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We present a resummed mean-field approximation for inferring the parameters of an Ising or a Potts model from empirical, noisy, one- and two-point correlation functions. Based on a resummation of a class of diagrams of the small correlation…

Disordered Systems and Neural Networks · Physics 2016-10-19 Hugo Jacquin , A. Rancon

We study the free energy of mixed $p$-spin spin glass models enriched with an additional magnetic field given by the canonical Gaussian field associated with a Ruelle probability cascade. We prove that this free energy converges to the…

Probability · Mathematics 2020-09-30 Jean-Christophe Mourrat , Dmitry Panchenko

A wide class of problems in combinatorics, computer science and physics can be described along the following lines. There are a large number of variables ranging over a finite domain that interact through constraints that each bind a few…

Probability · Mathematics 2017-11-17 Victor Bapst , Amin Coja-Oghlan

We compute analytically the probability distribution of large deviations in the spin-glass free energy for the Sherrington-Kirkpatrick mean field model, i.e. we compute the exponentially small probability of finding a system with intensive…

Disordered Systems and Neural Networks · Physics 2012-10-31 Giorgio Parisi , Tommaso Rizzo

We develop a cavity method in the spherical Sherrington-Kirkpatrick model at high temperature and small external field. As one application we compute the limit of the covariance matrix for fluctuations of the overlap and magnetization.

Probability · Mathematics 2010-02-01 Dmitry Panchenko

We discuss the mean-field theory of spin-glass models with frustrated long-range random spin exchange. We analyze the reasons for breakdown of the simple mean-field theory of Sherrington and Kirkpatrick. We relate the replica-symmetry…

Disordered Systems and Neural Networks · Physics 2015-06-24 Václav Janiš

We propose a new method for the problems of computing free energy and surface pressure for various statistical mechanics models on a lattice $\Z^d$. Our method is based on representing the free energy and surface pressure in terms of…

Probability · Mathematics 2015-05-13 David Gamarnik , Dmitriy Katz

Using a formalism based on the spectral decomposition of the replicated transfer matrix for disordered Ising models, we obtain several results that apply both to isolated one-dimensional systems and to locally tree-like graph and factor…

Disordered Systems and Neural Networks · Physics 2014-08-04 Carlo Lucibello , Flaviano Morone , Tommaso Rizzo

In [Physical Magazine, 35(3):593-601, 1977], Thouless, Anderson, and Palmer derived a representation for the free energy of the Sherrington-Kirkpatrick model, called the TAP free energy, written as the difference of the energy and entropy…

Probability · Mathematics 2019-01-15 Wei-Kuo Chen , Dmitry Panchenko

We suggest a possible approach to proving the M\'ezard-Parisi formula for the free energy in the diluted spin glass models, such as diluted K-spin or random K-sat model at any positive temperature. In the main contribution of the paper, we…

Probability · Mathematics 2016-01-27 Dmitry Panchenko

We propose a general scheme in which disordered systems are allowed to sacrifice energy equi-partitioning and separate into a hierarchy of ergodic sub-systems (clusters) with different characteristic time-scales and temperatures. The…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. van Mourik , A. C. C. Coolen

We provide a strategy to find in few elementary calculations the critical exponents of the overlaps for dilute spin glasses, in absence of external field. Such a strategy is based on the expansion of a suitably perturbed average of the…

Statistical Mechanics · Physics 2007-10-25 Luca De Sanctis , Adriano Barra , Viola Folli

We study the set of solutions of random k-satisfiability formulae through the cavity method. It is known that, for an interval of the clause-to-variables ratio, this decomposes into an exponential number of pure states (clusters). We refine…

Disordered Systems and Neural Networks · Physics 2009-11-13 Andrea Montanari , Federico Ricci-Tersenghi , Guilhem Semerjian

In a companion paper we developed the generalized TAP approach for general multi-species spherical mixed $p$-spin models. In this paper, we use it to compute the limit of the free energy at any temperature for all pure multi-species…

Probability · Mathematics 2022-05-04 Eliran Subag

We generalize the supersymmetry method in Random Matrix Theory to arbitrary rotation invariant ensembles. Our exact approach further extends a previous contribution in which we constructed a supersymmetric representation for the class of…

Mathematical Physics · Physics 2009-11-11 Thomas Guhr

We introduce a simple enhanced sampling approach for the calculation of free energy differences and barriers along a one-dimensional reaction coordinate. First, a small number of short nonequilibrium simulations are carried out along the…

Chemical Physics · Physics 2021-11-03 Kristof M. Bal

In this paper we study the Random energy model - so called toy model of the spin glass theory - where the underlying distributions are compactly supported. We prove a general theorem on the asymptotics of free energy and obtain formulae in…

Probability · Mathematics 2007-05-23 Nabin Kumar Jana

We investigate the large deviation behavior of the overlap probability density in the Sherrington--Kirkpatrick model from several analytical perspectives. First we analyze the spin glass phase using the coupled replica scheme. Here…

Statistical Mechanics · Physics 2009-11-07 Alain Billoire , Silvio Franz , Enzo Marinari

We introduce the Eggbox Ising model, a tunable construction of rugged energy landscapes defined by distances to a prescribed set of patterns. Correlated pattern ensembles realize arbitrary k-step replica-symmetry-breaking structures and…

Statistical Mechanics · Physics 2026-02-20 Mutian Shen , Yichen Xu , Zohar Nussinov

The free energy of TAP-solutions for the SK-model of mean field spin glasses can be expressed as a nonlinear functional of local terms: we exploit this feature in order to contrive abstract REM-like models which we then solve by a classical…

Disordered Systems and Neural Networks · Physics 2023-07-19 Nicola Kistler , Marius Alexander Schmidt , Giulia Sebastiani