Thu, 28 May 2026

12:00 - 12:30
Lecture Room 4, Mathematical Institute

Expanding the definition of a finite element: groups, complexes and software

India Marsden
((Mathematical Institute University of Oxford))
Abstract

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. 

 

 

Tue, 28 Apr 2026
14:00
L6

The wavefront set of representations of reductive p-adic groups

Dan Ciubotaru
((Mathematical Institute University of Oxford))
Abstract

A difficult question in the local Langlands framework is to understand the interplay between the characters of irreducible smooth representations of a reductive group over a local field and the geometry of the dual space of Langlands parameters. An important invariant of the character (viewed as a distribution, i.e, a continuous linear functional on the space of smooth compactly supported functions) is the wavefront set, a measure of its singularities along with their directions. Motivated by the work of Adams, Barbasch, and Vogan for real reductive groups, it is natural to expect that the wavefront set is dual (in a certain sense) to the geometric singular support of the Langlands parameter. Dan Ciubotaru will give an overview of these ideas and describe recent progress in establishing a precise connection for representations of reductive p-adic groups. 

Thu, 23 Apr 2026
11:00
L4

Upper bound to the GK-dimension for p-adic Banach representations with infinitesimal character

Reinier Sorgdrager
(University of Amsterdam and Université Paris-Saclay)
Abstract
Let p>2 and K be a finite extension of Q_p. In recent work I have shown that an admissible p-adic Banach representation of GL2(K) has Gelfand-Kirillov dimension at most the degree [K:Q_p] as soon as its locally analytic vectors have an infinitesimal character. In work yet to appear I adapt its method to 'p-adic Banach representations in families with infinitesimal characters in families' -- still for GL2(K).
 
I will briefly motivate the result by some consequences to the p-adic Langlands program, such as a generalization of the GK-bound of Breuil-Herzig-Hu-Morra-Schraen beyond K unramified. Then I will give a quick overview of the above notions and try to present the key idea of the proof, for a single representation and with K=Q_p.


 

A new 4-D hyperchaotic Lü system with a curve
equilibrium, its bifurcation analysis, multistability,
circuit simulation and synchronization via integral sliding mode control
Moroz, I VAIDYANATHAN, S HANNACHI, F SAMBAS, A MOHAMED, M Archives of Control Sciences (10 Apr 2026)
AI Bubbles with Large Language Models
Cartea, Á Chang, P Chen, N Zhong, M (2026)
Defect charges, gapped boundary conditions, and the symmetry TFT
Copetti, C Journal of High Energy Physics volume 2026 issue 4 (09 Apr 2026)
Partial Identifiability and Misspecification in Inverse Reinforcement Learning
Skalse, J Abate, A Artificial Intelligence 104525 (Mar 2026)
Thu, 11 Jun 2026

16:00 - 17:00
L5

Bridging Black-Scholes Implied-Volatility and Price Objectives via Differentiable Jäckel Operator And  Deep Hedging using Mixture of Experts 

Raeid Saqur
((Mathematical Institute University of Oxford))
Abstract
Modern ML methods for derivatives sit at a delicate interface between market prices, implied-volatility (IV) surfaces, and the simulated environments produced by market generators. To date, these models have largely operated in one of two coordinate systems: price space, where markets quote and no-arbitrage constraints are most naturally enforced, and IV space, where surfaces are smoothed, regularized, and evaluated. This talk presents a technique that unifies learning across both coordinates — using gradients from each via a differentiable Jäckel operator and a low-vega gating mechanism — enabling end-to-end batch training without the error-prone, expensive, hand-engineered filtering usually needed to discard incompatible IV values.
 
I will present PIVOT (Price-Implied Volatility Operator Transform), a differentiable Jäckel IV operator that preserves the accuracy of the standard "Let's Be Rational" (LBR) solver in the forward pass while supplying implicit gradients through the Black–Scholes/Black-76 price map. This gives neural volatility-surface models a principled bridge between price-space and IV-space objectives, with explicit handling of the low-vega singular regime.
Second, I will  present Fast-Vollib (https://pypi.org/project/fast-vollib/), a CUDA-accelerated option-pricing library with NumPy, PyTorch, and JAX interfaces, built for high-throughput pricing-label generation in AI/ML batch training.
 
With a differentiable surface in hand, I turn to the downstream task it enables: deep hedging in mixed training environments. Using the classical density-mixing results of Brigo and Mercurio, we replace naive pooling of paths from multiple calibrated generators with a single coherent diffusion - yielding a training environment that inherits the strengths of each expert while remaining a well-defined generative model - reducing the tendency of expressive policies such as causal transformers to overfit to artificial simulator identities.
A conjecture of Warnaar-Zudilin from deformations of lie superalgebras
Creutzig, T Garner, N Research in the Mathematical Sciences volume 13 issue 2 33 (02 Apr 2026)
Lethal conflict after group fission in wild chimpanzees
Sandel, A He, Y Ren, J Kei, Y Lee, K Clark, I Reddy, R Negrey, J Birungi, C Apamaku, B Kanweri, D Kalunga, D Aliganyira, C Ramírez-Amaya, S Nakayima, P Katumba, R Kamugyisha, B Acosta-Florez, D van Boekholt, B Mbabazi, G Akamumpa, E Namaganda, S Tumusiime, A Angedakin, S Reinert, G Madrid-Padilla, O Cucuringu, M Wipf, D Langergraber, K Watts, D Mitani, J Science volume 392 issue 6794 216-220 (09 Apr 2026)
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