Rankin Lecture 2024
Prof Tim Austin (University of Warwick)
Tuesday 21st May 16:00-17:00 LT 116, Mathematics and Statistics Building, UofG
Abstract
The School of Mathematics and Statistics is delighted to invite you to the Rankin Lecture 2024, to be given by Professor Tim Austin (University of Warwick). The lecture, entitled Notions of entropy in ergodic theory and representation theory, will be held on Tuesday 21st May 2024, 4-5pm BST, with a wine reception to follow at 5pm.
To attend in-person, please register in advance at https://rankin-lecture-2024.eventbrite.co.uk
To attend online, please register in advance at https://uofglasgow.zoom.us/meeting/register/tZEkcOGpqTwuGdR2LnnYR7hsf6g7O-lOh4R9
Location: Lecture Theatre 116 of the Mathematics and Statistics Building (map here)
Date/Time: Tuesday 21st May 2024, 4-5pm, with a wine reception to follow at 5pm
Speaker: Professor Tim Austin (University of Warwick)
Title: Notions of entropy in ergodic theory and representation theory
About the speaker
Tim Austin is the Regius Professor of Mathematics at the University of Warwick, and works in ergodic theory, probability, combinatorics and functional analysis. He was awarded a New Horizons in Mathematics Prize in 2020, the Michael Brin Prize in Dynamical Systems in 2021, and the Ostrowski Prize in 2021.
Abstract
Entropy has its origins in thermodynamics and statistical mechanics. It gained mathematical rigour in Shannon's work on the foundations of information theory, and quickly found striking applications to ergodic theory in work of Kolmogorov and Sinai. Many variants and other applications have appeared in pure mathematics since, connecting probability, combinatorics, dynamics and other areas.
I will survey a few recent developments in this story, with an emphasis on some of the basic ideas that they have in common. I will focus largely on (i) Lewis Bowen's "sofic entropy", which helps us to study the dynamics of "large" groups such as free groups, and (ii) a cousin of sofic entropy in the world of unitary representations, which leads to new connections with random matrices.
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