activity
20052023
most citedStochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics

66 citations · 189 across the 10 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

math.NA2019

A structure-preserving approximation of the discrete split rotating shallow water equations

Werner Bauer, Jörn Behrens, Colin J. Cotter

We introduce an efficient split finite element (FE) discretization of a y-independent (slice) model of the rotating shallow water equations. The study of this slice model provides…

math.NA2019

A Compatible Finite Element Discretisation for the Moist Compressible Euler Equations

Thomas M. Bendall, Thomas H. Gibson, Jemma Shipton +2

We present new discretisation of the moist compressible Euler equations, using the compatible finite element framework identified in Cotter and Shipton (2012). The discretisation s…

math.NA2019

Data assimilation for a quasi-geostrophic model with circulation-preserving stochastic transport noise

Colin Cotter, Dan Crisan, Darryl Holm +2

This paper contains the latest installment of the authors' project on developing ensemble based data assimilation methodology for high dimensional fluid dynamics models. The algori…

math.NA2019

Perspectives on the Formation of Peakons in the Stochastic Camassa-Holm Equation

Thomas M. Bendall, Colin J. Cotter, Darryl D. Holm

A famous feature of the Camassa-Holm equation is its admission of peaked soliton solutions known as peakons. We investigate this equation under the influence of stochastic transpor…

stat.AP2019

A Particle Filter for Stochastic Advection by Lie Transport (SALT): A case study for the damped and forced incompressible 2D Euler equation

Colin Cotter, Dan Crisan, Darryl D. Holm +2

In this work, we combine a stochastic model reduction with a particle filter augmented with tempering and jittering, and apply the combined algorithm to a damped and forced incompr…

eess.IV2019

Selective metamorphosis for growth modelling with applications to landmarks

Andreas Bock, Alexis Arnaudon, Colin Cotter

We present a framework for shape matching in computational anatomy allowing users control of the degree to which the matching is diffeomorphic. This control is given as a function…