Thu, 21 Nov 2024
13:00
N3.12

Aspects of anomalies

Alice Lüscher
Abstract

Anomalies characterize the breaking of a classical symmetry at the quantum level. They play an important role in quantum field theories, and constitute robust observables which appear in various contexts from phenomenological particle physics to black hole microstates, or to classify phases of matter. The anomalies of a d-dimensional QFT are naturally encoded via descent equations into the so-called anomaly polynomial in (d+2)-dimensions. The aim of this seminar is to review the descent procedure, anomaly polynomial, anomaly inflow, and in particular their realisation in M-theory. While this is quite an old story, there has been some more recent developments involving holography that I'll describe if time permits. 

 

Junior Strings is a seminar series where DPhil students present topics of common interest that do not necessarily overlap with their own research area. This is primarily aimed at PhD students and post-docs but everyone is welcome.

Thu, 21 Nov 2024
12:00
C6

Failure of the Measure Contraction Property on the Martinet Flat Structure

Samuel Borza
(University of Vienna)
Abstract

The Martinet flat structure is one of the simplest sub-Riemannian manifolds that has many non-Riemannian features: it is not equiregular, it has abnormal geodesics, and the Carnot-Carathéodory sphere is not sub-analytic. I will review how the geometry of the Martinet flat structure is tied to the equations of the pendulum. Surprisingly, the Measure Contraction Property (a weak synthetic formulation of Ricci curvature bounds in non-smooth spaces) fails, and we will try to understand why. If time permits, I will also discuss how this can be generalised to some Carnot groups that have abnormal extremals. This is a joint work in progress with Luca Rizzi.

Thu, 21 Nov 2024

12:00 - 12:30
Lecture Room 6

Local convergence of adaptively regularized tensor methods

Karl Welzel
(University of Oxford)
Abstract

Tensor methods are methods for unconstrained continuous optimization that can incorporate derivative information of up to order p > 2 by computing a step based on the pth-order Taylor expansion at each iteration. The most important among them are regularization-based tensor methods which have been shown to have optimal worst-case iteration complexity of finding an approximate minimizer. Moreover, as one might expect, this worst-case complexity improves as p increases, highlighting the potential advantage of tensor methods. Still, the global complexity results only guarantee pessimistic sublinear rates, so it is natural to ask how local rates depend on the order of the Taylor expansion p. In the case of strongly convex functions and a fixed regularization parameter, the answer is given in a paper by Doikov and Nesterov from 2022: we get pth-order local convergence of function values and gradient norms. 
The value of the regularization parameter in their analysis depends on the Lipschitz constant of the pth derivative. Since this constant is not usually known in advance, adaptive regularization methods are more practical. We extend the local convergence results to locally strongly convex functions and fully adaptive methods. 
We discuss how for p > 2 it becomes crucial to select the "right" minimizer of the regularized local model in each iteration to ensure all iterations are eventually successful. Counterexamples show that in particular the global minimizer of the subproblem is not suitable in general. If the right minimizer is used, the pth-order local convergence is preserved, otherwise the rate stays superlinear but with an exponent arbitrarily close to one depending on the algorithm parameters.

Thu, 21 Nov 2024

12:00 - 13:00
L3

Tension-induced giant actuation in elastic sheets (Marc Sune) Deciphering Alzheimer's Disease: A Modelling Framework for In Silico Drug Trials (Georgia Brennan)

Dr Marc Suñé & Dr Georgia Brennan
(Mathematical Institute)
Abstract

Tension-induced giant actuation in elastic sheets

Dr. Marc Suñé

Buckling is normally associated with a compressive load applied to a slender structure; from railway tracks in extreme heat to microtubules in cytoplasm, axial compression is relieved by out-of-plane buckling. However, recent studies have demonstrated that tension applied to structured thin sheets leads to transverse motion that may be harnessed for novel applications, such as kirigami grippers, multi-stable `groovy-sheets', and elastic ribbed sheets that close into tubes. Qualitatively similar behaviour has also been observed in simulations of thermalized graphene sheets, where clamping along one edge leads to tilting in the transverse direction. I will discuss how this counter-intuitive behaviour is, in fact, generic for thin sheets that have a relatively low stretching modulus compared to the bending modulus, which allows `giant actuation' with moderate strain.

Thu, 21 Nov 2024

11:00 - 12:00
C3

Almost sure convergence to a constant for a mean-aggregated term language

Sam Adam-Day
(University of Oxford)
Abstract
With motivation coming from machine learning, we define a term language on graphs generalising many graph neural networks. Our main result is that the closed terms of this language converge almost surely to constants. This probabilistic result holds for Erdős–Rényi graphs for a variety of sparsity levels, as well as the Barabási–Albert preferential attachment graph distribution. The key technique is a kind of almost sure quantifier elimination. A natural extension of this language generalises first-order logic, and a similar convergence result can be obtained there.
 
Wed, 20 Nov 2024
17:00
Lecture Theatre 1, Mathematical Institute, Radcliffe Observatory Quarter, Woodstock Road, OX2 6GG

Chance, luck, and ignorance: how to put our uncertainty into numbers - David Spiegelhalter

David Spiegelhalter
(University of Cambridge)
Further Information

We all have to live with uncertainty about what is going to happen, what has happened, and why things turned out how they did.  We attribute good and bad events as ‘due to chance’, label people as ‘lucky’, and (sometimes) admit our ignorance.  I will show how to use the theory of probability to take apart all these ideas, and demonstrate how you can put numbers on your ignorance, and then measure how good those numbers are. Along the way we will look at three types of luck, and judge whether Derren Brown was lucky or unlucky when he was filmed flipping ten Heads in a row.

David Spiegelhalter was Cambridge University's first Winton Professor of the Public Understanding of Risk. He has appeared regularly on television and radio and is the author of several books, the latest of which is The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck (Penguin, September 2024).

Please email @email to register to attend in person.

The lecture will be broadcast on the Oxford Mathematics YouTube Channel on Wednesday 11 December at 5-6pm and any time after (no need to register for the online version).

The Oxford Mathematics Public Lectures are generously supported by XTX Markets.

Wed, 20 Nov 2024
16:00
L6

Division rings in the service of group theory

Pablo Sánchez-Peralta
(Universidad Autonoma de Madrid)
Abstract

Embedding the group algebra into a division ring has proven to be a powerful tool for detecting structural properties of the group, especially in relation to its homology. In this talk, we will show how division rings can be used to identify residual properties of groups, one-ended groups, and coherent groups. We will place special emphasis on the class of free-by-cyclic groups to provide a clear, explicit exposition.

Wed, 20 Nov 2024
11:00
L4

Quadratic and $p^\mathrm{th}$ variation of stochastic processes through Schauder expansions

Yuchen Fan
(University of Oxford)
Abstract
We present a class of stochastic processes which admit a unique quadratic variation along any sequence of partitions $(\pi^n)_{n\geq 1}$ with $\sum_{n\geq 1}|\pi^n|<\infty$, which generalizes the previous results for finitely refining partitions. This class of processes contains some signed Takagi-Landsberg functions with random coefficients and standard Brownian motions, and these processes admit $\frac{1}{4}$-Hölder continuous version. We study the quadratic and $p^\mathrm{th}$ variation of signed Takagi-Landsberg functions with random coefficients. Finally, we seek some generalizations and applications of our results.


 

Tue, 19 Nov 2024
16:00
C3

Residually finite dimensional C*-algebras arising in dynamical contexts

Adam Skalski
(University of Warsaw)
Abstract

A C*-algebra is said to be residually finite-dimensional (RFD) when it has `sufficiently many' finite-dimensional representations. The RFD property is an important, and still somewhat mysterious notion, with subtle connections to residual finiteness properties of groups. In this talk I will present certain characterisations of the RFD property for C*-algebras of amenable étale groupoids and for C*-algebraic crossed products by amenable actions of discrete groups, extending (and inspired by) earlier results of Bekka, Exel, and Loring. I will also explain the role of the amenability assumption and describe several consequences of our main theorems. Finally, I will discuss some examples, notably these related to semidirect products of groups.

Tue, 19 Nov 2024
16:00
L6

Will large economies be stable?

Jean-Philippe Bouchaud
(Ecole Normale Supérieure/Capital Fund Management)
Abstract

We study networks of firms in which inputs for production are not easily substitutable, as in several real-world supply chains. Building on Robert May's original argument for large ecosystems, we argue that such networks generically become dysfunctional when their size increases, when the heterogeneity between firms becomes too strong, or when substitutability of their production inputs is reduced. At marginal stability and for large heterogeneities, crises can be triggered by small idiosyncratic shocks, which lead to “avalanches” of defaults. This scenario would naturally explain the well-known “small shocks, large business cycles” puzzle, as anticipated long ago by Bak, Chen, Scheinkman, and Woodford. However, an out-of-equilibrium version of the model suggests that other scenarios are possible, in particular that of `turbulent economies’.

Tue, 19 Nov 2024
15:00
L6

Studying monoids that model concurrency

Sarah Rees
(University of Newcastle)
Abstract

I’ll discuss joint work of mine with with Ascencio-Martin, Britnell, Duncan, Francoeurs and Koutny to set up and study algebraic models of concurrent computation. 

Trace monoids were introduced by Mazurkiewicz as algebraic models of Petri nets, where some pairs of actions can be applied in either of two orders and have the same effect. Abstractly, a trace monoid is simply a right-angled Artin monoid. More recently Koutny et al. introduced the concept of a step trace monoid, which allows the additional possibility that a pair of actions may have the same effect performed simultaneously as sequentially. 

I shall introduce these monoids, discuss some problems we’d like to be able to solve, and the methods with which we are trying to solve them. In particular I’ll discuss normal forms for traces, comtraces and step traces, and generalisations of Stallings folding techniques for finitely presented groups and monoids.

Tue, 19 Nov 2024
14:00
L5

Brennan Klein: Network Comparison and Graph Distances: A Primer and Open Questions

Brennan Klein
(Northeastern University Network Science Institute)
Further Information

Brennan Klein is an associate research scientist at the Network Science Institute at Northeastern University, where he studies complex systems across nature and society using tools from network science and statistics. His research sits in two broad areas: First, he develops methods and theory for constructing, reconstructing, and comparing complex networks based on concepts from information theory and random graphs. Second, he uses an array of interdisciplinary approaches to document—and combat—emergent or systemic disparities across society, especially as they relate to public health and public safety. In addition to his role at Northeastern University, Brennan is the inaugural Data for Justice Fellow at the Institute on Policing, Incarceration, and Public Safety in the Hutchins Center for African and African American Studies at Harvard University. Brennan received a PhD in Network Science from Northeastern University in 2020 and a B.A. in Cognitive Science from Swarthmore College in 2014. Website: brennanklein.com. Contact: @email; @jkbren.bsky.social.

Abstract
Quantifying dissimilarities between pairs of networks is a challenging and, at times, ill-posed problem. Nevertheless, we often need to compare the structural or functional differences between complex systems across a range of disciplines, from biology to sociology. These techniques form a family of graph distance measures, and over the last few decades, the number and sophistication of these techniques have increased drastically. In this talk, I offer a framework for categorizing and benchmarking graph distance measures in general: the within-ensemble graph distance (WEGD), a measure that leverages known properties of random graphs to evaluate the effectiveness of a given distance measure. In doing so, I hope to offer an invitation for the development of new graph distances, which have the potential to be more informative and more efficient than the tools we have today. I close by offering a roadmap for identifying and addressing open problems in the world of graph distance measures, with applications in neuroscience, material design, and infrastructure networks.
Tue, 19 Nov 2024

14:00 - 15:00
L4

Tight general bounds for the extremal number of 0-1 matrices

Oliver Janzer
(University of Cambridge)
Abstract

A zero-one matrix $M$ is said to contain another zero-one matrix $A$ if we can delete some rows and columns of $M$ and replace some 1-entries with 0-entries such that the resulting matrix is $A$. The extremal number of $A$, denoted $\operatorname{ex}(n,A)$, is the maximum number of 1-entries that an $n\times n$ zero-one matrix can have without containing $A$. The systematic study of this function for various patterns $A$ goes back to the work of Furedi and Hajnal from 1992, and the field has many connections to other areas of mathematics and theoretical computer science. The problem has been particularly extensively studied for so-called acyclic matrices, but very little is known about the general case (that is, the case where $A$ is not necessarily acyclic). We prove the first asymptotically tight general result by showing that if $A$ has at most $t$ 1-entries in every row, then $\operatorname{ex}(n,A)\leq n^{2-1/t+o(1)}$. This verifies a conjecture of Methuku and Tomon.

Our result also provides the first tight general bound for the extremal number of vertex-ordered graphs with interval chromatic number two, generalizing a celebrated result of Furedi, and Alon, Krivelevich and Sudakov about the (unordered) extremal number of bipartite graphs with maximum degree $t$ in one of the vertex classes.

Joint work with Barnabas Janzer, Van Magnan and Abhishek Methuku.

Tue, 19 Nov 2024
13:00
L2

Symmetry topological field theory and generalised Kramers–Wannier dualities

Clement Delcamp
(IHES)
Abstract

A modern perspective on symmetry in quantum theories identifies the topological invariance of a symmetry operator within correlation functions as its defining property. Within this paradigm, a framework has emerged enabling a calculus of topological defects in terms of a higher-dimensional topological quantum field theory. In this seminar, I will discuss aspects of this construction for Euclidean lattice field theories. Exploiting this framework, I will present generalisations of the celebrated Kramers-Wannier duality of the Ising model, as combinations of gauging procedures and generalised Fourier transforms of the local weights encoding the dynamics. If time permits, I will discuss implications of this framework for the real-space renormalisation group flow of these theories.

Mon, 18 Nov 2024
16:30
L4

Short- and long-time behavior in evolution equations: the role of the hypocoercivity index

Anton Arnold
(Vienna University of Technology)
Abstract

The "index of hypocoercivity" is defined via a coercivity-type estimate for the self-adjoint/skew-adjoint parts of the generator, and it quantifies `how degenerate' a hypocoercive evolution equation is, both for ODEs and for evolutions equations in a Hilbert space. We show that this index characterizes the polynomial decay of the propagator norm for short time and illustrate these concepts for the Lorentz kinetic equation on a torus. Discrete time analogues of the above systems (obtained via the mid-point rule) are contractive, but typically not strictly contractive. For this setting we introduce "hypocontractivity" and an "index of hypocontractivity" and discuss their close connection to the continuous time evolution equations.

This talk is based on joint work with F. Achleitner, E. Carlen, E. Nigsch, and V. Mehrmann.

References:
1) F. Achleitner, A. Arnold, E. Carlen, The Hypocoercivity Index for the short time behavior of linear time-invariant ODE systems, J. of Differential Equations (2023).
2) A. Arnold, B. Signorello, Optimal non-symmetric Fokker-Planck equation for the convergence to a given equilibrium, Kinetic and Related Models (2022).
3) F. Achleitner, A. Arnold, V. Mehrmann, E. Nigsch, Hypocoercivity in Hilbert spaces, J. of Functional Analysis (2025).
 

Mon, 18 Nov 2024
16:00
C3

Heegner points and Euler systems

Andrew Graham
(University of Oxford)
Abstract

Heegner points are a powerful tool for understanding the structure of the group of rational points on elliptic curves. In this talk, I will describe these points and the ideas surrounding their generalisation to other situations.

Mon, 18 Nov 2024
15:30
L5

Equivariant log concavity and representation stability

Nicholas Proudfoot
(University of Oregon)
Abstract

June Huh proved in 2012 that the Betti numbers of the complement of a complex hyperplane arrangement form a log concave sequence.  But what if the arrangement has symmetries, and we regard the cohomology as a representation of the symmetry group?  The motivating example is the braid arrangement, where the complement is the configuration space of n points in the plane, and the symmetric group acts by permuting the points.  I will present an equivariant log concavity conjecture, and show that one can use representation stability to prove infinitely many cases of this conjecture for configuration spaces.
 

Mon, 18 Nov 2024
15:30
L3

Critical phenomena in intermediate dimensions

Dr Pierre-Francois Rodriguez
(Imperial College )
Abstract

The talk will focus on recent developments regarding the (near-)critical behaviour of certain statistical physics models with long-range dependence in dimensions larger than 2, but smaller than 6, above which mean-field behaviour is known to set in. This “intermediate” regime remains a great challenge for mathematicians. The models revolve around a certain percolation phase transition that brings into play very natural probabilistic objects, such as random walk traces and the Gaussian free field. 

Mon, 18 Nov 2024
14:15
L4

Gromov-Witten theory in degenerations

Dhruv Ranganathan
(Cambridge)
Abstract

I will discuss recent and ongoing work with Davesh Maulik that explains how Gromov-Witten invariants behave under simple normal crossings degenerations. The main outcome of the study is that if a projective manifold $X$ undergoes a simple normal crossings degeneration, the Gromov-Witten theory of $X$ is determined, via universal formulas, by the Gromov-Witten theory of the strata of the degeneration. Although the proof proceeds via logarithmic geometry, the statement involves only traditional Gromov-Witten cycles. Indeed, one consequence is a folklore conjecture of Abramovich-Wise, that logarithmic Gromov-Witten theory “does not contain new invariants”. I will also discuss applications of this to a conjecture of Levine and Pandharipande, concerning the relationship between Gromov-Witten theory and the cohomology of the moduli space of curves.

Mon, 18 Nov 2024

14:00 - 15:00
Lecture Room 3

Model-based (unfolding) neural networks and where to find them: from practice to theory

Vicky Kouni
Abstract

In recent years, a new class of deep neural networks has emerged, which finds its roots at model-based iterative algorithms solving inverse problems. We call these model-based neural networks deep unfolding networks (DUNs). The term is coined due to their formulation: the iterations of optimization algorithms are “unfolded” as layers of neural networks, which solve the inverse problem at hand. Ever since their advent, DUNs have been employed for tackling assorted problems, e.g., compressed sensing (CS), denoising, super-resolution, pansharpening. 

In this talk, we will revisit the application of DUNs on the CS problem, which pertains to reconstructing data from incomplete observations. We will present recent trends regarding the broader family of DUNs for CS and dive into their theory, which mainly revolves around their generalization performance; the latter is important, because it informs us about the behaviour of a neural network on examples it has never been trained on before. 
Particularly, we will focus our interest on overparameterized DUNs, which exhibit remarkable performance in terms of reconstruction and generalization error. As supported by our theoretical and empirical findings, the generalization performance of overparameterized DUNs depends on their structural properties. Our analysis sets a solid mathematical ground for developing more stable, robust, and efficient DUNs, boosting their real-world performance.

Fri, 15 Nov 2024
15:00
L5

On the Limitations of Fractal Dimension as a Measure of Generalization

Inés García-Redondo
(Imperial College)
Abstract
Bounding and predicting the generalization gap of overparameterized neural networks remains a central open problem in theoretical machine learning. There is a recent and growing body of literature that proposes the framework of fractals to model optimization trajectories of neural networks, motivating generalization bounds and measures based on the fractal dimension of the trajectory. Notably, the persistent homology dimension has been proposed to correlate with the generalization gap. In this talk, I will present an empirical evaluation of these persistent homology-based generalization measures, with an in-depth statistical analysis. This study reveals confounding effects in the observed correlation between generalization and topological measures due to the variation of hyperparameters. We also observe that fractal dimension fails to predict generalization of models trained from poor initializations; and reveal the intriguing manifestation of model-wise double descent in these topological generalization measures. This is joint work with Charlie B. Tan, Qiquan Wang, Michael M. Bronstein and Anthea Monod.
 
Fri, 15 Nov 2024

14:00 - 15:00
L1

Managing your Dissertation

Dr Chris Hollings and Dr Neil Laws
Abstract

This session is particularly aimed at fourth-year and OMMS students who are completing a dissertation this year. For many of you this will be the first time you have written such an extended piece on mathematics. The talk will include advice on planning a timetable, managing the workload, presenting mathematics, structuring the dissertation and creating a narrative, and avoiding plagiarism.

Fri, 15 Nov 2024

12:00 - 13:00
Quillen Room

Ring-theoretic properties of affine and graded Hecke algebras

Max Mackie
(University of Oxford)
Abstract

After recalling how Hecke algebras occur in the representation theory of reductive groups, we will introduce affine Hecke algebras through a combinatorial object called a root datum. Through a worked example we will construct a filtration on the affine Hecke algebra from which we obtain the graded Hecke algebra. This has a role analogous to the Lie algebra of an algebraic group.

We will discuss star operations on these rings, with a view towards the classical problem of studying unitary representations of reductive groups.