Geometric singular perturbation theory for stochastic differential equations

dc.creatorBerglund, Nils
dc.creatorGentz, Barbara
dc.date2002-03-30
dc.date2003-06-14
dc.date.accessioned2026-07-07T04:47:21Z
dc.date.available2026-07-07T04:47:21Z
dc.descriptionWe consider slow-fast systems of differential equations, in which both the slow and fast variables are perturbed by noise. When the deterministic system admits a uniformly asymptotically stable slow manifold, we show that the sample paths of the stochastic system are concentrated in a neighbourhood of the slow manifold, which we construct explicitly. Depending on the dynamics of the reduced system, the results cover time spans which can be exponentially long in the noise intensity squared (that is, up to Kramers' time). We obtain exponentially small upper and lower bounds on the probability of exceptional paths. If the slow manifold contains bifurcation points, we show similar concentration properties for the fast variables corresponding to non-bifurcating modes. We also give conditions under which the system can be approximated by a lower-dimensional one, in which the fast variables contain only bifurcating modes.
dc.description43 pages. Published version. Remarks added, minor corrections
dc.identifierhttps://arxiv.org/abs/math/0204008
dc.identifierhttp://arxiv.org/abs/math/0204008
dc.identifierJ. Differential Equations 191:1-54 (2003)
dc.identifierdoi:10.1016/S0022-0396(03)00020-2
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/63681
dc.subjectProbability
dc.subjectDynamical Systems
dc.subject37H20, 34E15 (primary), 60H10 (secondary)
dc.titleGeometric singular perturbation theory for stochastic differential equations
dc.typetext

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