Stochastic Box-Ball System - Convergence to Brownian Motion
Offered By: Institute for Pure & Applied Mathematics (IPAM) via YouTube
Course Description
Overview
Explore the stochastic version of the box-ball system in this 40-minute lecture presented by David Keating from the University of Wisconsin-Madison at IPAM's Vertex Models workshop. Delve into the deterministic discrete-time dynamical system introduced by Takahashi and Satsuma, where boxes at each natural number can hold a single ball or be empty. Discover how the introduction of a failure probability ϵ transforms the system into a stochastic model. Examine the focus on inter-distance configurations rather than individual ball positions, and learn about the main result showing convergence to semi-martingale reflecting Brownian motion after suitable rescaling. Gain insights into this fascinating topic at the intersection of pure and applied mathematics.
Syllabus
David Keating - Stochastic Box-Ball System - IPAM at UCLA
Taught by
Institute for Pure & Applied Mathematics (IPAM)
Related Courses
Game TheoryStanford University via Coursera Network Analysis in Systems Biology
Icahn School of Medicine at Mount Sinai via Coursera Visualizing Algebra
San Jose State University via Udacity Conceptos y Herramientas para la Física Universitaria
Tecnológico de Monterrey via Coursera Aplicaciones de la Teoría de Grafos a la vida real
Universitat Politècnica de València via UPV [X]