Variational approach to closure of nonlinear dynamical systems: Autonomous case
Micka\"el D. Chekroun, Honghu Liu, James C. McWilliams

TL;DR
This paper introduces a variational method for deriving low-order reduced models of nonlinear autonomous systems using optimal parameterizing manifolds, improving upon classical invariant manifold approaches especially in turbulent regimes.
Contribution
It proposes a novel variational framework for constructing optimal parameterizing manifolds that generalize slow/invariant manifolds, applicable to complex turbulent systems.
Findings
Effective closure of atmospheric primitive equations.
Accurate modeling of Rayleigh-Bénard convection.
Efficient turbulence closure for Kuramoto-Sivashinsky system.
Abstract
A general, variational approach to derive low-order reduced systems for nonlinear systems subject to an autonomous forcing, is introduced. The approach is based on the concept of optimal parameterizing manifold (PM) that substitutes the more classical notion of slow manifold or invariant manifold when breakdown of slaving occurs. An optimal PM provides the manifold that describes the average motion of the neglected scales as a function of the resolved scales and allows, in principle, for determining the best vector field of the reduced state space that describes e.g. the dynamics' slow motion. The underlying optimal parameterizations are approximated by dynamically-based formulas derived analytically from the original equations. These formulas are contingent upon the determination of only a few (scalar) parameters obtained from minimization of cost functionals, depending on training…
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