Rare Events and Exit Problems for Stochastic Equations: Theory and Numerics

dc.contributor.advisorCerrai, Sandraen_US
dc.contributor.advisorCameron, Mariaen_US
dc.contributor.authorPaskal, Nicholasen_US
dc.contributor.departmentApplied Mathematics and Scientific Computationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2021-09-17T05:35:08Z
dc.date.available2021-09-17T05:35:08Z
dc.date.issued2021en_US
dc.description.abstractThis dissertation is concerned with the small-noise asymptotics of stochastic differential equations and stochastic partial differential equations. In the first part of the manuscript, we present an overview of large deviations theory in the context of stochastic differential equations, with a particular focus on describing the long time behavior of the system in the presence of point attractors. We then present results describing a novel algorithm for computing the \textit{quasi-potential}, a key quantity in large deviations theory, for two-dimensional stochastic differential equations. Our solver, the Efficient Jet Marcher, computes the quasi-potential $U(x)$ on a mesh by propagating $U$ and $\nabla U$ outward away from the attractor. By using higher-order interpolation schemes and approximations for the minimum action paths, we are able to achieve 2nd order accuracy in the mesh spacing $h$. In the second part of the manuscript, we consider two important problems in large deviations theory for stochastic partial differentiable equations. First, we consider stochastic reaction-diffusion equations posed on a bounded domain, which contain both a large diffusion term and a small noise term. We prove that in the joint small noise and large diffusion limits, the system satisfies a large deviations principle with respect to an action functional that is finite only on paths that are constant in the spatial variable. We then use this result to compute asymptotics of the first exit time of the solution from bounded domains in function spaces. Second, we consider the two-dimensional stochastic Navier-Stokes equations posed on the torus. In the simultaneous limit as the noise magnitude and noise regularization are both sent to $0$, the solutions converge to the deterministic Navier-Stokes equations. We prove that the invariant measures, which converge to a Dirac mass at $0$, also satisfy a large deviation principle with action functional given by the enstrophy.en_US
dc.identifierhttps://doi.org/10.13016/9had-0bt2
dc.identifier.urihttp://hdl.handle.net/1903/27813
dc.language.isoenen_US
dc.subject.pqcontrolledApplied mathematicsen_US
dc.subject.pquncontrolledLarge Deviations Theoryen_US
dc.subject.pquncontrolledProbability Theoryen_US
dc.subject.pquncontrolledStochastic Differential Equationsen_US
dc.subject.pquncontrolledStochastic Partial Differential Equationsen_US
dc.titleRare Events and Exit Problems for Stochastic Equations: Theory and Numericsen_US
dc.typeDissertationen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Paskal_umd_0117E_21830.pdf
Size:
1.76 MB
Format:
Adobe Portable Document Format