  The cluster variation method has been developed into a general theoretical
framework for treating short-range correlations in many-body systems after it
was first proposed by Kikuchi in 1951. On the numerical side, a message-passing
approach called generalized belief propagation (GBP) was proposed by Yedidia,
Freeman and Weiss about a decade ago as a way of computing the minimal value of
the cluster variational free energy and the marginal distributions of clusters
of variables. However the GBP equations are often redundant, and it is quite a
non-trivial task to make the GBP iteration converges to a fixed point. These
drawbacks hinder the application of the GBP approach to finite-dimensional
frustrated and disordered systems.
  In this work we report an alternative and simple derivation of the GBP
equations starting from the partition function expression. Based on this
derivation we propose a natural and systematic way of removing the redundance
of the GBP equations. We apply the simplified generalized belief propagation
(SGBP) equations to the two-dimensional and the three-dimensional ferromagnetic
Ising model and Edwards-Anderson spin glass model. The numerical results
confirm that the SGBP message-passing approach is able to achieve satisfactory
performance on these model systems. We also suggest that a subset of the SGBP
equations can be neglected in the numerical iteration process without affecting
the final results.
