No abstract

Extensions to the finite temperature Green's-function method for the calculation of equilibrium densities within the Kohn-Sham formulation of density functional theory are presented. In particular, an expression for the density in terms of single-particle Green's-function differences summed over all Matsubara poles is utilized. Numerical methods for the evaluation of this infinite sum are given. This formulation automatically includes discrete as well as continuum states, is valid for finite temperatures, and is especially well suited for high temperatures. Techniques are also presented for the calculation of single-particle Green's functions for spherically symmetric systems and arbitrary complex energies. The usefulness of these methods is demonstrated by their application to the problem of electron screening of nuclei in a plasma. Direct comparison is made with previous finite temperature, Kohn-Sham, wave function type calculations for protons and for neon nuclei in an electron gas.

The fusion-enhancement factor due to screening in the solar plasma is calculated. We use the Ðnite-temperature GreenÏs function method, and a self-consistent mean Ðeld approximation. We reduce this to one-center problems, because in the collision of two fusing ions, the turning point where tunneling may occur lies far inside the screening radius. The numerical results given by this method indicate that screening may be slightly weaker than that obtained in the most recent previous calculations.

An important design decision in the construction of a simulator is how to enable users to access the data generated in each run of a simulation experiment. As the simulator executes, the samples of performance metrics that are generated beg to be exposed either in their raw state or after having undergone mathematical processing. Also of concern is the particular format this data assumes when externalized to mass storage, since it determines the ease of processing by other applications or interpretation by the user. In this paper, we present a framework for the ns-3 network simulator for capturing data from inside an experiment, subjecting it to mathematical transformations, and ultimately marshaling it into various output formats. The application of this functionality is illustrated and analyzed via a study of common use cases. Although the implementation of our approach is specific to ns-3, this design presents lessons transferrable to other platforms.