An Importance Sampling Scheme for Models in a Strong External Field
Computational Physics
2016-11-17 v1 Information Theory
math.IT
Computation
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.
Cite
@article{arxiv.1512.08650,
title = {An Importance Sampling Scheme for Models in a Strong External Field},
author = {Mehdi Molkaraie},
journal= {arXiv preprint arXiv:1512.08650},
year = {2016}
}
Comments
Proc. IEEE Int. Symp. on Information Theory (ISIT), Hong Kong, June 14-19, 2015. arXiv admin note: text overlap with arXiv:1401.4912