Weighting methods for Monte-Carlo calculation of polymer configurations

Abstract

In the Rosenbluth and Rosenbluth method of computing polymer configurations, the configurations are weighted in order to remove bias of the estimated parameters of the configurations. This weighting method is investigated and generalized for importance sampling and Boltzmann factors. The estimates are found to be unbiased in the limit for an infinite sample of configurations, but to have a bias for a finite sam pit'. The standard deviations of the estimates are also derived.