The mathematical genius of birds with Christiana Mavroyiakoumou.

Mon, 13 Oct 2025
16:00
C3

Eigenvalues of non-backtracking matrices

Cedric Pilatte
(Mathematical Insitute, Oxford)
Abstract
Understanding the eigenvalues of the adjacency matrix of a (possibly weighted) graph is a problem arising in various fields of mathematics. Since a direct computation of the spectrum is often too difficult, a common strategy is to instead study the trace of a high power of the matrix, which corresponds to a high moment of the eigenvalues. The utility of this method comes from its combinatorial interpretation: the trace counts the weighted, closed walks of a given length within the graph.
 
However, a common obstacle arises when these walk-counts are dominated by trivial "backtracking" walks—walks that travel along an edge and immediately return. Such paths can mask the more meaningful structural properties of the graph, yielding only trivial bounds.
 
This talk will introduce a powerful tool for resolving this issue: the non-backtracking matrix. We will explore the fundamental relationship between its spectrum and that of the original matrix. This technique has been successfully applied in computer science and random graph theory, and it is a key ingredient in upcoming work on the 2-point logarithmic Chowla conjecture.
Word Meanings in Transformer Language Models.
Grindrod, J Grindrod, P CoRR volume abs/2508.12863 (Aug 2025)
Fri, 24 Oct 2025
12:00
L3

Gravitational Instantons, Weyl Curvature, and Conformally Kaehler Geometry

Claude LeBrun
(SUNY at Stony Brook)
Abstract

In this talk, I will discuss my joint paper with Olivier Biquard and Paul Gauduchon on ALF Ricci-flat Riemannian  4-manifolds. My collaborators had previously classified all such spaces that are toric and Hermitian, but not Kaehler. Our main result uses an open curvature condition to prove a rigidity result of the following type: any Ricci-flat metric that is sufficiently close to a non-Kaehler, toric, Hermitian ALF solution (with respect to a norm that imposes reasonable fall-off at infinity) is actually  one of the  known Hermitian toric  solutions. 
 

Fri, 17 Oct 2025
13:00
L6

Zero sets from the viewpoint of topological persistence

Vukašin Stojisavljević
(Oxford University)
Abstract

Studying the topology of zero sets of maps is a central topic in many areas of mathematics. Classical homological invariants, such as Betti numbers, are not always suitable for this purpose due to the fact that they do not distinguish between topological features of different sizes. Topological data analysis provides a way to study topology coarsely by ignoring small-scale features. This approach yields generalizations of a number of classical theorems, such as Bézout's theorem and Courant’s nodal domain theorem, to a wider class of maps. We will explain this circle of ideas and discuss potential directions for future research. The talk is partially based on joint works with L. Buhovsky, J. Payette, I. Polterovich, L. Polterovich and E. Shelukhin.

Wed, 22 Oct 2025
11:00
L4

Two partition-function approaches to non-symmetric random tensor eigenvalues

Giacomo La Scala
(Oxford University)
Abstract
At large N, random matrices with Gaussian distributed entries follow the Wigner semicircular law for the distribution of their eigenvalues. Random tensors are of interest in contexts of d > 2 dimensional quantum theories but do not enjoy simple generalisations of eigenvalues. Work has recently been done by Gurau to extend Wigner’s law to totally symmetric random tensors, with an approach inspired by the partition function of a Gaussian p-spin model. Starting from Gurau’s approach, I will motivate and introduce two new attempts to define and study eigenvalues of non-symmetric random tensors through partition functions, at finite and large N. One approach, based on a definition of a characteristic function, will be related to Gurau’s distribution. The other, based on a permuted definition of eigenvalues, will hint at a universality with differently-computed distributions for symmetric and complex random tensors.
Tue, 21 Oct 2025

14:00 - 15:00
L3

Optimal control of the Dyson equation and large deviations for Hermitian random matrices

Prof Panagiotis E. Souganidis
(University of Chicago)
Abstract

Using novel arguments as well as techniques developed over the last  twenty years to study mean field games, in this paper (i) we investigate the optimal control of the Dyson equation, which is the mean field equation for the so-called Dyson Brownian motion, that is, the stochastic particle system satisfied by the eigenvalues of large random matrices, (ii) we establish the well-posedness of the resulting infinite dimensional Hamilton-Jacobi equation, 
(iii) we provide a complete and direct proof for the large deviations for the spectrum of large random matrices, and (iv) we study the asymptotic behavior of the transition probabilities of the Dyson Brownian motion.  Joint work with Charles Bertucci and Pierre-Louis Lions.

Mon, 02 Feb 2026

15:30 - 16:30
L3

Mean field games without rational expectations

Benjamin Moll
(LSE)
Abstract
Mean Field Game (MFG) models implicitly assume “rational expectations”, meaning that the heterogeneous agents being modeled correctly know all relevant transition probabilities for the complex system they inhabit. When there is common noise, it becomes necessary to solve the “Master equation” (a.k.a. “Monster equation”), a Hamilton-JacobiBellman equation in which the infinite-dimensional density of agents is a state variable. The rational expectations assumption and the implication that agents solve Master equations is unrealistic in many applications. We show how to instead formulate MFGs with non-rational expectations. Departing from rational expectations is particularly relevant in “MFGs with a low-dimensional coupling”, i.e. MFGs in which agents’ running reward function depends on the density only through low-dimensional functionals of this density. This happens, for example, in most macroeconomics MFGs in which these lowdimensional functionals have the interpretation of “equilibrium prices.” In MFGs with a low-dimensional coupling, departing from rational expectations allows for completely sidestepping the Master equation and for instead solving much simpler finite-dimensional HJB equations. We introduce an adaptive learning model as a particular example of nonrational expectations and discuss its properties.
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