Asymptotic Independence via Malliavin-Stein Method

Título: Asymptotic Independence via Malliavin-Stein Method

Resumen: How far is the distance between the joint measure of a two-dimensional random vector and the product measure induced by its marginals? In this talk we consider this question in the context of a Markov process within the KPZ universality class, where the first coordinate of the vector is given by an observable of a Brownian initial condition, and the second one is an observable of the process at a later time. To attack this task we will use tools from Malliavin calculus and Stein’s Method, which will allow us to get a precise space-time scaling behavior for asymptotic independence. This is a joint work with Sergio I. López (available from https://arxiv.org/abs/2208.14987).