An Importance Sampling Scheme for Models in a Strong External Field

Abstract

We propose Monte Carlo methods to estimate the partition function of the two-dimensional Ising model in the presence of an external magnetic field. The estimation is done in the dual of the Forney factor graph representing the model. The proposed methods can efficiently compute an estimate of the partition function in a wide range of model parameters. As an example, we consider models that are in a strong external field.