Tue, 10 Feb 2026
13:00
L2

Dynamics of the Fermion-Rotor System

Vazha Loladze
(Oxford )
Abstract

In this talk, I will examine the dynamics of the fermion–rotor system, originally introduced by Polchinski as a toy model for monopole–fermion scattering. Despite its simplicity, the system is surprisingly subtle, with ingoing and outgoing fermion fields carrying different quantum numbers. I will show that the rotor acts as a twist operator in the low-energy theory, changing the quantum numbers of excitations that have previously passed through the origin to ensure scattering consistent with all symmetries, thereby resolving the long-standing Unitarity puzzle. I will then discuss generalizations of this setup with multiple rotors and unequal charges, and demonstrate how the system can be viewed as a UV-completion of boundary states for chiral theories, establishing a connection to the proposed resolution of the puzzle using boundary conformal field theory.

Massada Public Seminar @Worcester College 

Itay Glazer (Technion, Israeli Institute of Technology)  -  The Mathematics of Shuffling

Mon 9 Feb 2026 5:15 - 7:00 pm, Sultan Nazrin Shah Centre, Worcester College

Book here

Thu, 15 Jan 2026
14:00
C1

Igusa stacks and the cohomology of Shimura varieties

Pol van Hoften
(Zhejiang University)
Abstract
Associated to a modular form $f$ is a two-dimensional Galois representation whose Frobenius eigenvalues can be expressed in terms of the Fourier coefficients of $f$, using a formula known as the Eichler--Shimura congruence relation. This relation was proved by Eichler--Shimura and Deligne by analyzing the mod p (bad) reduction of the modular curve of level $\Gamma_0(p)$. In this talk, I will discuss joint work with Patrick Daniels, Dongryul Kim and Mingjia Zhang, where we give a new proof of this congruence relation that happens "entirely on the rigid generic fibre". More precisely, we prove a compatibility result between the cohomology of Shimura varieties of abelian type and the Fargues--Scholze semisimple local Langlands correspondence, generalizing the Eichler--Shimura relation of Blasius--Rogawski. Our proof makes crucial use of the Igusa stacks that we construct, generalizing earlier work of Zhang, ourselves, and Kim.
 
Quantization of the Willmore Energy in Riemannian Manifolds
Michelat, A Mondino, A Advances in Mathematics
Thu, 12 Feb 2026
12:00
Lecture Room 4, Mathematical Institute

TBA

Irina-Beatrice Nimerenco
Abstract

TBA

Thu, 29 Jan 2026
12:00
Lecture Room 4, Mathematical Institute

The latent variable proximal point algorithm for variational problems with inequality constraints

John Papadopoulos
Further Information
Abstract
The latent variable proximal point (LVPP) algorithm is a framework for solving infinite-dimensional variational problems with pointwise inequality constraints. The algorithm is a saddle point reformulation of the Bregman proximal point algorithm. Although equivalent at the continuous level, the saddle point formulation is significantly more robust after discretization.
 
LVPP yields simple-to-implement numerical methods with robust convergence and observed mesh-independence for obstacle problems, contact, fracture, plasticity, and others besides; in many cases, for the first time. The framework also extends to more complex constraints, providing means to enforce convexity in the Monge--Ampère equation and handling quasi-variational inequalities, where the underlying constraint depends implicitly on the unknown solution. Moreover the algorithm is largely discretization agnostic allowing one to discretize with very-high-order $hp$-finite element methods in an efficient manner. In this talk, we will describe the LVPP algorithm in a general form and apply it to a number problems from across mathematics.


 

Thu, 22 Jan 2026

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

General Matrix Optimization

Casey Garner
Abstract

Casey Garner will talk about; 'General Matrix Optimization'

Since our early days in mathematics, we have been aware of two important characteristics of a matrix, namely, its coordinates and its spectrum. We have also witnessed the growth of matrix optimization models from matrix completion to semidefinite programming; however, only recently has the question of solving matrix optimization problems with general spectral and coordinate constraints been studied. In this talk, we shall discuss recent work done to study these general matrix optimization models and how they relate to topics such as Riemannian optimization, approximation theory, and more.

Search for dark matter in association with a Higgs boson at the LHC: A model independent study
Baradia, S Bhattacharyya, S Datta, A Dutta, S Roy Chowdhury, S Sarkar, S Nuclear Physics B volume 1022 (01 Jan 2026)
Subscribe to