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dc.contributor.authorSalins, Michaelen_US
dc.date.accessioned2019-03-06T16:41:48Z
dc.date.available2019-03-06T16:41:48Z
dc.date.issued2019-03
dc.identifier.citationMichael Salins. 2019. "Smoluchowski–Kramers approximation for the damped stochastic wave equation with multiplicative noise in any spatial dimension." Stochastics and Partial Differential Equations: Analysis and Computations, Volume 7, Issue 1, pp. 86 - 122. https://doi.org/10.1007/s40072-018-0123-z
dc.identifier.issn2194-0401
dc.identifier.issn2194-041X
dc.identifier.urihttps://hdl.handle.net/2144/34251
dc.description.abstractWe show that the solutions to the damped stochastic wave equation converge pathwise to the solution of a stochastic heat equation. This is called the Smoluchowski–Kramers approximation. Cerrai and Freidlin have previously demonstrated that this result holds in the cases where the system is exposed to additive noise in any spatial dimension or when the system is exposed to multiplicative noise and the spatial dimension is one. The current paper proves that the Smoluchowski–Kramers approximation is valid in any spatial dimension when the system is exposed to multiplicative noise.en_US
dc.format.extentp. 86 - 122en_US
dc.languageen
dc.language.isoen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofStochastics and Partial Differential Equations: Analysis and Computations
dc.subjectSmoluchowski-Kramers approximationen_US
dc.subjectStochastic wave equationen_US
dc.subjectStochastic heat equationen_US
dc.subjectStochastic partialen_US
dc.subjectDifferential equationsen_US
dc.titleSmoluchowski–Kramers approximation for the damped stochastic wave equation with multiplicative noise in any spatial dimensionen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1007/s40072-018-0123-z
pubs.elements-sourcecrossrefen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Mathematics & Statisticsen_US
pubs.publication-statusPublished onlineen_US
dc.date.online2018-07-17
dc.date.online2018-07-17
dc.date.online2018-07-17


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