Thursday, May 22, 2025 - 10:00 in V2-210
Large deviations for stochastic evolution equations
A talk in the SPDEvent series by
Esmée Theewis from Delft University of Technology
| Abstract: |
This talk is about a recent large deviation result for solutions to quasilinear SPDEs with small Gaussian noise. We consider a general variational framework for stochastic evolution equations. The large deviation principle (LDP) has been successfully proved for such frameworks by means of the so-called weak convergence approach, but often, strong assumptions have to be made on the coefficients in the equation or on the Gelfand triple. In our current large deviation result, we do not require any additional assumption apart from those required for well-posedness of the equation. This leads to numerous applications for which the LDP was not established yet, in particular equations on unbounded spatial domains with gradient noise. The talk is based on joint work with Mark Veraar (Delft University of Technology).
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