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Stochastic PDEs are used to model systems that are spatially extended and include a random component. This course gives an introduction to this topic, including some general measure theory, some Gauss
Veuillez noter qu'il ne s'agit pas d'une liste complète des publications de cette personne. Elle inclut uniquement les travaux sémantiquement pertinents. Pour une liste complète, veuillez consulter Infoscience.
We present a simple PDE construction of the sine‐Gordon measure below the first threshold (), in both the finite and infinite volume settings, by studying the corresponding parabolic sine‐Gordon model. We also establish pathwise global well‐posedness of th ...
We consider the (discrete) parabolic Anderson model ∂u(t, x)/∂t = ∆u(t, x) + ξt(x)u(t, x), t ≥ 0, x ∈ Z d. Here, the ξ-field is R-valued, acting as a dynamic random environment, and ∆ represents the discrete Laplacian. We focus on the case where ξ is given ...
We consider the 2D stochastic Navier–Stokes equations driven by noise that have the regularity of space-time white noise but don’t exactly coincide with it. We show that, provided that the intensity of the noise is sufficiently weak at high frequencies, th ...
