for the two-tag displacement in single-file motionen_US
dc.typeArticleen_US
Appears in Collections:Research Papers (TP)

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