L1

I will describe a categorical approach to analytic geometry using the theory of quasi-abelian closed symmetric monoidal categories which works both for Archimedean and non-Archimdedean base fields. In particular I will show how the weak G-topologies of (dagger) affinoid subdomains can be characterized by homological method. I will end by briefly saying how to generalize these results for characterizing open embeddings of Stein spaces. This project is a collaboration with Oren Ben-Bassat and Kobi Kremnizer.

We will discuss our approach to global analytic geometry, based on overconvergent power series and functors of functions. We will explain how slight modifications of it allow us to develop a derived version of global analytic geometry. We will finish by discussing applications to the cohomological study of arithmetic varieties.

I will talk in down to earth terms about several main features of this theory.

We describe how p-adic height pairings allow us to find integral points on hyperelliptic curves, in the spirit of Kim's nonabelian Chabauty program. In particular, we discuss how to carry out this ``quadratic Chabauty'' method over quadratic number fields (joint work with Amnon Besser and Steffen Mueller) and present related ideas to find rational points on bielliptic genus 2 curves (joint work with Netan Dogra).

One of the big ideas in linear algebra is {\em eigenvalues}. Most matrices become in some basis {\em diagonal} matrices; so a lot of information about the matrix (which is specified by $n^2$ matrix entries) is encoded by by just $n$ eigenvalues. The fact that lots of different matrices can have the same eigenvalues reflects the fact that matrix multiplication is not commutative.

I'll look at how to make these vague statements (``lots of different matrices...") more precise; how to extend them from matrices to abstract symmetry groups; and how to relate abstract symmetry groups to matrices.

Artist Antoni Malinowski has been commissioned to produce a major wall painting in the foyer of the new Mathematical Institute in Oxford, the Andrew Wiles Building. To celebrate and introduce that work Antoni and a series of distinguished speakers will demonstrate the different impacts and perceptions of colour produced by the micro-structure of the pigments, from an explanation of the pigments themselves to an examination of how the brain perceives colour.

Speakers:

Jo Volley, Gary Woodley and Malina Busch, the Pigment Timeline Project, Slade School of Fine Art, University College London

‘Pigment Timeline’

Dr. Ruth Siddall - Senior Lecturer in Earth Sciences, University College London

‘Pigments: microstructure and origins?’  

Antoni Malinowski

‘Spectrum Materialised’ 

Prof. Hannah Smithson Associate Professor, Experimental Psychology, University of Oxford and Tutorial Fellow, Pembroke College

‘Colour Perception‘

11.30am, Lecture Theatre 1

Mathematical Institute, University of Oxford

Andrew Wiles Building

Radcliffe Observatory Quarter

No booking required

Dave Hewett: Canonical solutions in wave scattering

By a "canonical solution" I have in mind a closed-form exact solution of the scalar wave equation in a simple geometry, for example the exterior of a circular cylinder, or the exterior of an infinite wedge. In this talk I hope to convince you that the study of such problems is (a) interesting; (b) important; and (c) a rich source of (difficult) open problems involving eigenfunction expansions, special functions, the asymptotic evaluation of integrals, and matched asymptotic expansions.

We revisit the optimal exit problem by adding a moral hazard problem where a firm owner contracts out with an agent to run a project. We analyse the optimal contracting problem between the owner and the agent in a Brownian framework, when the latter modifies the project cash-flows with an hidden action. The analysis leads to the resolution of a constrained optimal stopping problem that we solve explicitly.

Most networks and graphs encountered in empirical studies, including internet and web graphs, social networks, and biological and ecological networks, are very sparse.  Standard spectral and linear algebra methods can fail badly when applied to such networks and a fundamentally different approach is needed.  Message passing methods, such as belief propagation, offer a promising solution for these problems.  In this talk I will introduce some simple models of sparse networks and illustrate how message passing can form the basis for a wide range of calculations of their structure.  I will also show how message passing can be applied to real-world data to calculate fundamental properties such as percolation thresholds, graph spectra, and community structure, and how the fixed-point structure of the message passing equations has a deep connection with structural phase transitions in networks.