Past Events

Binding of molecules, ions or proteins to small target sites is a generic step of cell activation. This process relies on rare stochastic events where a particle located in a large bulk has to find small and often hidden targets. I will present in...

Let f be a primitive modular form and L(s) its associated L-function. Anton Good (1982) bounded |L(s)| by approximately the cube root of the distance from the real axis on the line s = 1/2, in the case f is a modular form on the full modular group...

In this talk, we discuss some results on the non-vanishing of the central values of Rankin-Selberg convolutions of families of Hilbert modular forms. Such results are obtained by establishing some asymptotics of certain twisted first and second...

Systems with random fluctuations are ubiquitous in the real world. Stochastic PDEs are default models for these random systems, just as PDEs are default models for deterministic systems. However, a large class of such stochastic PDEs were poorly...

I will present a general approach for constructing a Markov process that describes the dynamics of a process when one or more observables of this process are observed to fluctuate in time away from their typical values. This will extend some well...

We discuss two recent scaling limit results for discrete dynamics converging to stochastic PDEs. The first is the asymmetric simple exclusion process in contact with sources and sinks at boundaries, called Open ASEP. We prove that under weakly...

Harnack inequalities have proved to be a powerful tool in PDE (regularity estimates), geometry (geometric flows) and probability (heat kernel estimates). In the early 1990s Grigor'yan and Saloff-Coste gave a characterisation of the parabolic Harnack...

The boundary Harnack principle (BHP) is a fundamental tool to understand the behaviour of positive harmonic functions near the boundary of a domain. For instance, the BHP implies a concrete description of the Martin boundary of a domain in geometric...

Many problems in scientific computing require the approximation of smooth, high-dimensional functions from limited amounts of data. For instance, a typical problem in uncertainty quantification involves identifying the parameter dependence of the...

Please bring your favourite (math) problems. Anyone with a problem to share will be given about 5 minutes to present it. We will also choose most of the speakers for the rest of the semester. EVERYONE IS WELCOME!