Past events

• Past years:  https://fmboire.github.io/uocms/

Fall 2026:

• Markus Riedle (King's College London) September 4, 2026

Title: Modelling Random Perturbations in Time and Space: Two Approaches to SPDEs

Abstract:

Stochastic partial differential equations (SPDEs) provide a mathematical framework for systems evolving in time and space under random perturbations. They arise naturally in fields such as engineering, economics, population dynamics, meteorology, physics, and seismology. The randomness may represent external or internal fluctuations, genuinely random future events, or uncertainty in the underlying model. There are two principal ways of formulating SPDEs. In the random field approach, the solution is described directly as a random function of time and space, while in the infinite-dimensional approach, the SPDE is interpreted as a stochastic evolution equation in a suitable function space.

In this talk, I will introduce these two viewpoints, explain how randomness can be modelled in each setting, and discuss the relationship between the two approaches. Particular attention will be paid to Gaussian and non-Gaussian noise, including random perturbations with jumps, and to the mathematical representations of randomness distributed over time and space.