The computation of open many-particle systems at high densities is a
major challenge since many decades due to the inherent limitations of
grand canonical simulation methods based on particle exchange
algorithms. In this paper we report on the statistical convergence
behavior in the high density regime of a recently developed alternative
called the grand canonical auxiliary field Monte Carlo method. We show
on a common soft matter model widely used in polymer simulation that it
possesses a more appropriate statistical behavior in the dense regime
than the currently employed grand canonical Monte Carlo methods relying
on particle exchange algorithms. (C) 2003 Elsevier B.V. All rights
reserved