L1

Mathematicians need to talk and writeabout their mathematics.  This includes undergraduates and MSc students, who may be writing a dissertation or project report, preparing a presentation on a summer research project, or preparing for a job interview.  We think that it can be helpful to think of this as a form of story telling, as this can lead to more effective communication.  For a story to be engaging you also need to know your audience.In this session, we'll discuss what we mean by telling a mathematical story, give you some top tips from our experience, and give you a chance to think about how you might put this into practice.  The session will be of relevance to all undergraduates and MSc students, not only those currently writing a dissertation or preparing an oral presentation.

Mathematical biology has grown enormously over the past 40 years and has changed considerably. At first, biology inspired mathematicians to come up with models that could, at an abstract level, "explain" biological phenomena - one of the most famous being Alan Turing's model for biological pattern formation. However, with the enormous recent advances in biotechnology and computation, the field is now truly inter- and multi-disciplinary. We shall discuss the changing role mathematics is playing in applications to biology and medicine.

Would you employ you? What are employers looking for in Mathematical graduates? What kind of work can use your skills? This workshop will get your minds thinking about the possibilities after you have finished studying and will cover:

·         General careers’ information starting from a mathematical sciences degree

·         Things to think about at CV and interview stage

·         How membership of a professional body (the IMA) supports your applications and career development.

·         Information about the Mathematics Teacher Training Scholarships

Mathematics is both the language and the instrument that connects our abstract understanding with the physical world, thus knowledge of mathematics quickly translates to substantial knowledge and influence on the way the world works.  But those who have the greatest ability to understand and manipulate the world hold the greatest capacity to do damage and inflict harm.  In this talk I'll explain that yes, there is ethics in mathematics, and that it is up to us as mathematicians to make good ethical choices in order to prevent our work from becoming harmful.

Are you keen to share your love of maths with non-mathematicians, but aren’t sure where to start? Whether you're keen to get involved in outreach activities at Oxford, or you'd just like to explain to your friends and family what you do all term, there's something for everyone in our interactive hour of workshop activities, and lots of laughs along the way. Just bring plenty of enthusiasm, and come prepared with a bit of mathematics you particularly like. 

This session is open to all, and no prior outreach experience is necessary.

When approximating PDEs with the finite element method, large sparse linear systems must be solved. The ideal preconditioner yields convergence that is  algorithmically optimal and parameter robust, i.e. the number of Krylov iterations required to solve the linear system to a given accuracy does not grow substantially as the mesh or problem parameters are changed.

Achieving this for the stationary Navier-Stokes has proven challenging: LU factorisation is Reynolds-robust but scales poorly with degree of freedom count, while Schur complement approximations such as PCD and LSC degrade as the Reynolds number is increased.

Building on the work of Schöberl, Olshanskii and Benzi, in this talk we present the first preconditioner for the Newton linearisation of the stationary Navier--Stokes equations in three dimensions that achieves both optimal complexity and Reynolds-robustness. The scheme combines a novel tailored finite element discretisation, discrete augmented Lagrangian stabilisation, a custom prolongation operator involving local solves on coarse cells, and an additive patchwise relaxation on each
level. We present 3D simulations with over one billion degrees of freedom with robust performance from Reynolds number 10 to 5000.

Employing the usual multilevel Monte Carlo estimator, we introduce a framework for estimating the solutions of SDEs by an Euler-Maruyama scheme. By considering the expected value of such solutions, we produce simulations using approximately normal random variables, and recover the estimate from the exact normal distribution by use of a multilevel correction, leading to faster simulations without loss of accuracy. We will also highlight this concept in the framework of reduced precision and vectorised computations.

Robert Timms

Title: Multiscale modelling of lithium-ion batteries

Lithium-ion batteries are one of the most widely used technologies for energy storage, with applications ranging from portable electronics to electric vehicles. Due to their popularity, there is a continued interest in the development of mathematical models of lithium-ion batteries. These models encompass various levels of complexity, which may be suitable to aid with design, or for real-time monitoring of performance. After a brief introduction to lithium-ion batteries, I will discuss some of the modelling efforts undertaken here at Oxford and within the wider battery modelling community.
 

Jan Vonk

Title: Singular moduli for real quadratic fields

At the 1900 ICM, David Hilbert posed a series of problems, of which the 12th remains completely open today. I will discuss how to solve this problem in the simplest open case, by considering certain exotic (so called p-adic) metrics on the set of numbers, and using its concomitant theories of analysis and geometry.
 

Are you teaching intercollegiate classes or tutorials this term? Would you like to explore inclusive teaching strategies that could help all students make the most of your sessions? In this interactive workshop, we'll explore strategies that have been found effective. This will be a self-contained session, but will also be a good introduction to the "Developing Learning and Teaching" course offered by MPLS for graduate students and early career researchers. The session will be led by Vicky Neale (Mathematics) and Delia O'Rourke (Oxford Learning Institute).