Mean Field Approximation

Andreas Wipf

Diego Luis González, Alberto Pimpinelli, T. L. Einstein

We propose a mean-field method to calculate approximately the spacing distribution functions p((n))(s) in one-dimensional classical many-particle systems. We compare our method with two other commonly used methods, the independent interval approximation and the extended Wigner surmise. In our mean-field approach, p((n))(s) is calculated from a set of Langevin equations, which are decoupled by using a mean-field approximation. We find that in spite of its simplicity, the mean-field approximation provides good results in several systems. We offer many examples illustrating that the three previously mentioned methods give a reasonable description of the statistical behavior of the system. The physical interpretation of each method is also discussed.

James L. Monroe

Results based on the indirect fluctuating mean-field theory recently proposed by Suzuki (1986) are reported. The results indicate some of the important characteristics of this approximation method, which differs in significant ways from the standard mean-field approximation and recent improvements of it.

Tomoyasu Tanaka

Cayetano Di Bartolo, Lorenzo Leal

We study a modified mean-field approximation for the Ising Model in arbitrary dimension. Instead of taking a "central" spin, or a small "drop" of fluctuating spins coupled to the effective field of their nearest neighbors as in the Mean-Field or the Bethe-Peierls-Weiss methods, we take an infinite chain of fluctuating spins coupled to the mean field of the rest of the lattice. This results in a significative improvement of the Mean-Field approximation with a small extra effort.