Reduced models of point vortex systems
Jonathan Maack, Bruce Turkington

TL;DR
This paper develops optimal closure-based reduced models for point vortex systems to effectively describe their relaxation to equilibrium, validated against detailed numerical simulations.
Contribution
It introduces a novel optimal closure method for Hamiltonian vortex models, capturing late-stage turbulence evolution with reduced complexity.
Findings
Models accurately predict relaxation to equilibrium states.
Reduced models describe energy transfer in two-layer flows.
Validation shows strong agreement with direct numerical simulations.
Abstract
Nonequilibrium statistical models of point vortex systems are constructed using an optimal closure method, and these models are employed to approximate the relaxation toward equilibrium of systems governed by the two-dimensional Euler equations, as well as the quasi-geostrophic equations for either single-layer or two-layer flows. Optimal closure refers to a general method of reduction for Hamiltonian systems, in which macroscopic states are required to belong to a parametric family of distributions on phase space. In the case of point vortex ensembles, the macroscopic variables describe the spatially coarse-grained vorticity. Dynamical closure in terms of those macrostates is obtained by optimizing over paths in the parameter space of the reduced model subject to the constraints imposed by conserved quantities. This optimization minimizes a cost functional that quantifies the rate of…
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