Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/6793
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dc.contributor.advisorBasu, Urnaen_US
dc.contributor.authorMISHRA, SEEMANTen_US
dc.date.accessioned2022-05-04T07:09:51Z-
dc.date.available2022-05-04T07:09:51Z-
dc.date.issued2022-05-
dc.identifier.citation72en_US
dc.identifier.urihttp://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/6793-
dc.description.abstractWe study the behaviour of the Symmetric Exclusion Process in the presence of a non- Markovian stochastic resetting, where the system’s configuration is reset to a step-like profile at power-law waiting times with an exponent α. We find that power-law resetting leads to a rich behaviour for the diffusive and total currents, as well as the density profile. For α < 1, we show that, in the limit of large system size L → ∞, the density profile eventually becomes uniform while the average diffusive current grows sub-linearly with time t, with an exponent that lies between 1/2 and 1. For any finite L, however, the current grows ∼ t^α at late-times t ≫ L2. We develop a perturbative approach to get the distributions of the diffusive current and explain the origins of certain peculiar ‘peaks’ in them. Furthermore, we find that the average total current grows ∼√t. Using a renewal approach, we also compute the total current distributions, which turn out to be strongly non-Gaussian and bimodal for α ≃ 1/2. For α > 1, the system relaxes to an eventual non-trivial stationary density profile, which we compute exactly. In this regime, the average diffusive current grows ∼ t. The total current, on the other hand, reaches a stationary distribution with typical non-Gaussian fluctuations and a diverging average for α ≤ 3/2, while for α > 3/2 the average total current reaches a stationary value.en_US
dc.language.isoenen_US
dc.subjectStatistical Physicsen_US
dc.subjectStochastic Resettingen_US
dc.subjectSymmetric Exclusion Processen_US
dc.subjectNon-Markovianen_US
dc.titleSymmetric Exclusion Process under Power-law Stochastic Resettingen_US
dc.typeThesisen_US
dc.type.degreeBS-MSen_US
dc.contributor.departmentDept. of Physicsen_US
dc.contributor.registration20161094en_US
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