Universal statistics of point vortex turbulence

A new methodology, based on the central limit theorem, is applied to describe the statistical mechanics of two-dimensional point vortex motion in a bounded container D, as the number of vortices N tends to infinity. The key to the approach is the identification of the normal modes of the system with the eigenfunction solutions of the so-called hydrodynamic eigenvalue problem of the Laplacian in D. The statistics of the projection of the vorticity distribution onto these eigenfunctions (‘vorticity projections’) are then investigated. The statistics are used first to obtain the density-of-states function and caloric curve for the system, generalising previous results to arbitrary (neutral) distributions of vortex circulations. Explicit expressions are then obtained for the microcanonical (i.e. fixed energy) probability density functions of the vorticity projections in a form that can be compared directly with direct numerical simulations of the dynamics. The energy spectra of the resulting flows are predicted analytically. Ensembles of simulations with N=100, in several conformal domains, are used to make a comprehensive validation of the theory, with good agreement found across a broad range of energies. The probability density function of the leading vorticity projection is of particular interest because it has a unimodal distribution at low energy and a bimodal distribution at high energy. This behaviour is indicative of a phase transition, known as Onsager–Kraichnan condensation in the literature, between low-energy states with no mean flow in the domain and high-energy states with a coherent mean flow. The critical temperature for the phase transition, which depends on the shape but not the size of D, and the associated critical energy are found. Finally the accuracy and the extent of the validity of the theory, at finite N, are explored using a Markov chain phase-space sampling method

Dynamics and statistical mechanics of point vortices in bounded domains

A general treatment of the dynamics and statistical mechanics of point vortices in bounded domains is introduced in Chapter 1. Chapter 2 then considers high positive energy statistical mechanics of 2D Euler vortices. In this case, the most-probable equilibrium dynamics are given by solutions of the sinh-Poisson equation and a particular heart-shaped domain is found in which below a critical energy the solution has a dipolar structure and above it a monopolar structure. Sinh-Poisson predictions are compared to long-time averages of dynamical simulations of the $N$ vortex system in the same domain. Chapter 3 introduces a new algorithm (VOR-MFS) for the solution of generalised point vortex dynamics in an arbitrary domain. The algorithm only requires knowledge of the free-space Green's function and utilises the exponentially convergent method of fundamental solutions to obtain an approximation to the vortex Hamiltonian by solution of an appropriate boundary value problem. A number of test cases are presented, including quasi-geostrophic shallow water (QGSW) point vortex motion (governed by a Bessel function). Chapter 4 concerns low energy (positive and negative) statistical mechanics of QGSW vortices in `Neumann oval' domains. In this case, the `vorticity fluctuation equation' -- analogous to the sinh-Poisson equation -- is derived and solved to give expressions for key thermodynamic quantities. These theoretical expressions are compared with results from direct sampling of the microcanonical ensemble, using VOR-MFS to calculate the energy of the QGSW system. Chapter 5 considers the distribution of 2D Euler vortices in a Neumann oval. At high energies, vortices of one sign cluster in one lobe of the domain and vortices of the other sign cluster in the other lobe. For long-time simulations, these clusters are found to switch lobes. This behaviour is verified using results from the microcanonical ensemble