Abstract
Virial coefficients are predicted over a large range of both temperatures and model parameter values (e.g., alchemical transformation) from an individual Mayer-sampling Monte Carlo simulation by statistical mechanical extrapolation with minimal increase in computational cost. With this extrapolation method, a Mayersampling Monte Carlo simulation of SPC/E water is able to quantitatively predict the second virial coefficient as a continuous function spanning over four orders of magnitude in value and over three orders of magnitude in temperature with less than a 2% deviation. In addition, the same simulation predicts the second virial coefficient if the site charges were scaled by a constant factor, from an increase of 40% all the way to no charge at all. This method is also shown to perform well for the third virial coefficient and the exponential parameter for a Lennard-Jones fluid. Example code is provided at
https://github.com/usnistgov/mayer- extrapolation.