DMS-EPSRC Sharp Large Deviation Estimates of Fluctuations in Stochastic Hydrodynamic Systems
Lead Research Organisation:
University of Warwick
Department Name: Mathematics
Abstract
Extreme events can be highly impactful. They are typically rare, which is fortunate if their consequences are negative on society, but also makes them difficult to predict. The scope of this project is to develop computational tools that can be applied to gain understanding of how extreme events occur in complex stochastic systems. Examples are models for the forecasting of extreme weather-related events like tropical storms and flooding as well as the spread of pollutants in case of ocean oil spills. Our tools will enable researchers to ask questions beyond of what is currently possible. This will lead to transformative improvement of current predictive models, which is essential for efficient management of natural and man made disasters. Further applications include the characterization of extreme events in stochastic models that behave similar to fluids, for example in the context of epidemics, traffic, and star formation.
People |
ORCID iD |
Tobias Grafke (Principal Investigator) |
Publications
Frishman A
(2022)
Mechanism for turbulence proliferation in subcritical flows
in Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Frishman A
(2022)
Mechanism for turbulence proliferation in subcritical flows
Schorlepp T
(2022)
Symmetries and zero modes in sample path large deviations
Frishman A
(2022)
Dynamical landscape of transitional pipe flow.
in Physical review. E
Grafke T
(2023)
Sharp asymptotic estimates for expectations, probabilities, and mean first passage times in stochastic systems with small noise
in Communications on Pure and Applied Mathematics
Sprittles J
(2023)
Rogue nanowaves: A route to film rupture
in Physical Review Fluids
Schorlepp T
(2023)
Scalable methods for computing sharp extreme event probabilities in infinite-dimensional stochastic systems
in Statistics and Computing
Grafke T
(2023)
Sample Path Large Deviations for Climate, Ocean, and Atmosphere