Past

The celebrated additive kinematic formula expresses the mean volume of the Minkowski sum of two compact convex subsets of the Euclidean space placed at random. What about non convex subsets? What about other Lie groups than the Euclidean space? In a joint work with Andreas Bernig, we prove additive kinematic formulas for compact subanalytic sets of the Euclidean space and of the 3-sphere. The key is to generalize the Minkowski sum of convex bodies by a notion of convolution of subanalytic sets introduced by Schapira in the late 80s using Euler characteristic computations. The above will of course be an excuse to discuss integral geometric formulas and constructible functions.

In this talk, I will focus on a new construction of boundary correlators (or wavefunction coefficients in dS) that highlights simplicity at all spins and automatically imposes the conservation of boundary currents. This new construction is formulated in twistor space, a complex projective space that encodes solutions to equations of motion as holomorphic data. This is done via an isomorphism called the Penrose transform. First, I will discuss the case of AdS_3 and AdS_5, where bulk-to-boundary correlators naturally arise in minitwistor space. Then, I will show how in (A)dS₄ one can construct bulk correlation functions using only twistors, dual twistors, and the infinity twistor as building blocks. The relation to coordinate space arises now via nested Penrose transforms. The boundary limit of these correlators yields CFT correlators/wavefunction coefficients that satisfy the expected Ward identities. Finally, I will briefly discuss how this can be generalized to AdS_5 boundary correlators using ambitwistors.

Mechanistic ordinary differential equation (ODE) models are a powerful tool to study dynamic biological systems. However, their predictive power is constrained by gaps, biases, and inconsistencies in the literature. They typically also require quantitative time-lapse data for training, which is time-consuming to collect. At the same time, machine-learning approaches can capture complex patterns from data, but they are often harder to interpret and typically require large training datasets. Hybrid scientific machine learning (SciML) models offer a promising way to combine the strengths of both approaches by integrating mechanistic models with flexible data-driven modules. 
Despite this promise, the use of SciML in biology remains limited by insufficient infrastructure. Dedicated software is needed because coding end-to-end differentiable workflows for gradient-based training of hybrid models is technically challenging. In addition, model exchange is hindered by the lack of a standardized, reproducible format for specifying SciML training problems, analogous to the PEtab standard for ODE models. To address these challenges, we developed PEtab-SciML, an extension of the PEtab format, and implemented support for it in the state-of-the-art modeling toolboxes PEtab.jl and AMICI. In this seminar, I will introduce the PEtab-SciML format. Using real-data examples, I will show how PEtab-SciML enables the integration of diverse data modalities into dynamic model training; such as learning the kinetic parameters of an ODE model from omics and protein sequence data. I will also show how it supports machine-learning-based black-boxing of complex model components, such as quarantine strength in an SIR model. Finally, I will show how PEtab-SciML enables the use of efficient training strategies, such as curriculum learning, that make SciML models easier to train and apply in practice. 

Stability is the prototypical model theoretic dividing line. One interpretation is that a binary relation is stable if it is "close to unary": if the question $(x,y)\in E$ can be answered, at least most of the time, by knowing enough information about $x$, and separately enough information about $y$.

One natural question is asking how this can generalize to ternary (and higher-arity) relations. The connection to hypergraph regularity suggests an approach to identifying ternary stable-like properties, and also that there should be several versions, since a ternary relation could be almost unary, or almost binary, or a combination of these properties.

In this talk, I'll survey some of what we know about several of these "stable-like" ternary notions.

In many prediction and decision problems, the relevant inputs are path-valued covariates rather than static feature vectors. This paper studies asymptotic theory and empirical applications for path regression using signatures. We first establish \(L^2\) approximation rates for truncated signature representations. We prove a minimax-optimal approximation rate over a class of smooth coefficient functionals of observable It\^{o} diffusions. Building on this approximation theory, we then develop asymptotic results for three signature-based learning procedures: Signature-OLS, Signature-LASSO, and Signature-Logistic. These results establish asymptotic normality for least-squares path regression, sparse recovery for high-dimensional signature regression, and latent-score consistency for binary-response classification. Extensive empirical studies cover three real-data applications: foreign-exchange realized-volatility forecasting from intraday price paths, battery end-of-life prediction from early HPPC pulse paths, and epileptic seizure detection from short EEG windows. The empirical results show that signatures provide informative representations of path-valued covariates relative to handcrafted features.

Understanding the behaviour of L-functions of modular forms is a very classical and yet open problem. The Bloch-Kato conjecture predicts that the order of vanishing of the L-function of a modular form should be given by the rank of certain Bloch-Kato Selmer groups. In order to give a lower bound to these ranks in certain cases where the L-function vanishes, Bellaiche and Chenevier developed a clever strategy where they construct classes in the Selmer group via the geometry of points corresponding to certain lifts of modular forms on higher dimensional eigenvarieties. This strategy was successfully adapted for ordinary modular forms by Berger and Betina to give a lower bound in terms of the smoothness of Saito-Kurokawa points on a genus 2 Siegel eigenvariety. We generalise this work to finite slope and crucially infinite slope forms which are not seen on the Coleman-Mazur eigencurve - here we must develop the machinery of small parabolic eigenvarieties for the problem to be well defined. As a result we get new results towards the Bloch—Kato conjecture for infinite slope forms.

The ε-energy is a regularisation of the Dirichlet energy introduced by Tobias Lamm. Like the famous Sacks-Uhlenbeck regularisation this greatly improves the existence and regularity theory. When we take the limit of a sequence of ε-harmonic maps with the parameter ε decreasing to 0 these converge, in the standard bubbling sense, to harmonic maps, which we hope to extract information about. I will talk about some recent results for these sequences, being when we might hope to have no loss of energy and no neck forming and what sort of harmonic maps we can obtain in the limit.

Professor De Terran will talk about: 'New results on the inclusion of closure orbits and bundles of matrices and matrix pencils' 

Orbits of nxn matrices under similarity are sets of matrices with the same Jordan Canonical form (JCF). When computing the JCF (or just the eigenvalues) of a matrix, the knowledge of all possible JCFs of small perturbations of a given JCF can help to understand the output of the algorithm, which is affected by roundoff errors.

The JCFs that can be obtained after small perturbations of a given JCF, say J, correspond to orbits that ``dominate" the orbit of J. In other words, the orbit of J is in the closure of its dominant orbits. The hierarchy of orbit closures of general matrices is well-known, as well as that of the set of matrices with bounded rank.

For matrix pencils (namely, pairs of matrices with the same size) the inclusion relationship between orbit closures has been also considered since, at least the 1980's. In this case, the standard equivalence relation is the so-called strict equivalence, which preserves the eigenstructure of the pencil, and the canonical form for this relation is the Kronecker canonical form (KCF). The hierarchy of orbit closures of general pencils under strict equivalence is also well-known. However, when the pencil has some particular structure (e. g., symmetric or Hermitian) then we encounter a different problem if we want the perturbations to maintain this structure. Some effort has been devoted in recent years to the analysis of orbit closures of structured pencils.

In this talk, we will review some recent results on the inclusion relationship between orbit closures of general and bounded-rank structured matrix pencils. We will also consider the inclusion relation of bundle closures. Bundles are generalizations of orbits, allowing the eigenvalues to change, while keeping the KCF. 
 

Global symmetries have been generalized to non-invertible ones. For finite symmetries in $(1+1)$d, these are known as unitary fusion category symmetries. One natural question is: which fusion categories can arise as symmetries on a lattice? 
Progress has been made including the anyon chains, which realizes any fusion category symmetries. However, their Hilbert spaces do not admit the usual tensor product structure (tensor product of local Hilbert spaces over each site).
In [arxiv:2507.05185], Evans and Jones introduced an operator-algebraic framework and showed that a fusion category symmetry can be realized on a tensor product quasi-local algebra if and only if it is "integral". After reviewing this result, I will discuss a recent extension by Bunner and Jones [arxiv:2605.21327], who showed that this constraint disappears after stabilization with infinite-dimensional ancilla spaces on anyon chains. As a consequence, every unitary fusion category can be realized on tensor product Hilbert spaces.

Lorenzo Lazzarino will talk about: 'Error estimations for randomized low-rank approximations'

Randomized algorithms in numerical linear algebra have proven to be effective in ameliorating issues of scalability when working with large matrices, efficiently producing accurate low-rank approximations. A key remaining challenge, however, is to efficiently assess the approximation accuracy of randomized methods without additional expensive matrix accesses.

In this talk, we discuss a posteriori error estimation strategies for randomized low-rank approximations, with a focus on estimators that can be constructed from the same data used to compute the approximation or without matrix global accesses. These can serve both as certification tools and as algorithmic building blocks, enabling adaptive approximations and informed trade-offs between accuracy and computational cost. As a motivation and a case study, we include a discussion on spectromicroscopy experiments.

More than seventy years after its publication, Turing’s article “The Chemical Basis of Morphogenesis” is still able to surprise its reader, in particular for the power and the depth of its vision. If we know from his biographer, Andrew Hodges, that Turing became interested in embryology and morphogenesis because he wanted to build or, better, to grow a brain, many questions still arise for the reader of the original article: why did Turing – a mathematician, a logician, a cryptographer, one of the fathers of computer science – not use any informational metaphor associated with the notion of “genetic program” in his work on morphogenesis, preferring instead to develop a modelling approach based on a system of partial differential equations ? Where did he draw his modelling inspiration from, both from the point of view of the mathematics and from the point of view of references to biology ? In my presentation I will address these questions by highlighting the morphological connotations of Turing’s work in biology, that can be related to Turing’s interest, in D’Arcy Wentworth Thompson’s classic On Growth and Form (1917). The 1952 article is rather sparse in indications in this regard, which are, however, provided by Turing’s other writings, unpublished during his lifetime, in which he situates his work in continuity with Thompson’s morphological questions. I will also suggest that, as in a virtuous circle, Turing masterfully brings to life a synergy between a morphological look at the living (that implies that his work has a connotation in theoretical biology) and a mathematical exploration of the non-linear, helped by an appropriate and meaningful use of numerical calculus. 

In this talk, I will introduce the concept of Archimedean closedness - a concept from real non-commutative algebraic geometry which determines when "positivity" of an element (captured through *-representations) in a *-algebra can be completely certified algebraically. On the other hand, property FD is a representation theoretic property of groups depicting when any representation of a group can be approximated by finite representations in the unitary dual. I will try to connect these two seemingly very different concepts through some examples and speculations. This is a work in progress.

Given a quantum field theory, realising its global symmetries and anomalies on a lattice has been a fruitful approach to gain new insights of these symmetries. In this talk, we present an exact lattice model in 2+1D which hosts an exact microscopic avatar of its low-energy SU(2) valley symmetry and parity anomaly. We first show that our lattice model has a Lieb-Schultz-Mattis (LSM) anomaly of the “Onsager symmetries” in the UV, which indeed enforces that every Hamiltonian which is symmetric has to be gapless. We then show that the SU(2) Parity anomaly on the IR can be exactly matched by this LSM anomaly. Finally, we briefly discuss our results in relation to similar anomaly matching schemes in 1+1D and 3+1D. 

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 noise. This mini course  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 critical Fortuin–Kasteleyn random planar map with parameter q>0 is a model of random (discretised) surfaces decorated by loops, related to the q-state Potts model. For q<4, Sheffield established a scaling limit result for these discretised surfaces, where the limit is described by a so-called Liouville quantum gravity surface decorated by a conformal loop ensemble. At q=4 a phase transition occurs, and the correct rescaling needed to obtain a limit has so far remained unclear. I will talk about joint work with William Da Silva, XinJiang Hu, and Mo Dick Wong, where we identify the right rescaling at this critical value and prove a number of convergence results.

In the context of Fourier analysis on the real line, a \textit{one-sided problem} involves deducing properties of a function $f$ from some information about the restriction of its Fourier transform $\widehat{f}$ to a half-line, for instance to $\mathbb{R}_- := (-\infty, 0)$. A prototypical result, which is foundational to the theory of Hardy spaces on $\mathbb{R}$, asserts that if $f \in L^2(\mathbb{R})$ is non-zero and $\widehat{f}$ vanishes on a half-line, then $f$ satisfies the \textit{Szeg\H{o} condition} $\int_{-\infty}^\infty \frac{\log |f(x)|}{1+x^2} \, dx > -\infty$. 

Various problems in operator theory involve the study of functions $f$ satisfying a weaker condition of decay of $\widehat{f}$ on a half-line. In this setting, simple examples show that the Szeg\H{o} condition need not be satisfied. However, the following local Szeg\H{o}-type conditions hold: if the decay of $\widehat{f}$ is strong enough on a half-line, then the mass of the function $f \in L^2(\mathbb{R})$ must concentrate enough for the integral $\int_E \log |f(x)| dx$ to converge on a "massive" set $E$. 

In his talk, Bartosz Malman will describe this mass condensation phenomenon and its applications to operator-theoretic problems.

The `conifold gap' conjecture asserts that the polar part of the Gromov-Witten potential of a Calabi-Yau threefold near its conifold locus has a universal expression described by the logarithm of the Barnes G-function. In this talk I will describe a proof of the Conifold Gap Conjecture for the local projective plane, whereby the higher genus conifold Gromov-Witten generating series of local P2 are related to the thermodynamics of a certain statistical mechanical ensemble of repulsive particles on the positive half-line. As a corollary, this establishes the all-genus mirror principle for local P2 through the direct integration of the BCOV holomorphic anomaly equations.

Clean markings on surfaces were a key component in Masur and Minsky's hierarchy machinery, which proved to be a powerful tool in the study of mapping class groups. In this talk, I will briefly discuss the connection between clean markings and hierarchies, and I will explain how a natural analogue can be constructed for finite-type Artin groups.

We present a new dynamical way of establishing local laws for sparse random matrices, the Bernoulli flow method. It is based on a Markovian jump process, where the entries of the matrix jump independently from 0 to 1 at rate one. As an application, we show optimal (up to a constant) isotropic delocalisation for bulk eigenvectors of Erdös-Rényi graphs with edge probability p \geq (log N)^2/N. In the same regime, we obtain a local law with optimal (up to a constant) error bounds. Joint work with Antti Knowles.

Ken Brown reviews the history of the question in the title, and describes some recent progress towards answering it, including the identification of a "minimal criminal". The new material is joint work with Jason Bell (Waterloo) and Toby Stafford (Manchester).

Many systems in the natural sciences and beyond exhibit complex relational structure that changes over time. Social networks evolve as relationships change, traffic patterns vary throughout the day, and protein–protein interactions shift with cellular conditions. Learning these dynamics from data is a challenging problem. A recent approach in this area, Graph Neural Controlled Differential Equations, extends Neural CDEs from paths on Euclidean domains to paths on graph domains. In this talk, we discuss an extension of this framework that respects the geometry of the underlying set and is equivariant to permutations of the node ordering. We will discuss empirical advantages of this modification, as well as benefits of the formulation as a continuous-time model. 

Schwinger’s Closed Time Path formalism is the basis of modern treatments of cosmological field theories, hydrodynamics and open quantum systems. Its application to gauge theories at finite temperature is well studied, relying on KMS boundary conditions and complex-time contours. By contrast the discussion of gauge theories such as Yang-Mills out of equilibrium has been less well developed, in large part due to a lack of development of how to treat gauge issues and Faddeev-Popov-DeWitt ghosts on the CTP. I will show how to construct the CTP in the BRST formalism, where a single diagonal copy of BRST symmetry survives, and how to implement the boundary conditions for ghosts for arbitrary initial physical states. As an illustration I will discuss how Hard-thermal-loop EFTs can be viewed as open quantum systems, and how to construct an open EFT for a gauge theory in a Higgs phase. 

The cylindrical snap-fit is a ubiquitous fastening method that is both simple to manufacture and assemble, and yet secure. It consists of a partial cylindrical shell that ‘snaps’ onto a cylindrical object. We build on previous work to describe the mechanics of the cylindrical snap-fit as a naturally curved thin elastic shell placed atop a rigid cylinder; we investigate the shell's behaviour when subject to a point force pushing it onto or pulling it off the cylinder. We classify the possible contact regimes according to whether the shell has a nonzero lifting capacity. We term situations with lifting capacity ‘grip-fits’ and show that this includes both the snap-fit and a ‘stick-fit’ regime, which allows lifting despite not having the characteristic ‘snap’. We show that the different regimes may be characterized entirely by the shell/cylinder geometry and the coefficient of friction. We then consider different metrics for the lifting performance in the grip-fit regime. Our analysis reveals the trade-offs between assembly force, disassembly force, lifting force, and clamping force, providing design principles for secure lifting, easy detachment, and safe handling of fragile objects.

I will discuss some general PDE techniques, for example ``extended substitute kernel'' and ``linearized gluing'', and their application to various gluing constructions in Differential Geometry.

This paper advances the theory of \textit{Collective Finance}, as developed in \cite{BDFFM26}, \cite{DFM25} and \cite{F25}. Within a general semimartingale framework, we study the relationship between collective market efficiency and individual rationality. We derive necessary and sufficient condition for the existence of (possibly zero-sum) exchanges among agents that strictly increase their indirect utilities and characterize this condition in terms of the compatibility between agents’ preferences and collective pricing measures. The framework applies to both continuous and discrete-time models and clarifies when cooperation leads to a strict improvement in each participating agent’s indirect utility.

Fox’s trapezoidal conjecture, proposed in 1962, states that the absolute values of the coefficients of the Alexander polynomial of an alternating knot form a trapezoidal sequence: they strictly increase, possibly plateau, and then strictly decrease. In this talk, I will discuss recent progress on the conjecture, based on joint work with András Juhász and Tamás Kálmán. In particular, we prove the conjecture for diagrammatic plumbings of special alternating links and obtain partial results for alternating three-braid closures

Professor Nicolas Loizou will talk about: 'Extragradient Methods for Modern Machine Learning: New Convergence Guarantees, Step-Size Rules, and Stochastic Variants'

Extragradient methods are a fundamental class of algorithms for solving min-max optimization problems and variational inequalities. While the classical theory is largely developed under smoothness and other relatively restrictive assumptions, many problems arising in modern machine learning call for analysis in weaker regularity regimes and in stochastic large-scale settings. In this talk, we present new convergence results for deterministic and stochastic extragradient methods beyond the classical framework. In particular, we establish convergence guarantees under the (L0, L1)-Lipschitz condition and derive new step-size rules that expand the range of provably convergent regimes. We also introduce Polyak-type step sizes for deterministic and stochastic extragradient methods, leading to adaptive variants with favourable theoretical properties and practical performance. Our results focus primarily on monotone problems, with extensions to selected structured non-monotone settings. We conclude with numerical experiments that illustrate the theory and the empirical behaviour of the proposed methods.

Much recent research has gone into understanding the first order theory of II1 factors. Very recently, Peterson released a preprint which develops deformation rigidity in the ultrapower setting. His techniques give many explicit examples of non-isomorphic ultrapowers for natural families of II1 factors. In this talk, I will introduce some of Peterson's techniques and results, including an analogue of amenability in the ultrapower setting and the interplay between property T and malleable deformations.

I will report on a joint work in progress with Egor Morozov proving that for generic elements in several families of Laplace-type operators invariant under a finite group action, all eigenspaces are irreducible representations. In particular, for the case of Laplace-Beltrami operators, this provides a natural generalization of Uhlenbeck's result on the generic simplicity of the spectrum to the equivariant setting. Moreover, this extends previous work of Zelditch and solves the finite group case of a well-known question raised by Guillemin and Yau. For Schrödinger operators, our results rigorously underpin the notion of accidental degeneracy for certain quantum-mechanical systems with finite symmetry. Our approach involves modern methods of equivariant transversality which we extend to higher dimensions.

For any manifold, we can assign its mapping class group, that is, the group of its diffeomorphisms modulo isotopies. Although such a group can be studied for manifolds of any dimension, the mapping class groups of surfaces draw special attention. They are isomorphic to the outer automorphism groups of $\pi_1(S)$ and have many properties similar to lattices in semisimple Lie groups, as well as connections with the theory of moduli of curves.

One of the most important parts of the research on mapping class groups is the study of their representation. In particular, in the general situation, we still don't know if they have a faithful representation into $\operatorname{GL}_n(\mathbb{C})$.

In my talk, I will show basic facts about mapping class groups and briefly describe a few known methods for constructing their representations and discuss their properties. In particular, I will present recent results classifying low-dimensional representations of the mapping class group.

Many cells exhibit exponential growth not only at the population level but also at the single-cell level. However, single-cell growth rates fluctuate over time. We distinguish between two conceptually distinct sources of growth rate fluctuations: intrinsic continuous fluctuations resulting from intracellular processes, and fluctuations that originate at division events, which we refer to as kicks. We use a simple model to describe single-cell growth and identify the signatures of continuous noise and division kicks. To infer the true biological behavior reliably from experiments, it is crucial to account for measurement noise. We derive analytical expressions for the statistics of meaningful observables, accounting for continuous fluctuations, division kicks, and measurement noise. Importantly, we find that ignoring measurement noise can lead to incorrect biological conclusions. Our results provide insights into how different sources of growth rate variability and measurement errors influence observed cell size dynamics, offering an interpretable framework for analyzing experimental data in cellular biology. 

Professor Luis Nunes Vicente will talk about 'Reducing Sample Complexity in Stochastic Derivative-Free Optimization via Tail Bounds and Hypothesis Testing';

We introduce and analyze new probabilistic strategies for enforcing sufficient decrease conditions in stochastic derivative-free optimization, with the goal of reducing sample complexity and simplifying convergence analysis. First, we develop a new tail bound condition imposed on the estimated reduction in function value, which permits flexible selection of the power used in the sufficient decrease test, q in (1,2]. This approach allows us to reduce the number of samples per iteration from the standard O(delta^{−4}) to O(delta^{-2q}), assuming that the noise moment of order q/(q-1) is bounded. Second, we formulate the sufficient decrease condition as a sequential hypothesis testing problem, in which the algorithm adaptively collects samples until the evidence suffices to accept or reject a candidate step. This test provides statistical guarantees on decision errors and can further reduce the required sample size, particularly in the Gaussian noise setting, where it can approach O(delta^{−2-r}) when the decrease is of the order of delta^r. We incorporate both techniques into stochastic direct-search and trust-region methods for potentially non-smooth, noisy objective functions, and establish their global convergence rates and properties. 

This is joint work with Anjie Ding, Francesco Rinaldi, and Damiano Zeffiro.

Quantum magic quantifies the computational resources needed for quantum operations that cannot be easily performed classically. This requires unitaries, known as "Non-Clifford gates", that map Pauli operators to outside the Pauli group. I will first provide a pedagogical introduction to these concepts following [arXiv:quant-ph/9807006] and then summarise the recent results of [arXiv:2604.14271] constructing non-Clifford gates from path integrals in Chern-Simons theories, whose magic-generating properties are determined by the algebraic data of the topological field theory.

India Marsden will talk about: 'Expanding the definition of a finite element: groups, complexes and software'

The finite element method is a flexible framework to discretise and solve partial differential equations which has been applied to many problems across science and engineering, for example weather modelling and battery design. A core feature of the success of the finite element method, the Ciarlet definition of the components of a finite element has been used for many years. The experience of these decades (and the subsequent implementations) has exposed several key deficiencies. In particular, Ciarlet’s definition is missing information about the global continuity of the mesh and how the degrees of freedom map to each other under the relative orientation of the mesh entities. This information is necessary to implement the finite element method, leaving scope for a new definition.

We propose a new definition to handle these issues and incorporate the constantly growing landscape of new elements. This new definition also aims to encapsulate more information about the elements, such as the symmetries, incorporating ideas from Group Theory. Through this work, we hope to produce a robust, thorough definition that allows processes such as implementation-independent serialisation of finite element data.

Alongside this new definition, we will discuss the new software FUSE, which provides a domain specific language for the definition and enables elements defined in this way to be used in high performance simulation using the finite element package Firedrake. 

Core-annular flows are often proposed to reduce frictional losses in industrial pipeline transport processes. Traditionally, a low-viscosity lubricating film is placed around a more viscous core to reduce the drag on the core. However, maintaining stable pipelining, where the core and the lubricant remain separated has proved challenging.
In this talk we present an alternative approach using three-layer, horizontal core-annular pipe flow, in which two fluids are separated by a deformable elastic solid. In the experiments, an elastic solid created by an in-situ chemical reaction maintains the separation of the core and annular fluids. Corrugations of the elastic interface are observed and stable pipelining, where the elastic shell created separating the two fluids remains intact, is successfully demonstrated even when the core fluid is buoyant. We also develop a theoretical model combining lubrication theory for the fluids with standard shell theory for the elastic solid, to predict the buckling states resulting from radial compression of the shell.
The self-sculpting of the shell by buckling cannot by itself generate hydrodynamic lift owing to symmetry in the direction of flow. Instead, we demonstrate that hydrodynamic lift can be achieved by other elastohydrodynamic effects, when that symmetry becomes broken during the bending of the shell.

Abstract elementary classes (AECs) provide an extension of first order model theory in which we can still attempt a classification theory. The question of when limit models (a kind of surrogate for saturated models for AECs) are isomorphic has connections to important open problems in AECs, such as Shelah's categoricity conjecture. Most work in this area is towards 'positive' results - that is, showing limit models are isomorphic. The question of when limit models are not isomorphic is less explored.

In this talk we give a full characterisation of the spectrum of limit models under reasonable assumptions in a stable AEC - that is, describe completely which limit models are isomorphic and which are not. In particular this applies to the first order stable setting. Given time we will discuss applications, a more general result in the 'positive' direction, and touch on a recent result which says that all high cofinality limit models are disjoint amalgamation bases. Based largely on joint work with Marcos Mazari-Armida.

I will give a short introduction to knotted surfaces in 4-space and discuss some recent developments. First, I will give some motivation, briefly discuss methods for distinguishing knotted surfaces (such as the Khovanov TQFT), and talk about connections with 4-manifolds. Then, I will introduce Artin’s spinning construction, variants of which were defined by Zeeman, Fox, Litherland, and Price-Roseman. Finally, I will specialize to knotted RP^2’s in S^4 and construct a knotted RP^2 in S^4 that cannot be decomposed as the connected sum of an unknotted RP^2 and a knotted S^2. This last result on RP^2’s is joint with Hughes, Kim, and Miller.

Two hundred years ago, Robert Brown observed the statistics of the motion of grains of pollen in water. It took almost one hundred years for Einstein and others to develop an effective theory describing this motion as that of a random walker. In this talk, I will challenge a key implication of this well established theory. When studying systems with very large numbers of particles diffusing together, I will argue that the Einstein random walk theory breaks down when it comes to predicting the statistical behavior of extreme particles—those that move the fastest and furthest in the system. In its place, I will describe a new theory of extreme diffusion which captures the effect of the hidden environment in which particles diffuse together and allows us to interrogate that environment by studying extreme particles. I will highlight one piece of mathematics that led us to develop this theory—a non-commutative binomial theorem—and hint at other connections to integrable probability, quantum integrable systems and stochastic PDEs.

By using the ratios conjecture, we study the asymptotic behaviour of the mean square of long truncations of the Dirichlet series for \(\bigl(\zeta'/\zeta\bigr)^{k}\) near the critical line. We explain the connection between this problem and the variance of the convoluted von Mangoldt function in short intervals. We obtain an explicit leading piecewise polynomial in the length parameter which is consistent with the microscopic-shift results of Fan Ge. We also discuss other RMT results for moments of the logarithmic derivative of characteristic polynomials and their relation to trace-average problems over U(N). 

The Poisson boundary of a probability measure on a countable group is a probability space endowed with a stationary group action that captures the asymptotic behaviour of the associated random walk. Since its introduction by Furstenberg in the 1960s, the study of Poisson boundaries and stationary actions has become a powerful tool for understanding geometric and algebraic properties of groups.

In this talk, I will discuss connections between stabilizers of stationary actions, in particular, those arising from the Poisson boundary, and the C*-simplicity of the associated reduced group C*-algebra. I will also address the (seemingly unrelated) problem of realizing different Poisson boundaries on a common underlying topological model. The talk is based on joint work with Anna Cascioli and Martín Gilabert Vio, and with Josh Frisch.