1-d parabolic Anderson model with rough spatial noise

Series
Stochastics Seminar
Time
Thursday, March 7, 2019 - 3:05pm for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Samy Tindel – Purdue University
Organizer
Christian Houdré
In this talk I will first recall some general facts about the parabolic Anderson model (PAM), which can be briefly described as a simple heat equation in a random environment. The key phenomenon which has to be observed in this context is called localization. I will review some ways to express this phenomenon, and then single out the so called eigenvectors localization for the Anderson operator. This particular instance of localization motivates our study of large time asymptotics for the stochastic heat equation. In the second part of the talk I will describe the Gaussian environment we consider, which is rougher than white noise, then I will give an account on the asymptotic exponents we obtain as time goes to infinity. If time allows it, I will also give some elements of proof.