Past

Let G be a group acting on a tree. I will discuss necessary conditions for G to have a finitely generated infinite normal subgroup of infinite index. When the edge stabilisers are virtually cyclic this naturally leads to considering (virtual) fibering of G. I will give an “if and only if” criterion for (virtual) fibering in the special case of amalgamated free products over virtually cyclic subgroups. The talk will be based on joint work with Jon Merladet.

We introduce a new spanning tree model which we call Random Spanning Trees in Random Environment (RSTRE), which was introduced independently by A. Kúsz. As the inverse temperature beta varies in the underlying Gibbs measure, it interpolates between the uniform spanning tree and the minimum spanning tree. On the complete graph with n vertices, we show that with high probability, the diameter of the random spanning tree is of order n^1/2 when β=o(n/log n), and is of order n^1/3 when β > n^4/3 log n. We conjecture that the diameter exponent linearly interpolates between these two regimes as the power exponent of beta varies. Based on joint work with L. Makowiec and M. Salvi.

Robustness to perturbation is a key topic in the study of complex systems occurring across a wide variety of applications from epidemiology to biochemistry. In this talk I will examine the eigenspectrum of the Jacobian matrices associated to a general class of networked dynamical systems, which contains information on how perturbations to a stationary state develop over time. I will show that stability is always determined by a spectral outlier, but with pronounced differences to the corresponding eigenvector in different regimes. Depending on model details, instability may originate in nodes of anomalously low or high degrees, or may occur everywhere in the network at once. Our results have potentially useful applications in network monitoring to predict or prevent catastrophic failures.

This talk discusses various applications of the relative entropy method in the context of fluid mechanics, focusing on weak-strong uniqueness results and asymptotic limits. Particular attention is given to Euler-type equations involving nonlocal interactions. Furthermore, I will present recent results regarding a novel approach to pressureless Euler equations.

Another application of the relative entropy method to be discussed is the unconditional stability of certain radially symmetric steady states for compressible viscous fluids in domains with inflow/outflow boundary conditions. Specifically, we demonstrate that any solution to the associated evolutionary problem, not necessarily radially symmetric, converges to a unique radially symmetric steady state.

Theta operators are weight-shifting differential operators on  automorphic forms. They play an important role in studying congruences between Hecke eigenforms and their p-adic variation. For instance, the classical theta operator, which acts on q-expansions of modular forms as q·(d/dq), is used crucially in Edixhoven’s proof of the weight part of Serre’s conjecture, Katz’s construction of p-adic L-functions over CM fields, and Coleman’s classicality theorem.

Recent years have witnessed extensive works on understanding theta operators over general Shimura varieties, from both geometric and representation-theoretic perspectives. In this talk, I will hint at some aspects of this fascinating area of research. If time permits, I will discuss my ongoing work on overconvergent theta operators over Siegel Shimura varieties.

Recent advances at the interface of stochastic analysis, rough path theory, stochastic filtering, stochastic control, and mean-field systems have led to a rapidly developing framework for analyzing stochastic dynamics conditioned on common/observation noice. This talk will survey how rough stochastic differential equations, introduced in 2021 by A. Hocquet, K. Lê and the speaker, lead to a unifying perspective across several areas of applied probability.

(Additional coauthors include F. Bugini, J. Dause, W. Stannat, H. Zhang and P.Zorin-Kranich.)

The stable Andrews-Curtis conjecture remains one of the most notorious unsolved problems in group theory. It proposes that every balanced presentation of the trivial group can reduced to the standard presentation (with one generator and one relation) using a sequence of simple moves. In my talk, I will focus on group presentations that are ‘thickenable’, which means that their associated 2-complex embeds in a 3-manifold. For such presentations, the stable Andrews-Curtis conjecture is known to hold. In my talk, I will explain how one can also get an explicit exponential-type upper bound on the number of stable Andrews-Curtis moves that are required. This is in sharp contrast to what is known about non-thickenable presentations.

This talk will present a new approach to the geometry of moduli spaces of hyperbolic monopoles.  It is well-known that the L^2 metric on the moduli space of hyperbolic monopoles, defined using a Coulomb gauge fixing condition, diverges. Recently we have shown that a supersymmetry-inspired gauge-fixing condition cures this divergence, resulting in a pluricomplex geometry that generalises the hyperkaehler geometry of euclidean monopole moduli spaces.  We will compare this with metrics introduced by Nash and Bielawski—Schwachhofer, and present explicit calculations of both metrics for charge 2 monopoles.

Part 1: In the first part of this talk, we develop a convergence analysis for training neural PDEs in the overparameterized limit. Many engineering and scientific fields have recently become interested in modelling terms in PDEs with neural networks (NNs), which requires solving the inverse problem of learning NN terms from observed data in order to approximate missing or unresolved physics in the PDE model. The resulting neural PDE model, being a function of the NN parameters, can be calibrated to the available ground truth data by optimizing over the PDE using gradient descent, where the gradient is evaluated in a computationally efficient manner by solving an adjoint PDE. We study the convergence of the adjoint gradient descent optimization method for training neural PDE models in the limit where both the number of hidden units and the training time tend to infinity, proving convergence of the trained neural PDE solution to the target data.

Part 2: For the second part, we turn towards developing a convergence analysis of the regularized Newton method for training NNs in the overparameterized limit. As the number of hidden units tends to infinity, the NN training dynamics converge in probability to the solution of a deterministic limit equation involving a „Newton neural tangent kernel“ (NNTK). Explicit rates characterizing this convergence are provided and, in the infinite-width limit, we prove that the NN converges exponentially fast to the target data. We show that this convergence is uniform across the frequency spectrum, addressing the spectral bias inherent in gradient descent. Mathematical challenges that need to be addressed in our analysis include the implicit parameter update of the Newton method with a potentially indefinite Hessian matrix and the fact that the dimension of this linear system of equations tends to infinity as the NN width grows.

One of the problems posed by Kadison in 1967 asks whether every separably acting von Neumann algebra is generated by a single element. The problem remains open in its full generality but significant progress has been made since. One can of course ask the same question in the C*-algebraic setting where, however, counterexamples are abundant even among commutative C*-algebras. I will give an overview of the history of the problem and then discuss some recent results on single generation of C*-algebras associated to graphs and C*-algebras with Cartan subalgebras.

I will discuss stochastic systems of interacting particles with non-overlapping constraints, which give rise to so-called excluded-volume interactions. The aim is to derive effective macroscopic equations governing the evolution of particle densities from the underlying microscopic dynamics. When particles possess nontrivial size or shape, geometric constraints become essential: they complicate the coarse-graining process and strongly influence the emergent behaviour of the system. I will present two representative examples, hard spheres and infinitely thin needles, highlighting how geometry enters the macroscopic description

This session is aimed at first-year undergraduates preparing for Prelims exams. A panel of lecturers and current students will share key advice on exam technique and revision strategies, offering practical tips from their own experience.

Cells make decisions across developmental biology, immunology, and synthetic biology. These processes are typically described using systems of ordinary differential equations, where mathematical analysis focuses on steady-state solutions. However, understanding how the timing of cell decisions is controlled requires moving beyond this paradigm. In this talk, I will discuss two complementary molecular mechanisms for controlling dynamical speed. First, I will show how timing can be regulated through critical slowing down, and how combining different bifurcations can generate emergent temporal behaviours even in small gene regulatory networks. Secondly, I will address developmental tempo, where embryos from different species execute remarkably similar genetic programmes at different speeds. I will present a mathematical framework based on orbit invariance that allows us to explore potential molecular mechanisms underlying species-specific differences in developmental timing.

7 years ago, also in Oxford, Sylvy Anscombe and I asked this question, which is part of the general effort to try and understand the model theory of henselian valued fields through dividing lines. In 2024, Sylvy Anscombe and Franziska Jahnke completely classified NIP henselian valued fields. Their methods can be extended, with the help of works of Chernikov, Kaplan and Simon and of Kuhlmann and Rzepka, to NTP2 henselian valued fields, obtaining the following:

• if a henselian valued field is NTP2, then it is semitame and its residue field is NTP2;
• if a henselian valued field is separably algebraically maximal Kaplansky and its residue field is NTP2, then it is NTP2.

This covers a large class of fields, but there is still a gap. Notably, Fp((Q)) is in the middle: it is semitame but not Kaplansky.

To answer this question, we studied so called tame henselian fields with finite residue field, and derived quantifier elimination results, namely, we prove that any formula in the language of valued fields reduces to a formula of the form (∃y f(x,y)=0) ∧ φ(v(x)) ∧ ψ(res(x)), where φ and ψ are formulas in the language of ordered groups and of rings, respectively.

In Fp((Q)) specifically, the valuation ring itself is definable with a diophantine formula (ie of the form ∃y f(x,y)=0), reducing further our quantifier elimination result.

Finally, a large chunk of these formulas are known to be NTP2: when f(x,y) is additive in y, the formula ∃y f(x,y)=z is NTP2 (with respect to x and z). Unfortunately, that does not cover all formulas, so the answer to the titular question is still unknown.

A question of Ben Green asks whether every finite set $A$ of integers with doubling constant $K$ must contain a subset $A'$ of comparable size whose doubling is at most $K + o(1)$ due to some explicit algebraic structure on $A'$. This was previously understood in the regime $K < 4 - o(1)$ by work of Eberhard, Green, and Manners, who showed that one can find such a subset $A'$ with density at least $1/2 + o(1)$ inside a long arithmetic progression. In this talk, I will provide a brief survey of this question as well as mention some new progress towards this. This is joint work with Yifan Jing.

Speaker Prof Dr Maria Lukacova will talk about 'Numerical analysis of oscillatory solutions of compressible flows'

Oscillatory solutions of compressible flows arise in many practical situations.  An iconic example is the Kelvin-Helmholtz problem, where standard numerical methods yield oscillatory solutions. In such a situation,  standard tools of numerical analysis for partial differential equations are not applicable. 

We will show that structure-preserving numerical methods converge in general to generalised solutions, the so-called dissipative solutions. 
The latter describes the limits of oscillatory sequences. We will concentrate on the inviscid flows, the Euler equations of gas dynamics, and mention also the relevant results obtained for the viscous compressible flows, governed by the Navier-Stokes equations.

We discuss a concept of K-convergence that turns a weak convergence of numerical solutions into the strong convergence of
their empirical means to a dissipative solution. The latter satisfies a weak formulation of the Euler equations modulo the Reynolds turbulent stress.  We will also discuss suitable selection criteria to recover well-posedness of the Euler equations of gas dynamics. Theoretical results will be illustrated by a series of numerical simulations.  

The period matrix of a smooth complex projective variety encodes the isomorphism between its singular homology and its algebraic De Rham cohomology. Numerical approximations with high precision of the entries of the period matrix allow to recover some algebraic invariants of the variety, such as the Néron-Severi group in the case of surfaces. In this talk, we will see a method relying on the computation of an effective description of the homology for obtaining such numerical approximations of periods of algebraic varieties, and showcase implementations and applications, in particular to computation of the Picard rank of certain K3 surfaces related to Feynman diagrams.

In this seminar, we consider an isoperimetric problem for planar tilings with possibly unequal repeating cells. We present general existence and regularity results, and we study the classification of planar isoperimetric double tilings, namely tilings with two repeating cells of minimal perimeter. In this case, we explicitly determine the associated energy profile and provide a complete description of the phase transitions. We also comment on possible extensions and discuss some open problems. This is based on joint work with M. Novaga and E. Paolini.

Daniel Cortild is going to talk about: 'Regularization Methods for Hierarchical Programming'

We consider hierarchical variational inequality problems, or more generally, variational inequalities defined over the set of zeros of a monotone operator. This framework includes convex optimization over equilibrium constraints and equilibrium selection problems. In a real Hilbert space setting, we combine a Tikhonov regularization and a proximal penalization to develop a flexible double-loop method for which we prove asymptotic convergence and provide rate statements in terms of gap functions. Our method is flexible, and effectively accommodates a large class of structured operator splitting formulations for which fixed-point encodings are available. 

Joint work with Meggie Marschner, and Mathias Staudigl (University of Mannheim)

Insects use flight as far more than a means of getting from A to B. Flight creates an aeiral theatre for interaction, whether between species or among members of the same species. For example, a male dragonfly must hunt for food, fend off rival males, and pursue evasive females in order to reproduce, tasks that all revolve around chasing fast-moving targets. Despite the remarkable diversity of insect species and their aerial behaviours, common patterns emerge in how they exploit speed and manoeuvrability to achieve these goals. Simple geometric guidance laws can describe these flight trajectories with surprising accuracy, revealing shared strategies that underpin insect aerial combat.

Pseudo-Anosov flows are a rich class of dynamical systems on 3-manifolds which are studied for their deep connections to the geometry and topology of the underlying space. A modern tool for studying these flows is to capture them with combinatorial objects called veering triangulations. This correspondence lets us study the flows from a computational perspective. In this talk, I will first give an introduction to pseudo-Anosov flows and how they are captured by these ‘old’ triangulations. I will then give a ‘new’ triangulation which captures these flows in greater generality, giving us many new explicit examples. I will finish by discussing how to algorithmically pass between the old and the new.

In this talk, we give a construction of the Abelian Yang--Mills--Higgs measure on the two-dimensional torus via the variational approach initiated by Barashkov--Gubinelli. The construction is carried out through a disintegration of measures: we first construct the conditional Higgs measure given a rough gauge field, and then construct the gauge field marginal. This leads to iterated variational problems, one for the Higgs field and one for the gauge field. At the technical level, the starting point is the construction of the renormalised covariant Laplacian associated to a rough gauge field, together with the study of its resolvent. This allows us to define the covariant Gaussian free field, which serves as the reference Gaussian field for the conditional Higgs measure. Finally, we analyse the ratios of determinants that arise from the change-of-measure formula for Gaussian measures. This is joint work with Nikolay Barashkov, Ajay Chandra, Ilya Chevyrev, and Andreas Koller.
 

If you are curious about using your maths outside academia, want to learn new skills, or just want a change of pace from your PhD, then consider a policy internship. During a three-month UKRI policy internship at the Joint Nature Conservation Committee, I worked on assessing the impact of human-made underwater noise on harbour porpoises. I got to see what it was like to work for a government advisory body, and how scientific modelling is used to inform policy and real-world decision making, all whilst occasionally spotting dolphins from my office window. In this talk, I will describe my project and use it as a starting point to discuss internships more broadly: what you can gain from them, how they differ from academic research, and how to apply.

The study of combinatorial designs includes some of the oldest questions at the heart of combinatorics. In a breakthrough result of 2014, Keevash proved the longstanding Existence Conjecture by showing the existence of (n,q,r)-Steiner systems (equivalently K_q^r-decompositions of K_n^r) for all large enough n satisfying the necessary divisibility conditions. Meanwhile, in recent decades, incremental progress has been made on the celebrated Nash-Williams' Conjecture of 1970, which posits that any large enough, triangle-divisible graph on n vertices with minimum degree at least 3n/4 admits a triangle decomposition. In 2021, Glock, Kühn, and Osthus proposed a generalization of these results by conjecturing a hypergraph version of the Nash-Williams' Conjecture, where their proposed minimum degree K_q^r-decomposition threshold is motivated by hypergraph Turán theory. By using the recently developed method of refined absorption and establishing a non-uniform Turán theory, we tie the K_q^r-decomposition threshold to its fractional relaxation. Combined with the best-known fractional decomposition threshold from Delcourt, Lesgourgues, and Postle, this dramatically closes the gap between what was known and the above conjecture. This talk is based on joint work with Luke Postle.

Recurrent neural networks (RNNs) provide a theoretical framework for understanding computation in biological neural circuits, yet classical results, such as Hopfield's model of associative memory, rely on symmetric connectivity that restricts network dynamics to gradient-like flows. In contrast, biological networks support rich time-dependent behaviour facilitated by their asymmetry. In this talk, I will introduce a general framework, known as ‘drift-diffusion matching’, for training continuous-time RNNs to represent arbitrary stochastic dynamical systems within a low-dimensional latent subspace. Allowing asymmetric connectivity, I will show that RNNs can embed the drift and diffusion of an arbitrary stochastic differential equation, including nonlinear and nonequilibrium dynamics such as chaotic attractors. As an application, we have constructed RNN realisations of stochastic systems that transiently explore various attractors through both input-driven switching and autonomous transitions driven by nonequilibrium currents, which we interpret as models of associative and sequential (episodic) memory. To elucidate how these dynamics are encoded in the network, I will introduce decompositions of the RNN based on its asymmetric connectivity and its time-irreversibility. These results extend attractor neural network theory beyond equilibrium, showing that asymmetric neural populations can implement a broad class of dynamical computations within low-dimensional manifolds, unifying ideas from associative memory, nonequilibrium statistical mechanics, and neural computation.

Quantization is notoriously difficult and even when we have found quantizations of, say, coordinate rings of varieties, these often appear ad-hoc.  But, using ideas that were just emerging when the speaker was embarking on their research journey in the Institute some twenty years ago, a remarkable alternative approach has been developed. We will describe the journey, culminating in a recent result with Pressland showing that quantization and categorification are intimately linked. Braidings, grading and mirror symmetry also feature in our story.

The Hitchin equations are an integrable system in two-dimensions that plays a variety of important roles across mathematics and physics and this talk will start with some of this motivation.  It will go on to discuss how the 4d Chern-Simons of Costello, Witten and Yamazaki fits into ideas from  30-40 years ago that sought to unify the study of integrable systems via the study of the self-duality equations and their twistor constructions.  In particular 4d Chern-Simons provides a uniform approach to 2d integrable systems and their canonical structures.  The Hitchin equations have been missing in this approach and this talk will explain I will explain how Hitchin equations are incorporated with reductions to Toda and Sine Gordon, and  gives new approaches to understanding canonical strucures associated with these equations.  This talk is based on joint work with Roland Bittleston and Faroogh Moosavian https://arxiv.org/abs/2601.05309.

Everyone is invited to celebrate International Women in Mathematics Day with a pizza lunch! We will be watching ‘Journeys of Women in Mathematics’, a powerful 20-minute film by the International Mathematical Union showcasing the experiences of women mathematicians worldwide. It follows three mathematicians from India, Cameroon, and Brazil from their home institutions to the (WM)² international meeting, showing their research and what it’s like to be part of the global maths community.

We provide a derivation of the fourth-order DLSS equation based on an interpretation as a chemical reaction network. We consider on the discretized circle the rate equation for the process where pairs of particles sitting on the same side jump simultaneously to the two neighboring sites, and the reverse jump where a pair of particles sitting on a common site jump simultaneously to the side in the middle. Depending on the rates, in the vanishing mesh size limit we obtain either the classical DLSS equation or a variant with nonlinear mobility of power type. We identify the limiting gradient structure to be driven by entropy with respect to a generalization of the diffusive transport type with nonlinear mobility via EDP convergence. Furthermore, the DLSS equation with nonlinear mobility of the power type shares qualitative similarities with the fast diffusion and porous medium equations, since we find traveling wave solutions with algebraic tails and polynomial compact support, respectively.    
       

Joint work with Alexander Mielke and Artur Stephan arXiv:2510.07149. The DLSS part is based on joints works with Daniel Matthes, Eva-Maria Rott and Giuseppe Savaré.

We will begin with an overview of Stark's conjectures before discussing the case of imaginary quadratic fields, covering both the limit formula and the existence of elliptic units. The classical expositions of these are at times lacking in intuition, but thanks to Kato's deep insights 20 years ago, we can present more geometric and illuminating proofs of both results.

One can learn a lot about a compact manifold if one can show that it fibres over the circle - in essence, this allows us to view a static n-dimensional manifold as a manifold of dimension n-1 that evolves in time.Being fibred (over the circle) is a relatively rare property. It is much more common to be virtually fibred, that is, to admit a finite cover that is fibred. For example, it was the content of a conjecture of William Thurston, now two theorems by Ian Agol and Dani Wise, that all finite-volume hyperbolic 3-manifolds are virtually fibred; in fact, this property is extremely common among irreducible 3-manifolds.The situation is less clear in higher dimensions. On the obstruction side, we know that virtually fibred manifolds must have vanishing Euler characteristic. This immediately shows that compact hyperbolic manifolds in even dimensions will not be virtually fibred. A more involved obstruction comes from L2-homology: virtually fibred manifolds must be L2-acyclic. The motivation behind the research I will present lies in trying to find situations in which the vanishing of L2-homology is is not only necessary, but also sufficient for virtual fibring. It turns our that a lot more can be said if we replace aspherical manifolds by their homological cousins: Poincare duality groups. Concretely, if G is an n-dimensional Poincare-duality group over the rationals, and if G satisfies the RFRS property, then G is L2-acyclic if and only if there is a finite-index subgroup G0 of G and an epimorphism from G0 onto the integers such that its kernel is a Poincare-duality group over the rationals of dimension n-1. (This last theorem is joint with Sam Fisher and Giovanni Italiano.)The RFRS property was introduced in Agol's work on Thurston's conjecture. A countable group is RFRS if and only if it is residually {virtually abelian and poly-Z}. All compact special groups in the sense of Haglund-Wise satisfy this property, so there is a ready supply of RFRS groups, also among fundamental groups of hyperbolic manifolds in high dimensions.

We study the clustering behavior of weakly interacting diffusions under the influence of sufficiently localized attractive interaction potentials on the one-dimensional torus. We describe how this clustering behavior is closely related to the presence of discontinuous phase transitions in the mean-field PDE. For local attractive interactions, we employ a new variant of the strict Riesz rearrangement inequality to prove that all global minimizers of the free energy are either uniform or single-cluster states, in the sense that they are symmetrically decreasing. We analyze different timescales for the particle system and the mean-field (McKean-Vlasov) PDE, arguing that while the particle system can exhibit coarsening by both coalescence and diffusive mass exchange between clusters, the clusters in the mean-field PDE are unable to move and coarsening occurs via the mass exchange of clusters. By introducing a new model for this mass exchange, we argue that the PDE exhibits dynamical metastability. We conclude by presenting careful numerical experiments that demonstrate the validity of our model.

Given a Fano variety X with smooth anticanonical divisor D, one may consider the enumerative geometry of X, of the pair (X,D) or of D. A-model Quantum Lefschetz, Residue and Serre relate counts of genus 0 curves in X,  (X,D) and D. While the A-model statements are fairly involved, they become standard integral transforms when formulated as B-model correspondences within the Intrinsic Mirror Construction of Gross-Siebert. I will explain how this works. Time permitting, I will explain how for K-polystable del Pezzo surfaces, genus 0 log BPS instanton expansions transform into modular forms.

Associate Professor Nicolas Boumal will talk about: 'Smooth, globally Polyak-Łojasiewicz functions are nonlinear least-squares'

Polyak-Łojasiewicz (PŁ) functions abound in the literature, especially in nonconvex optimization. When they are also smooth, they become surprisingly simple---with an exotic twist. The plan is for us to discover the structure of those functions and of their sets of minimizers via gradient flow and fiber bundles.

Joint work with Christopher Criscitiello and Quentin Rebjock.

In a joint work with Yu Deng (University of Chicago) and Xiao Ma (University of Michigan), we extended Lanford’s theorem to long times—specifically, for as long as the solution of the Boltzmann equation exists. This allowed us to fully carry out Hilbert’s program and derive the fluid equations in the Boltzmann–Grad limit. The underlying strategy builds on earlier joint work with Yu Deng that resolved a parallel problem in which colliding particles are replaced by nonlinear waves, thereby establishing the mathematical foundations of wave turbulence theory. In this talk, we will review this progress and discuss some related problems and future directions. 

This week’s Fridays@2 session is intended to provide advice on exam preparation and how to approach the Part A, B, and C exams.  A panel consisting of past examiners and current students will answer any questions you might have as you approach exam season.

Drug discovery is slow and expensive, and a growing body of AI work tackles this by training generative models that propose new candidate molecules directly, searching chemical space far faster than a human chemist could. Most of this work has focused on standard small molecules, leaving more specialized but valuable classes underexplored.

Macrocycles are ring-shaped molecules that offer a promising alternative to small-molecule drugs due to their enhanced selectivity and binding affinity against difficult targets. Despite their chemical value, they remain underexplored in generative modeling, likely owing to their scarcity in public datasets and the challenges of enforcing topological constraints in standard deep generative models.

We introduce MacroGuide: Topological Guidance for Macrocycle Generation, a diffusion guidance mechanism that uses Persistent Homology to steer the sampling of pretrained molecular generative models toward the generation of macrocycles, in both unconditional and conditional (protein pocket) settings. At each denoising step, MacroGuide constructs a Vietoris-Rips complex from atomic positions and promotes ring formation by optimizing persistent homology features. Empirically, applying MacroGuide to pretrained diffusion models increases macrocycle generation rates from 1% to 99%, while matching or exceeding state-of-the-art performance on key quality metrics such as chemical validity, diversity, and PoseBusters checks.

Accepted to ICML 2026. Paper: https://arxiv.org/abs/2602.14977