Paul Tschisgale
Abstract: In this talk we present Glauber dynamics as a way of simulating configurations according to the Gibbs distribution of the Curie-Weiss Potts model . In particular, we first present essential aspects of discrete-time Markov chains like convergence, mixing times, and the cut-off phenomenon; afterwards, with the help of results from two original computer programs, we show how the convergence behavior depends on the (inverse) temperature of the model.
Some basic notions on Markov chains that will be used during the talk can be found in this handout.
