PADE APPROXIMANTS FOR RADIAL DISTRIBUTION FUNCTIONS OF GAUSSIAN MODEL

Radial distribution functions (g) are computed for the Gaussian model of a fluid by approximating the density expansion with a Fade approximant g (m, n). Several choices of m and n are studied by comparing these calculated g's with those previously obtained using the Percus-Yevick and hypernetted chain integral equations, a Monte Carlo method, and simple truncation of the density expansion. It is found that, if a few terms in the density expansion are known, the range of densities for which this information is useful may be extended by the proper choice of m and n in the Pade approximant. A form of g(m, n) is presented which approximates g quite well for a large range of densities.