Large Deviations for a Class of Parabolic Semilinear Stochastic Partial Differential Equations in Any Space Dimension

Abstract

We prove the large deviation principle for the law of the solutions to a class of parabolic semilinear stochastic partial differential equations driven by multiplicative noise, in C([0,T]:L(D)), where D⊂ Rd with d≥slant 1 is a bounded convex domain with smooth boundary and is any real, positive and large enough number. The equation has nonlinearities of polynomial growth of any order, the space variable is of any dimension, and the proof is based on the weak convergence method.

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