Friday, April 26, 2024 1:30 PM - 2:30 PM (ET)
Laufer Center for Physical and Quantitative Biology - Laufer Center - Lecture Hall 101100 Nicolls RdStony Brook NY 11794
IACS Staffiacs@stonybrook.edu
Mixing, stopping, coupling, lifting, and other keys to the second Monte Carlo revolution
Abstract: The Markov-chain Monte Carlo method is an outstanding tool in science that, essentially, consists in evaluating very high-dimensional integrals using a stochastic approach. A first "revolution", in the 1950s, introduced the concept of sampling, and built on its analogy with equilibrium statistical mechanics. It lead, for example, to the famous Metropolis and heat-bath algorithms. Recent decades have witnessed a second revolution, where the concepts of mixing, stopping, coupling, and lifting, etc., have lead to a better understanding, and to much faster, and sometimes even "perfect" sampling methods. They often build on the notion of non-reversibility and map onto non-reversible physical dynamics.
In this talk, I will introduce to this interdisciplinary field of research about non-equilibrium in equilibrium, starting with the above keywords of modern Markov-chain Monte Carlo. In particular, I will discuss applications from Bethe-ansatz solvable particle models to new Monte Carlo algorithms in statistical and chemical physics.
Bio linked here.