Explicit mean-field radius for nearly parallel vortex filaments in statistical equilibrium

Details Explicit mean-field radius for nearly parallel vortex filaments in statistical equilibrium Explicit mean-field radius for nearly parallel vortex filaments in statistical equilibrium

2006-11-19

arxiv.org/abs/math-ph/0611049v1

Physics

Mathematical Physics

27 pages, 6 figures, to be presented at Joint AMS and MAA conference and submitted to GAFD

Scientific paper

Geophysical research has focused on flows, such as ocean currents, as two dimensional. Two dimensional point or blob vortex models have the advantage of having a Hamiltonian, whereas 3D vortex filament or tube systems do not necessarily have one, although they do have action functionals. On the other hand, certain classes of 3D vortex models called nearly parallel vortex filament models do have a Hamiltonian and are more accurate descriptions of geophysical and atmospheric flows than purely 2D models, especially at smaller scales. In these ``quasi-2D'' models we replace 2D point vortices with vortex filaments that are very straight and nearly parallel but have Brownian variations along their lengths due to local self-induction. When very straight, quasi-2D filaments are expected to have virtually the same planar density distributions as 2D models. An open problem is when quasi-2D model statistics behave differently than those of the related 2D system and how this difference is manifested. In this paper we study the nearly parallel vortex filament model of Klein, Majda, Damodaran in statistical equilibrium. We are able to obtain a free-energy functional for the system in a non-extensive thermodynamic limit that is a function of the mean square vortex position $R^2$ and solve \emph{explicitly} for $R^2$. Such an explicit formula has never been obtained for a non-2D model. We compare the results of our formula to a 2-D formula of \cite{Lim:2005} and show qualitatively different behavior even when we disallow vortex braiding. We further confirm our results using Path Integral Monte Carlo (Ceperley (1995)) \emph{without} permutations and that the Klein, Majda, Damodaran model's asymptotic assumptions \emph{are valid} for parameters where these deviations occur.

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