The 2d (massless) Sinh-Gordon model is amongst the simplest 2d quantum field theories that are expected to be integrable (= infinitely many symmetries), but without conformal symmetry. In this talk I will explain a rigorous construction of this model and its vertex correlations (= Laplace transforms) on the infinite cylinder using probability theory. A fundamental role is played by the Sinh-Gordon Hamiltonian and I will explain how the theory of Gaussian multiplicative chaos can be used to analyze this linear map. This talk will be based on joint work with Colin Guillarmou and Vincent Vargas.

When doing arithmetic geometry, it is helpful to have invariants of the objects which we are studying that see both the arithmetic and the geometry. Motivic homotopy theory allows us to produce new invariants which generalise classical topological invariants, such as the Euler characteristic of a variety. These motivic invariants not only recover the classical topological ones, but also provide arithmetic information. In this talk, I'll review the construction of a motivic Euler characteristic, then study its arithmetic properties, and mention some applications. I'll then talk about work in progress with Ran Azouri, Stephen McKean and Anubhav Nanavaty which studies a "higher Euler characteristic", allowing us to produce an invariant of automorphisms valued in an arithmetically interesting group. I'll then talk about how to relate part of this invariant to a more classical invariant of quadratic forms.

You can cut a cake in half, a pizza into slices, but can you cut an infinite group? I'll tell you about my sensei's secret cutting technique and demonstrate a couple of examples. There might be some spectral goodies at the end too. 

In continuum kinetic models of quasineutral plasmas, binary collisions between particles are represented by the bilinear Fokker-Planck collision operator. In full-F kinetic models, which solve for the entire particle probability distribution function, it is important to correctly capture this operator, which pushes the system towards thermodynamic equilibrium. We show a multi-species, conservative, finite element implementation of this operator, using the continuum Galerkin representation, in the Julia programming language. A Jacobian-free-Newton-Krylov solver is used to implement a backward-Euler time advance. We present several example problems that demonstrate the performance of the implementation, and we speculate on future applications.

Optimal damping consists of identifying a viscosity vector that maximizes the decay rate of a mechanical system's response. This can be rephrased as minimizing the trace of the solution of a Lyapunov equation whose coefficient matrix, representing the system dynamics, depends on the dampers' viscosities. The latter must be nonnegative for a physically meaningful solution, and the system must be asymptotically stable at the solution.

In this talk, we present conditions under which the system is never stable or may not be stable for certain values of the viscosity vector, and, in the latter case, discuss how to modify the constraints so as to guarantee stability. We show that the KKT conditions of our nonlinear optimization problem are equivalent to a viscosity-dependent nonlinear residual function that is equal to zero at an optimal viscosity vector. To minimize this residual function, we propose a Barzilai-Borwein residual minimization algorithm (BBRMA) and a spectral projection gradient algorithm (SPG). The efficiency of both algorithms relies on a fast computation of the gradient for BBRMA, and both the objective function and its gradient for SPG. By fully exploiting the low-rank structure of the problem, we show how to compute these in $O(n^2)$ operations, $n$ being the size of the mechanical system.

This is joint work with Qingna Li (Beijing Institute of Technology).

I will discuss some of my work on thermal correlators in AdS/CFT. In particular, given a thermal correlator, how are the characteristic properties of bulk black holes encoded in such correlators? This includes exploring the spectrum of QNMs, the so-called thermal product formula, the photon ring, and geodesics bouncing off the black hole singularity. I will discuss how the latter might change when finite string effects are considered.

TBA

Cell and tissue movement during development, immune response, and cancer invasion depends on chemical or mechanical guidance cues. In many systems, this guidance arises not from long-range, pre-patterned cues but from self-generated gradients locally shaped by cells. However, how heterogeneous cell mixtures coordinate their migration by self-generated gradients remains largely unexplored. In this talk, I will first summarize our recent discovery that immune cells steer their long-range migration using self-generated chemotactic cues (Alanko et al., 2023). I will then introduce a multi-component Keller-Segel model that describes migration and patterning strategies of heterogeneous cell populations (Ucar et al., 2025). Our model predicts that the relative chemotactic sensitivities of different cell populations determine the shape and speed of traveling density waves, while boundary conditions such as external cell and attractant reservoirs substantially influence the migration dynamics. We quantitatively corroborate these predictions with in vitro experiments on co-migrating immune cell mixtures. Interestingly, immune cell co-migration occurs near the optimal parameter regime predicted by theory for coupled and colocalized migration. Finally, I will discuss the role of mechanical interactions, revealing a non-trivial interplay between chemotactic and mechanical non-reciprocity in driving collective migration.
 

This session will look at how you can get the most out of your lectures and tutorials. We’ll talk about how to prepare effectively, make lectures more productive, and understand what tutors expect from you during tutorials. You’ll leave with practical tips to help you study more confidently and make your learning time count.

This session is likely to be most relevant for first-year undergraduates, but all are welcome.

Mathematicians often like to think of maths as objective. Science communicator Hana Ayoob joins us to discuss how the fact that humans do maths means that the ways maths is developed, used, and communicated are not neutral.

Classical finite element methods discretize scalar functions using piecewise polynomials. Vector finite elements, such as those developed by Raviart-Thomas, Nédélec, and Brezzi-Douglas-Marini in the 1970s and 1980s, have since undergone significant theoretical advancements and found wide-ranging applications. Subsequently, Bossavit recognized that these finite element spaces are specific instances of Whitney’s discrete differential forms, which inspired the systematic development of Finite Element Exterior Calculus (FEEC). These discrete topological structures and patterns also emerge in fields like Topological Data Analysis.

In this talk, we present an overview of discrete and finite element differential forms motivated by applications from topological hydrodynamics, alongside recent advancements in tensorial finite elements. The Bernstein-Gelfand-Gelfand (BGG) sequences encode the algebraic and differential structures of tensorial problems, such as those encountered in solid mechanics, differential geometry, and general relativity. Discretization of the BGG sequences extends the periodic table of finite elements, originally developed for Whitney forms, to include Christiansen’s finite element interpretation of Regge calculus and various distributional finite elements for fluids and solids as special cases. This approach further illuminates connections between algebraic and geometric structures, generalized continuum models, finite elements, and discrete differential geometry.

Modern deep learning methods provide the state-of-the-art in image reconstruction in most areas of computational imaging. However, such techniques are very data hungry and in a number of key imaging problems access to ground truth data is challenging if not impossible. This has led to the emergence of a range of self-supervised learning algorithms for imaging that attempt to learn to image without ground truth data. 

In this talk I will review some of the existing techniques and look at what is and might be possible in self-supervised imaging.

I will discuss an ascending filtration on the Chow group of zero-cycles on a smooth projective variety obtained roughly by considering the successive kernels of the iterates of some modified diagonal embedding of the variety. This filtration is particularly relevant in the case of abelian varieties and of hyper-Kähler varieties, where it is expected to be opposite to the conjectural Bloch-Beilinson filtration. In the case of abelian varieties, it can in fact be described explicitly in terms of the Beauville decomposition, while in the case of hyper-Kähler varieties, I conjecture (and prove in some cases) that it coincides with a filtration introduced earlier by Claire Voisin. As a by-product we obtain in joint work with Olivier Martin a criterion involving second Chern classes for two effective zero-cycles on a moduli space of stable objects on a K3 surface to be rationally equivalent, generalising a result of Marian-Zhao.

I will relate two notorious open questions in low-dimensional topology.  The first asks whether every hyperbolic group is residually finite. The second, the congruence subgroup property, relates the finite-index subgroups of mapping class groups to the topology of the underlying surface. I will explain why, if every hyperbolic group is residually finite, then mapping class groups enjoy the congruence subgroup property. Time permitting, I may give some further applications to the question of whether hyperbolic 3-manifolds are determined by the finite quotients of their fundamental groups.

We consider targeted intervention problems in dynamic network and graphon games. First, we study a general dynamic network game in which players interact over a graph and seek to maximize their heterogeneous, concave goal functionals. We establish the existence and uniqueness of a Nash equilibrium in both the finite-player network game and the corresponding infinite-player graphon game, and prove its convergence as the number of players tends to infinity. We then introduce a central planner who implements a dynamic targeted intervention. Given a fixed budget, the central planner maximizes the average welfare at equilibrium by perturbing the players' heterogeneous goal functionals. Using a novel fixed-point argument, we prove the existence and uniqueness of an optimal intervention in the graphon setting, and show that it achieves near-optimal performance in large finite networks. Finally, we study the special case of linear-quadratic goal functionals and derive semi-explicit solutions for the optimal intervention.

 

This is a joint work with Sturmius Tuschmann.  

Equations of fluctuating hydrodynamics, also called Dean-Kawasaki type equations, are stochastic PDEs describing the evolution of finitely many interacting particles which obey a Langevin equation. First, we give a mathematical derivation for such equations. The focus is on systems of interacting particles described by second order Langevin equations. For such systems,  the equations of fluctuating hydrodynamics are a stochastic variant of Vlasov-Fokker-Planck equations, where the noise is white in space and time, conservative and multiplicative. We show a dichotomy previously known for purely diffusive systems holds here as well: Solutions exist only for suitable atomic initial data, but provably not for any other initial data. The class of systems covered includes several models of active matter. We will also discuss regularisations, where existence results hold under weaker assumptions. 

Introduced by Lusztig in the eighties, character sheaves are the geometrical counterpart of irreducible representations of finite groups of Lie type. Defined over algebraic groups, they allow us to use geometrical tools to deduce information on the finite groups. In this talk, Marie Roth will give a definition of character sheaves before explaining how to compute their restriction to conjugacy classes (to some extent). This work was part of her PhD thesis under the supervision of Olivier Dudas and Gunter Malle.

Consider a tail trivial, positively associated site percolation process such that the set of open vertices is stochastically dominated by the set of closed ones. We show that, for any planar graph $G$, such a process must contain zero or infinitely many infinite connected components. The assumptions cover Bernoulli site percolation at parameter $p$ less than or equal to one half, resolving a conjecture of Benjamini and Schramm. As a corollary, we prove that $p_c$ is greater than or equal to $1/2$ for any unimodular, invariantly amenable planar graphs.

We will then apply this percolation statement to the loop $O(n)$ model on the hexagonal lattice, and show that, whenever $n$ is between $1$ and $2$ and $x$ is between $1/\sqrt{2}$ and $1$, the model exhibits infinitely many loops surrounding every face of the lattice, giving strong evidence for conformally invariant behavior in the scaling limit (as conjectured by Nienhuis).

This is joint work with Alexander Glazman (University of Innsbruck) and Nathan Zelesko (Northeastern University).

Logarithmic and orbifold structures provide two independent ways to model curves in a variety with tangency along a normal crossings divisor. The associated systems of Gromov-Witten invariants benefit from complementary techniques; this has motivated extensive interest in comparing the two approaches.

I will report on work in which we establish a complete comparison which, crucially, incorporates negative tangency orders. Negative tangency orders appear naturally in the boundary splitting formalisms of both theories. As such, our comparison opens the way for the wholesale importation of techniques from one side to the other. Work of Sam Johnston uses our comparison to give a new proof of the associativity of the Gross-Siebert intrinsic mirror ring.

Along the way, I will discuss the pathological geometry of negative tangency mapping spaces, and how this can be understood and controlled via tropical geometry. A crucial contribution of our work is the discovery of a "refined virtual class" on the logarithmic moduli space, which gives rise to a distinguished sector of the Gromov-Witten theory.

This is joint work with Luca Battistella and Dhruv Ranganathan.

What do the roots of random polynomials look like? Classical works of Erdős-Turán and others show that most roots are near the unit circle and they are approximately rotationally equidistributed. We will begin with an understanding of why this happens and see how ideas from extremal combinatorics can mix with analytic and probabilistic arguments to show this. Another main feature of random polynomials is that their roots tend to "repel" each other. We will see various quantitative statements that make this rigorous. In particular, we will study the smallest separation $m_n$ between pairs of roots and show that typically $m_n$ is on the order of $n^{-5/4}$. We will see why this reflects repulsion between roots and discuss where this repulsion comes from. This is based on joint work with Oren Yakir.

to follow

A discussion on how race and ethnicity interact with the concept of merit in academia, based on sections from the book 'Misconceiving Merit' by Blair-Loy and Cech. 

In this talk, we will explore three flow configurations that illustrate the behaviour of slow-moving viscous fluids in confined geometries: viscous gravity currents, fracturing of shear-thinning fluids in a Hele-Shaw cell, and rectangular channel flows of non-Newtonian fluids. We will first develop simple mathematical models to describe each setup, and then we will compare the theoretical predictions from these models with laboratory experiments. As is often the case, we will see that even models that are grounded in solid physical principles often fail to accurately predict the real-world flow behaviour. Our aim is to identify the primary physical mechanisms absent from the model using laboratory experiments. We will then refine the mathematical models and see whether better agreement between theory and experiment can be achieved.

TBA

TBC

Several interesting and emerging problems in statistics, machine learning and optimal transport can be cast as minimisation of (entropy-regularised) objective functions defined on an appropriate space of probability distributions.  Numerical methods have historically focused on linear objective functions, a setting in which one has access to an unnormalised density for the distributional target.  For nonlinear objectives, numerical methods are relatively under-developed; for example, mean-field Langevin dynamics is considered state-of-the-art.  In the nonlinear setting even basic questions, such as how to tell whether or not a sequence of numerical approximations has practically converged, remain unanswered.  Our main contribution is to present the first computable measure of sub-optimality for optimisation in this context.  

Joint work with Clémentine Chazal, Heishiro Kanagawa, Zheyang Shen and Anna Korba.

The machinery of Euler systems (originating in the work of Kolyvagin and Thaine in the late 1980s) is an extremely powerful tool for studying the cohomology of Galois representations, and hence for attacking big conjectures such as Birch–Swinnerton-Dyer. However, current approaches to this theory require the Galois representation to satisfy some sort of "ordinarity" condition, which is a serious restriction in applications. I will discuss recent joint work with Sarah Zerbes in which we extend the Euler system machine to cover situations where this ordinary condition doesn't hold, using a surprising new ingredient (adapted from earlier work of Naomi Sweeting): non-principal ultrafilters, which serve to keep track of the sequences of auxiliary primes arising in Kolyvagin's argument. Applications of this theory, including new cases of the Iwasawa main conjecture, will be discussed in Sarah's talk later the same afternoon.

to follow

The development of a complex functional multicellular organism from a single cell involves tightly regulated and coordinated cell behaviours coupled through short- and long-range biochemical and mechanical signals. To truly comprehend this complexity, alongside experimental approaches we need mathematical and computational models, which can link observations to mechanisms in a quantitative, predictive, and experimentally verifiable way. In this talk I will describe our efforts to model aspects of embryonic development, focusing in particular on the planar polarised behaviours of cells in epithelial tissues, and discuss the mathematical and computational challenges associated with this work. I will also highlight some of our work to improve the reproducibility and re-use of such models through the ongoing development of Chaste (https://github.com/chaste), an open-source C++ library for multiscale modelling of biological tissues and cell populations.

This week's Fridays@2 will be a panel discussion focusing on what it is like to pursue a research degree. The panel will share their thoughts and experiences in a question-and-answer session, discussing some of the practicalities of being a postgraduate student, and where a research degree might lead afterwards.

A conjecture of Holzegel, Schmelzer and Warnick states that there is a Ricci flow with surgery connecting the two Ricci flat metrics Taub-Bolt and Taub-NUT. We will present some recent progress towards proving this conjecture. This includes showing for the first time the existence of a Ricci flow with surgery with local topology change $\mathbb{CP}^2\setminus\{ \mathrm{pt}\} \rightarrow \mathbb{R}^4$.