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In these notes I will review the results that have been obtained in these last years on the computation of the number of metastable states in infinite-range models of disordered systems. This is a particular case of the problem of computing…

Disordered Systems and Neural Networks · Physics 2007-05-23 Giorgio Parisi

Inspired by striking advances in language modeling, there has recently been much interest in developing autogressive sequence models that are amenable to analytical study. In this short note, we consider extensions of simple disordered…

Disordered Systems and Neural Networks · Physics 2025-12-18 Jacob A. Zavatone-Veth , Cengiz Pehlevan

The study of the normalized sum of random variables and its asymptotic behaviour has been and continues to be a central chapter in probability and statistical mechanics. When those variables are independent the central limit theorem ensures…

Mathematical Physics · Physics 2012-12-18 M. Fedele

In this review article, we discuss connections between the physics of disordered systems, phase transitions in inference problems, and computational hardness. We introduce two models representing the behavior of glassy systems, the spiked…

Disordered Systems and Neural Networks · Physics 2022-12-07 David Gamarnik , Cristopher Moore , Lenka Zdeborová

In this talk I will review the approach to spin glasses based on the spontaneously broken replica symmetry. I will concentrate my attention mostly on more general ideas, skipping technical details and stressing the characteristic…

Condensed Matter · Physics 2007-05-23 Giorgio Parisi Dipartimento di fisica Roma

We study the link overlap between two replicas of an Ising spin glass in three dimensions using the Migdal-Kadanoff approximation and scaling arguments based on the droplet picture. For moderate system sizes, the distribution of the link…

Disordered Systems and Neural Networks · Physics 2009-10-31 Barbara Drossel , Hemant Bokil , M. A. Moore , A. J. Bray

Using mappings to computer-science problems and by applying sophisticated algorithms, one can study numerically many problems much better compared to applying standard approaches like Monte Carlo simulations. Here, using calculations of…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. K. Hartmann

We develop a mean-field theory for random quantum spin systems using the spin coherent state path integral representation. After the model is reduced to the mean field one-body Hamiltonian, the integral is analyzed with the aid of several…

Disordered Systems and Neural Networks · Physics 2007-11-20 Kazutaka Takahashi

For ill-posed inverse problems, a regularised solution can be interpreted as a mode of the posterior distribution in a Bayesian framework. This framework enriches the set the solutions, as other posterior estimates can be used as a solution…

Statistics Theory · Mathematics 2013-04-22 Natalia Bochkina

In this work we discuss a short range version of the $p$-spin model. The model is provided with a parameter that allows to control the crossover with the mean field behaviour. We detect a discrepancy between the perturbative approach and…

Disordered Systems and Neural Networks · Physics 2009-10-31 Matteo Campellone , Giorgio Parisi , Paola Ranieri

We generalize the strategy, we recently introduced to prove the existence of the thermodynamic limit for the Sherrington-Kirkpatrick and p-spin models, to a wider class of mean field spin glass systems, including models with multi-component…

Disordered Systems and Neural Networks · Physics 2007-05-23 Francesco Guerra , Fabio L. Toninelli

The out of equilibrium dynamics of finite dimensional spin glasses is considered from a point of view going beyond the standard `mean-field theory' versus `droplet picture' debate of the last decades. The main predictions of both theories…

Statistical Mechanics · Physics 2009-11-07 Alain Barrat , Ludovic Berthier

We study the Blume-Emery-Griffiths spin glass model in presence of an attractive coupling between real replicas, and evaluate the effective potential as a function of the density overlap. We find that there is a region, above the first…

Statistical Mechanics · Physics 2009-11-07 A. de Candia

The effects of random magnetic fields are considered in an Ising spin-glass model defined in the limit of infinite-range interactions. The probability distribution for the random magnetic fields is a double Gaussian, which consists of two…

Statistical Mechanics · Physics 2009-11-13 N. Crokidakis , F. D. Nobre

We derive a number of exact relations between equilibrium and nonequilibrium quantities for spin glasses in external fields using the Jarzynski equality and gauge symmetry. For randomly-distributed longitudinal fields, a lower bound is…

Disordered Systems and Neural Networks · Physics 2015-05-27 Masayuki Ohzeki , Hitoshi Katsuda , Hidetoshi Nishimori

We introduce an approach to derive an effective scalar field theory for the glass transition; the fluctuating field is the overlap between equilibrium configurations. We apply it to the case of constrained liquids for which the introduction…

Disordered Systems and Neural Networks · Physics 2014-05-07 Giulio Biroli , Chiara Cammarota , Gilles Tarjus , Marco Tarzia

We use a random pinning procedure to investigate stable glassy states associated with large deviations of the activity in a model glass-former. We pin particles both from active (equilibrium) configurations and from stable (inactive) glassy…

Statistical Mechanics · Physics 2014-07-02 Christopher J. Fullerton , Robert L. Jack

This PhD thesis is organized as follows. In the first two chapters I will review some basic notions of statistical physics of disordered systems, such as random graph theory, the mean-field approximation, spin glasses and combinatorial…

Disordered Systems and Neural Networks · Physics 2019-10-15 Enrico M. Malatesta

A defining feature of sampling-based motion planning is the reliance on an implicit representation of the state space, which is enabled by a set of probing samples. Traditionally, these samples are drawn either probabilistically or…

Robotics · Computer Science 2019-03-13 Brian Ichter , James Harrison , Marco Pavone

We consider particle systems with mean-field interactions whose distribution is invariant by translations. Under the assumption that the system seen from its centre of mass be reversible with respect to a Gibbs measure, we establish large…

Probability · Mathematics 2019-04-25 Julien Reygner