Seminar

Large deviations for a class of 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] : Lρ(D) where D ⊂ Rd with d 1 is a bounded convex domain with smooth boundary and ρ 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.

Monster Math

There is an impending doom that the undead will once again populate the Earth. In this talk, I will describe the mathematics behind this invasion. First, using scientific zombie data, I will discuss and analyze the population dynamics of zombie infestations and how it may be possible to overcome them. After, I will talk about some advances in the science of Vampirology with former Pitt math major Jackie Ruchti. In the presence of vampire killers, oscillations can emerge between the populations of vampires and their victims.