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This paper gives an introduction to some of the statistical physics problems which appear in the study of structural glasses. It is a shortened and updated version of a more detailed review paper which has appeared in cond-mat/0005173.

Disordered Systems and Neural Networks · Physics 2009-11-07 Marc Mezard

We discuss the metastate, a probability measure on thermodynamic states, and its usefulness in addressing difficult questions pertaining to the statistical mechanics of systems with quenched disorder, in particular short-range spin glasses.…

Disordered Systems and Neural Networks · Physics 2007-05-23 C. M. Newman , D. L. Stein

Recent work on the zero temperature phases and phase transitions of strongly random electronic system is reviewed. The transition between the spin glass and quantum paramagnet is examined, for both metallic and insulating systems. Insight…

Condensed Matter · Physics 2009-10-28 Subir Sachdev , N. Read

This thesis pretends to be another step in the development of numerical research in disordered systems. Specifically, we will focus on spin glasses which have demonstrated to be a fertile field from both, experimental and theoretical…

Disordered Systems and Neural Networks · Physics 2021-07-08 Javier Moreno-Gordo

By using numerical simulations we show that the 4D $J=\pm 1$ Edwards Anderson spin glass in magnetic field undergoes a mean field like phase transition. We use a dynamical approach: we simulate large lattices (of volume $V$) and work out…

Disordered Systems and Neural Networks · Physics 2016-08-31 E. Marinari , G. Parisi , F. Zuliani

An introduction and overview is given of the theory of spin glasses and its application.

Disordered Systems and Neural Networks · Physics 2007-05-23 David Sherrington

Spin glasses are a longstanding model for the sluggish dynamics that appears at the glass transition. However, spin glasses differ from structural glasses for a crucial feature: they enjoy a time reversal symmetry. This symmetry can be…

An extensive list of results for the ground state properties of spin glasses on random graphs is presented. These results provide a timely benchmark for currently developing theoretical techniques based on replica symmetry breaking that are…

Disordered Systems and Neural Networks · Physics 2009-11-07 S. Boettcher

These lecture notes introduce some topics of classical statistical physics, particularly those that are relevant for neural networks and deep learning. Statistical physics is treated as a branch of probability theory or statistics, with the…

Disordered Systems and Neural Networks · Physics 2026-05-12 Olaf Hohm

We study aspects of the thermodynamics of quantum versions of spin glasses. By means of the Lie-Trotter formula for exponential sums of operators, we adapt methods used to analyze classical spin glass models to answer analogous questions…

Mathematical Physics · Physics 2009-11-11 Nick Crawford

Statistical physics has proven to be a very fruitful framework to describe phenomena outside the realm of traditional physics. The last years have witnessed the attempt by physicists to study collective phenomena emerging from the…

Physics and Society · Physics 2009-05-11 Claudio Castellano , Santo Fortunato , Vittorio Loreto

This paper is an introduction to some of the main present issues in the theory of structural glasses. After recalling a few experimental facts, it gives a short account of the analogy between fragile glasses and the mean field discontinuous…

Statistical Mechanics · Physics 2007-05-23 Marc Mezard

Spin glasses are the paradigm of complex systems. These materials present really slow dynamics. However, the nature of the spin glass phase in finite dimensional systems is still controversial. Different theories describing the low…

Disordered Systems and Neural Networks · Physics 2020-06-24 J. J. Ruiz-Lorenzo

In this paper we study the fluctuations of the probability distributions of the overlap in mean field spin glasses in the presence of a magnetic field on the De Almeida-Thouless line. We find that there is a large tail in the left part of…

Disordered Systems and Neural Networks · Physics 2012-02-28 Giorgio Parisi , Federico Ricci-Tersenghi

The state space for the $N$-spin mean field (SK) spin glass--nominally an $N$-cube--is embedded in a low dimensional continuous space in such a way that metastable and stable phases can easily be discerned, a concept of nearness of…

Statistical Mechanics · Physics 2007-11-08 L. S. Schulman

Aim of this work is not trying to explore a macroscopic behavior of some recent model in statistical mechanics but showing how some recent techniques developed within the framework of spin glasses do work on simpler model, focusing on the…

Disordered Systems and Neural Networks · Physics 2009-11-13 Adriano Barra

The Hopfield model, originally inspired by spin-glass physics, occupies a central place at the intersection of statistical mechanics, neural networks, and modern artificial intelligence. Despite its conceptual simplicity and broad…

Disordered Systems and Neural Networks · Physics 2026-01-15 Denis D. Caprioti , Matheus Haas , Constantino F. Vasconcelos , Mauricio Girardi-Schappo

This talk describes how techniques developed by Computer Scientists have helped our understanding of certain problems in statistical physics which involve randomness and ``frustration''. Examples will be given from two problems that have…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. P. Young

The Parisi solution of the mean-field spin glass has been widely accepted and celebrated. Its marginal stability in 3d and its complexity however raised the question of its relevance to real spin glasses. This paper gives a short overview…

Disordered Systems and Neural Networks · Physics 2009-06-26 Eric Vincent , J. Hammann , Miguel Ocio

Ground states of the three dimensional Edwards-Anderson spin glass are computed in the presence of an external magnetic field. Our algorithm is sufficiently powerful for us to treat systems with up to 600 spins. We perform a statistical…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. Houdayer , O. C. Martin