Published:
[Erscheinungsort nicht ermittelbar]: Banff International Research Station (BIRS) for Mathematical Innovation and Discovery, 2020
Published in:Online Open Probability School (20ss230) ; (Jan. 2020)
Extent:
1 Online-Ressource (130 MB, 00:57:15:21)
Language:
English
DOI:
10.5446/55657
Identifier:
Origination:
Footnote:
Audiovisuelles Material
Description:
Mixing times for Markov chains is an active area of research in modern probability and it lies at the interface of mathematics, statistical physics and theoretical computer science. The mixing time of a Markov chain is defined to be the time it takes to come close to equilibrium. There is a variety of techniques used to estimate mixing times, coming from probability, representation theory and spectral theory. In this mini course I will focus on probabilistic techniques and in particular, I will present some recent results (see references below) on connections between mixing times and hitting times of large sets. Prerequisites: It would be helpful to be familiar with Chapters 4(mixing definitions) and 12(spectral methods) from the book Mixing Times for Markov Chains by D. Levin, Y. Peres and E. Wilmer