Effect of Macroscopic Surface Heterogeneities on an Advancing Contact Line.
Melides, S
Vella, D
Ramaioli, M
Langmuir : the ACS journal of surfaces and colloids
volume 38
issue 44
13358-13369
(27 Nov 2022)
We are pleased to announce that applications for the award-winning programme, RisingWISE, are now open. Aimed at women postdoc researchers in STEM and run in collaboration with the University of Cambridge, we are now in our fifth year of creating impact. RisingWISE is an enterprise course and network for women early career researchers in STEM that has a consistent success rate of 100 referral score and a growing alumni community.
It is almost Christmas (no, really) and that means we need a card. Or, to be precise, a mathematically inspired card. So if you are feeling creative and want to win £50 of Amazon vouchers please email Dyrol (@email). Our designers will work with you so you don't have to have final design or even a fully thought out idea. However, the idea is that the final card will animate (click the image below to see last year's animation).
Organization and evolution of the UK far-right network on Telegram
Bovet, A
Grindrod, P
Applied Network Science
volume 7
(15 Nov 2022)
Upscaling the Poisson–Nernst–Planck equations for ion transport in weakly heterogeneous charged porous media
Klika, V
Gaffney, E
Applied Mathematics Letters
volume 137
(12 Nov 2022)
Thu, 01 Dec 2022
16:00
16:00
Virtual
Particle filters for Data Assimilation
Dan Crisan
(Imperial College London)
Note: we would recommend to join the meeting using the Teams client for best user experience.
Further Information
Abstract
Modern Data Assimilation (DA) can be traced back to the sixties and owes a lot to earlier developments in linear filtering theory. Since then, DA has evolved independently of Filtering Theory. To-date it is a massively important area of research due to its many applications in meteorology, ocean prediction, hydrology, oil reservoir exploration, etc. The field has been largely driven by practitioners, however in recent years an increasing body of theoretical work has been devoted to it. In this talk, In my talk, I will advocate the interpretation of DA through the language of stochastic filtering. This interpretation allows us to make use of advanced particle filters to produce rigorously validated DA methodologies. I will present a particle filter that incorporates three additional add-on procedures: nudging, tempering and jittering. The particle filter is tested on a two-layer quasi-geostrophic model with O(10^6) degrees of freedom out of which only a minute fraction are noisily observed.