Cavity method

The cavity method is a mathematical method presented by Marc Mézard, Giorgio Parisi and Miguel Angel Virasoro in 1987 to solve some mean field type models in statistical physics, specially adapted to disordered systems. The method has been used to compute properties of ground states in many condensed matter and optimization problems. Initially invented to deal with the Sherrington–Kirkpatrick model of spin glasses, the cavity method has shown wider applicability. It can be regarded as a generalization of the Bethe—Peierls iterative method in tree-like graphs, to the case of a graph with loops that are not too short. The different approximations that can be done with the cavity method are usually named after their equivalent with the different steps of the replica method which is mathematically more subtle and less intuitive than the cavity approach. The cavity method has proved useful in the solution of optimization problems such as k-satisfiability and graph coloring. It has yielded

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Verre de spin

vignette|Représentation schématique d'une structure aléatoire d'un verre de spins (haut) et d'un état ferromagnétique (bas). Les verres de spin sont des alliages métalliques comportant un petit nomb

EPFL2014

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Approaching the Rate-Distortion Limit by spatial Coupling with Belief Propagation and Decimation

Vahid Aref, Nicolas Macris, Marc Vuffray

We investigate an encoding scheme for lossy compression based on spatially coupled Low-Density Generator-Matrix codes. The degree distributions are regular, or are Poisson on the code-bit side and check-regular which allows use for any compression rate. The performance of a low complexity Belief Propagation Guided Decimation algorithm is excellent, and for large check degrees it gets close to Shannon's rate-distortion limit. We investigate links between the algorithmic performance and the phase diagram of a relevant random Gibbs measure. The associated dynamical and condensation thresholds are computed within the framework of the cavity method. We observe that: (i) the dynamical threshold of the spatially coupled construction saturates towards the condensation threshold; (ii) for large degrees the condensation threshold approaches the information theoretic test-channel parameter of rate-distortion theory. This provides heuristic insight into the excellent performance of the BPGD algorithm.

2013

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Approaching the Rate-Distortion Limit with Spatial Coupling, Belief propagation and Decimation

Vahid Aref, Nicolas Macris, Marc Vuffray

We investigate an encoding scheme for lossy compression of a binary symmetric source based on simple spatially coupled Low-Density Generator-Matrix codes. The degree of the check nodes is regular and the one of code-bits is Poisson distributed with an average depending on the compression rate. The performance of a low complexity Belief Propagation Guided Decimation algorithm is excellent. The algorithmic rate-distortion curve approaches the optimal curve of the ensemble as the width of the coupling window grows. Moreover, as the check degree grows both curves approach the ultimate Shannon rate-distortion limit. The Belief Propagation Guided Decimation encoder is based on the posterior measure of a binary symmetric test-channel. This measure can be interpreted as a random Gibbs measure at a "temperature" directly related to the "noise level of the test-channel". We investigate the links between the algorithmic performance of the Belief Propagation Guided Decimation encoder and the phase diagram of this Gibbs measure. The phase diagram is investigated thanks to the cavity method of spin glass theory which predicts a number of phase transition thresholds. In particular the dynamical and condensation "phase transition temperatures" (equivalently test-channel noise thresholds) are computed. We observe that: (i) the dynamical temperature of the spatially coupled construction saturates towards the condensation temperature; (ii) for large degrees the condensation temperature approaches the temperature (i.e. noise level) related to the information theoretic Shannon test-channel noise parameter of rate-distortion theory. This provides heuristic insight into the excellent performance of the Belief Propagation Guided Decimation algorithm. The paper contains an introduction to the cavity method.

Institute of Electrical and Electronics Engineers

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PHYS-435: Statistical physics III

This course introduces statistical field theory, and uses concepts related to phase transitions to discuss a variety of complex systems (random walks and polymers, disordered systems, combinatorial optimisation, information theory and error correcting codes).

COM-712: Statistical Physics for Communication and Computer Science

The course introduces the student to notions of statistical physics which have found applications in communications and computer science. We focus on graphical models with the emergence of phase transitions, and their relation to the behavior of efficient algorithms.

PHYS-512: Statistical physics of computation

This course covers the statistical physics approach to computer science problems ranging from graph theory and constraint satisfaction to inference and machine learning. In particular the replica and cavity methods, message passings algorithms, and analysis of the related phase transitions.