As you may know, the MSc in Mathematical Sciences (OMMS) is a standalone MSc which runs parallel with Part C. To help the MSc students feel welcomed to the department, we have a buddy system where our OMMS students are paired with current Part B students who will be staying on to Part C and they can communicate over the summer if they choose. A buddy would be someone the MSc student could ask informal questions (a bit like a college parent). MSc students and buddies would then be free to decide when to meet during the academic year.

The World Cup is almost here and everyone has an opinion about likely winners. But being mathematicians, we have insisted on looking at the data, and we think we have found the secret to predicting results.

Josh Bull is our analyst in the studio.

Tue, 16 Jun 2026

12:00 - 13:00
C5

Global existence for a cross diffusion system with different mobilities

Charles Elbar
(Université Claude Bernard Lyon 1)
Abstract

We consider a cross diffusion system of two populations, often called the Busenberg-Travis system. The two species are transported by the same pressure gradient with Darcy’s law, modeling overcrowding effect (populations tend to move away from regions of high pressure). However, their mobility is different: the first species moves with mobility 1, whereas the second moves with mobility \nu. The difficulty to prove existence is to prove strong compactness of each densities, which we achieve with a variant of the div-curl lemma applied to evolution PDEs.

Wed, 24 Jun 2026

11:00 - 13:00
L4

Wasserstein Limits for Empirical Measures of Markov Processes

Fengyu Wang
(University of Swansea)
Abstract

In this talk we summary some recent progress on limit theorems for the Wasserstein distance of empirical measures of Markov processes. For symmetric diffusion processes on Riemannian manifold possibly with reflecting or killing boundary, the sharp convergence rate is derived with renormalization limit formulated by using the spectrum of the generator. Moreover, a general framework is established to estimate the convergence rate in Wasserstein distance of empirical measures for ergodic Markov processes.

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