Thu, 27 Jan 2022

15:00 - 16:00
Virtual

Ricci curvature lower bounds for metric measure spaces.

Dimitri Navarro
(Oxford University)
Abstract

In the '80s, Gromov proved that sequences of Riemannian manifold with a lower bound on the Ricci curvature and an upper bound on the dimension are precompact in the measured Gromov--Hausdorff topology (mGH for short). Since then, much attention has been given to the limits of such sequences, called Ricci limit spaces. A way to study these limits is to introduce a synthetic definition of Ricci curvature lower bounds and dimension upper bounds. A synthetic definition should not rely on an underlying smooth structure and should be stable when passing to the limit in the mGH topology. In this talk, I will briefly introduce CD spaces, which are a generalization of Ricci limit spaces.

Mon, 14 Feb 2022
12:45
L1

The uses of lattice topological defects

Paul Fendley
(University of Oxford)
Abstract

Great progress has been made recently in exploiting categorical/topological/higher symmetries in quantum field theory. I will explain how the same structure is realised directly in the lattice models of statistical mechanics, generalizing Kramers-Wannier duality to a wide class of models. In particular, I will give an overview of my work with Aasen and Mong on using fusion categories to find and analyse lattice topological defects in two and 1+1 dimensions.  These defects possess a variety of remarkable properties. Not only is the partition function is independent of deformations of their path, but they can branch and fuse in a topologically invariant fashion.  The universal behaviour under Dehn twists gives exact results for scaling dimensions, while gluing a topological defect to a boundary allows universal ratios of the boundary g-factor to be computed exactly on the lattice.  I also will describe how terminating defect lines allows the construction of fractional-spin conserved currents, giving a linear method for Baxterization, I.e. constructing integrable models from a braided tensor category.

Mon, 17 Jan 2022
12:45
Virtual

Symmetry TFTs from String Theory

Federico Bonetti
(University of Oxford)
Abstract

The global symmetries of a d-dimensional quantum field theory (QFT), and their ’t Hooft anomalies, are conveniently captured by a topological field theory (TFT) in (d+1) dimensions, which we may refer to as the Symmetry TFT of the given d-dimensional QFT. This point of view has a vast range of applicability: it encompasses both ordinary symmetries, as well as generalized symmetries. In this talk, I will discuss systematic methods to compute the Symmetry TFT for QFTs realized by M-theory on a singular, non-compact space X. The desired Symmetry TFT is extracted from the topological couplings of 11d supergravity, via reduction on the space L, the boundary of X. The formalism of differential cohomology allows us to include discrete symmetries originating from torsion in the cohomology of L. I will illustrate this framework in two classes of examples: M-theory on an ALE space (engineering 7d SYM theory); M-theory on Calabi-Yau cones (engineering 5d superconformal field theories).

Fri, 25 Feb 2022

14:00 - 15:00
L6

Iwahori-Hecke algebras and equivariant K-theory of the affine Flag variety

Tom Zielinski
(University of Oxford)
Abstract

In this talk, I will talk about the category of coherent sheaves on the affine Flag variety of a simply-connected reductive group over $\mathbb{C}$. In particular, I'll explain how the convolution product naturally leads to a construction of the Iwahori-Hecke algebra, and present some combinatorics related to computing duals in this category.

Thu, 27 Jan 2022

16:00 - 17:00
Virtual

Learning Homogenized PDEs in Continuum Mechanics

Andrew Stuart
(Caltech)
Further Information
Abstract

Neural networks have shown great success at learning function approximators between spaces X and Y, in the setting where X is a finite dimensional Euclidean space and where Y is either a finite dimensional Euclidean space (regression) or a set of finite cardinality (classification); the neural networks learn the approximator from N data pairs {x_n, y_n}. In many problems arising in the physical and engineering sciences it is desirable to generalize this setting to learn operators between spaces of functions X and Y. The talk will overview recent work in this context.

Then the talk will focus on work aimed at addressing the problem of learning operators which define the constitutive model characterizing the macroscopic behaviour of multiscale materials arising in material modeling. Mathematically this corresponds to using machine learning to determine appropriate homogenized equations, using data generated at the microscopic scale. Applications to visco-elasticity and crystal-plasticity are given.

Mon, 31 Jan 2022
12:45
L1

Topological Gravity as the Early Phase of our Universe

Prateek Agrawal
(University of Oxford)
Abstract

 I will present a scenario where the early universe is in a topological phase of gravity.  I will discuss a number of analogies which motivate considering gravity in such a phase. Cosmological puzzles such as the horizon problem provide a phenomenological connection to this phase and can be explained in terms of its topological nature. To obtain phenomenological estimates, a concrete realization of this scenario using Witten's four dimensional topological gravity will be used. In this model, the CMB power spectrum can be estimated by certain conformal anomaly coefficients. A qualitative prediction of this phase is the absence of tensor modes in cosmological fluctuations.

Tue, 15 Feb 2022

16:00 - 17:00
C1

Schatten class Hankel operators on the Segal-Bargmann space and the Berger-Coburn phenomenon

Jani Virtanen
(University of Reading)
Abstract

In the late 1980s, Berger and Coburn showed that the Hankel operator $H_f$ on the Segal-Bargmann space of Gaussian square-integrable entire functions is compact if and only if $H_{\bar f}$ is compact using C*-algebra and Hilbert space techniques. I will briefly discuss this and three other proofs, and then consider the question of whether an analogous phenomenon holds for Schatten class Hankel operators. 

Tue, 08 Feb 2022

12:30 - 13:30
C5

Reinforcement Learning for Optimal Execution

Huining Yang
(Mathematical Institute (University of Oxford))
Abstract

Optimal execution of large positions over a given trading period is a fundamental decision-making problem for financial services. In this talk we explore reinforcement learning methods, in particular policy gradient methods, for finding the optimal policy in the optimal liquidation problem. We show results for the case where we assume a linear quadratic regulator (LQR) model for the underlying dynamics and where we apply the method to the data directly. The empirical evidence suggests that the policy gradient method can learn the global optimal solution for a larger class of stochastic systems containing the LQR framework, and that it is more robust with respect to model misspecification when compared to a model-based approach.

Fri, 04 Feb 2022

14:00 - 15:00
Virtual

Representations of GL_2 and p-adic Symmetric Spaces

James Taylor
(University of Oxford)
Abstract

Let $F$ be a finite field or a $p$-adic field. One method of constructing irreducible representations of $G = GL_2(F)$ is to consider spaces on which $G$ naturally acts and look at the representations arising from invariants of these spaces, such as the action of $G$ on cohomology groups. In this talk, I will discuss how this goes for abstract representations of $G$ (when $F$ is finite), and smooth representations of $G$ (when $F$ is $p$-adic). The first space is an affine algebraic variety, and the second a tower of rigid spaces. I will then mention some recent results about how this tower allows us to construct new interesting $p$-adic representations of $G$, before explaining how trying to adapt these methods leads naturally to considerations about certain geometric properties of these spaces.

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