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Related papers: Statistical physics of complex systems: glasses, s…

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Spin glasses occupy a unique place in condensed matter: they freeze collectively while remaining struc-turally disordered, and they exhibit slow, history-dependent dynamics that reflect an exceptionally rug-ged free-energy landscape. This…

Disordered Systems and Neural Networks · Physics 2025-12-25 Naeimeh Tahriri , Vahid Mahdikhah , Jahanfar Abouie , Daryoosh Vashaee

We study the glass and jamming transition of finite-dimensional models of simple liquids: hard- spheres, harmonic spheres and more generally bounded pair potentials that modelize frictionless spheres in interaction. At finite temperature,…

Disordered Systems and Neural Networks · Physics 2013-07-16 Hugo Jacquin

The goal of this book is to present new mathematical techniques for studying the behaviour of mean-field systems with disordered interactions. We mostly focus on certain problems of statistical inference in high dimension, and on spin…

Probability · Mathematics 2023-11-29 Tomas Dominguez , Jean-Christophe Mourrat

Spin glasses are magnetic systems exhibiting both quenched disorder and frustration, and have often been cited as examples of `complex systems.' In this talk I review some of the basic notions of spin glass physics, and discuss how some of…

Disordered Systems and Neural Networks · Physics 2018-03-28 D. L. Stein

In these notes the main theoretical concepts and techniques in the field of mean-field spin-glasses are reviewed in a compact and pedagogical way, for the benefit of the graduate and undergraduate student. One particular spin-glass model is…

Disordered Systems and Neural Networks · Physics 2009-11-11 Tommaso Castellani , Andrea Cavagna

Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

This paper first describes, from a high level viewpoint, the main challenges that had to be solved in order to develop a theory of spin glasses in the last fifty years. It then explains how important inference problems, notably those…

Disordered Systems and Neural Networks · Physics 2023-12-12 Marc Mézard

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

We review the field of the glass transition, glassy dynamics and aging from a statistical mechanics perspective. We give a brief introduction to the subject and explain the main phenomenology encountered in glassy systems, with a particular…

Statistical Mechanics · Physics 2020-10-12 Francesco Arceri , François P. Landes , Ludovic Berthier , Giulio Biroli

In talk I will review the theoretical results that have been obtained for spin glasses, paying a particular attention to finite dimensional spin glasses. I will concentrate my attention on the formulation of the mean field approach and on…

Disordered Systems and Neural Networks · Physics 2009-11-13 Giorgio Parisi

I give a very brief non-technical introduction to the intersection of the fields of spin systems and computational complexity. The focus is on spin glasses and their relationship to NP-complete problems.

Quantum Physics · Physics 2010-08-25 Daniel Gottesman

We study the off-equilibrium dynamics of the three-dimensional Ising spin glass in the presence of an external magnetic field. We have performed simulations both at fixed temperature and with an annealing protocol. Thanks to the Janus…

This paper is divided into two parts. The first part concerns several standard scenarios for how short-range spin glasses might behave at low temperature. Earlier theorems of the authors are reviewed, and some new results presented,…

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

Glass transition where viscosity of liquids increases dramatically upon decrease of temperature without any major change in structural properties, remains one of the most challenging problems in condensed matter physics (Cavagna, 2009;…

Statistical Mechanics · Physics 2014-05-29 Smarajit Karmakar , Giorgio Parisi

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

This review presents various aspects of a mean-field spin glass model known as the p-spin spherical spin glass model, which has raised a lot of interest in the study of spin glasses, and also for its possible links with a mean-field theory…

Disordered Systems and Neural Networks · Physics 2008-02-03 A. Barrat

The chapter starts with a historical summary of first attempts to optimize the spin glass Hamiltonian, comparing it to recent results on searching largest cliques in random graphs. Exact algorithms to find ground states in generic spin…

Disordered Systems and Neural Networks · Physics 2023-01-03 Sergio Caracciolo , Alexander K. Hartmann , Scott Kirkpatrick , Martin Weigel

The physics of the glass transition and amorphous materials continues to attract the attention of a wide research community after decades of effort. Supercooled liquids and glasses have been studied numerically since the advent of molecular…

Statistical Mechanics · Physics 2023-02-09 Ludovic Berthier , David R. Reichman

Numerical studies in random systems are plagued with strong finite-size effects and boundary effects. We introduce a window-measurement method as a practical solution to these difficulties. We observe physical quantities only within a…

Disordered Systems and Neural Networks · Physics 2015-06-19 Tota Nakamura , Takayuki Shirakura

In this thesis I discuss combinatorial optimization problems, from the statistical physics perspective. The starting point are the motivations which brought physicists together with computer scientists and mathematicians to work on this…

Disordered Systems and Neural Networks · Physics 2020-01-13 Andrea Di Gioacchino