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Monte Carlo Sampling of Negative-temperature Plasma States
Author(s) -
John A. Krommes,
Sharadini Rath
Publication year - 2002
Language(s) - English
Resource type - Reports
DOI - 10.2172/808375
Subject(s) - monte carlo method , physics , amplitude , statistical physics , nonlinear system , poisson distribution , excited state , poisson's equation , mathematics , quantum mechanics , statistics
A Monte Carlo procedure is used to generate N-particle configurations compatible with two-temperature canonical equilibria in two dimensions, with particular attention to nonlinear plasma gyrokinetics. An unusual feature of the problem is the importance of a nontrivial probability density function R0(PHI), the probability of realizing a set {Phi} of Fourier amplitudes associated with an ensemble of uniformly distributed, independent particles. This quantity arises because the equilibrium distribution is specified in terms of {Phi}, whereas the sampling procedure naturally produces particles states gamma; {Phi} and gamma are related via a gyrokinetic Poisson equation, highly nonlinear in its dependence on gamma. Expansion and asymptotic methods are used to calculate R0(PHI) analytically; excellent agreement is found between the large-N asymptotic result and a direct numerical calculation. The algorithm is tested by successfully generating a variety of states of both positive and negative temperature, including ones in which either the longest- or shortest-wavelength modes are excited to relatively very large amplitudes

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