Large Deviations for Infinite Dimensional Stochastic Dynamical Systems
Abstract
The 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 27, 2007
- Accession Number
- ADA476186
Entities
People
- Amarjit Budhiraja
- Paul Dupuis
- Vasileios Maroulas
Organizations
- Brown University