Speaker: Dr. Romain Veltz, INRIA, France
Date: Thursday, 18th March 2021, 10am (CET)
Zoom-Link: Please request via email from Michael Schlottke-Lakemper

Abstract

In this talk, I will first present the basics of bifurcation theory. Then, I will give a panorama of BifurcationKit.jl, a Julia package to perform numerical bifurcation analysis of large dimensional equations (PDE, nonlocal equations, etc) possibly on GPUs using Matrix-Free / Sparse Matrix formulations of the problem. Julia programming language gives access to a rich ecosystem (PDE, GPU, AD, cluster…). Notably, numerical bifurcation analysis can be done entirely on GPU as will be shown in an example.

BifurcationKit incorporates continuation algorithms (PALC, deflated continuation, …) which can be used to perform fully automatic bifurcation diagram computation of stationary states. I will showcase this with the 2d Bratu problem.

Additionally, by leveraging on the above methods, the package can also seek for periodic orbits of Cauchy problems by casting them into an equation of high dimension. It is by now, one of the only software which provides parallel (Standard / Poincaré) shooting methods and finite differences based methods to compute periodic orbits in high dimensions. I will present an application highlighting the ability to fine tune BifurcationKit to get performance.

In a last part, I will describe a mean field model of stochastic spiking neurons described with a 2d measure valued equation. I will present a numerical scheme based on an implicit Finite Volume method. I will then provide some mathematical properties of the mean field concerning well posedness and stationary solutions. Additionally, I will show how BifurcationKit.jl can be used to study numerically the model. Finally, I will conclude on open problems, some of which could hopefully be tackled numerically with Trixi.jl.