Large deviations for infinite dimensional stochastic dynamical systems

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dc.creatorBudhiraja, Amarjit
dc.creatorDupuis, Paul
dc.creatorMaroulas, Vasileios
dc.date2008-08-27
dc.date.accessioned2026-07-07T09:58:40Z
dc.date.available2026-07-07T09:58:40Z
dc.descriptionThe large deviations analysis of solutions to stochastic differential equations and related processes is often based on approximation. The construction and justification of the approximations can be onerous, especially in the case where the process state is infinite dimensional. In this paper we show how such approximations can be avoided for a variety of infinite dimensional models driven by some form of Brownian noise. The approach is based on a variational representation for functionals of Brownian motion. Proofs of large deviations properties are reduced to demonstrating basic qualitative properties (existence, uniqueness and tightness) of certain perturbations of the original process.
dc.descriptionPublished in at http://dx.doi.org/10.1214/07-AOP362 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0808.3631
dc.identifierhttp://arxiv.org/abs/0808.3631
dc.identifierAnnals of Probability 2008, Vol. 36, No. 4, 1390-1420
dc.identifierdoi:10.1214/07-AOP362
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/167799
dc.subjectProbability
dc.subject60H15, 60F10 (Primary) 37L55 (Secondary)
dc.titleLarge deviations for infinite dimensional stochastic dynamical systems
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