Radial Distribution Functions for the Gaussian Model

Abstract

Radial distribution functions $g$ are computed for the "Gaussian model" using the Monte Carlo (MC) method and the convolution-hypernetted-chain (CHNC) and Percus-Yevick (PY) integral equations. These results are compared with the density-expansion results obtained by Helfand and Kornegay (HK). For low density, the MC, PY, and CHNC $g\text{'}\mathrm{s}$ show excellent agreement with HK data, indicating that the errors introduced in the numerical solutions are small. At higher densities the HK data are no longer applicable, but the PY, CHNC, and MC results continue to show good agreement, with closest agreement between CHNC and MC results.