A very fast inference algorithm for finite-dimensional spin glasses: Belief Propagation on the dual lattice

Details A very fast inference algorithm for finite-dimensional spin glasses: Belief Propagation on the dual lattice A very fast inference algorithm for finite-dimensional spin glasses: Belief Propagation on the dual lattice

2011-02-16

arxiv.org/abs/1102.3305v2

Phys. Rev. E 84, 046706 (2011)

Physics

Condensed Matter

Disordered Systems and Neural Networks

23 pages, 12 figures. v2: improved introduction

Scientific paper

10.1103/PhysRevE.84.046706

Starting from a Cluster Variational Method, and inspired by the correctness of the paramagnetic Ansatz (at high temperatures in general, and at any temperature in the 2D Edwards-Anderson model) we propose a novel message passing algorithm --- the Dual algorithm --- to estimate the marginal probabilities of spin glasses on finite dimensional lattices. We show that in a wide range of temperatures our algorithm compares very well with Monte Carlo simulations, with the Double Loop algorithm and with exact calculation of the ground state of 2D systems with bimodal and Gaussian interactions. Moreover it is usually 100 times faster than other provably convergent methods, as the Double Loop algorithm.

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