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Magnetizations are introduced to the Generalized Random Energy Model (GREM) and numerical simulations on ac susceptibility is made for direct comparison with experiments in glassy materials. Prominent dynamical natures of spin glasses, {\it…

Disordered Systems and Neural Networks · Physics 2009-10-31 Munetaka Sasaki , Koji Nemoto

We determine explicit variational expressions for the free energy of mean-field spin glasses in a transversal magnetic field, whose glass interaction is given by a hierarchical Gaussian potential as in Derrida's Generalized Random Energy…

Mathematical Physics · Physics 2022-07-20 Chokri Manai , Simone Warzel

The complete phase diagram of Random Energy Model (REM) is obtained for complex temperatures using the method proposed by Derrida. We find the density of zeroes for statistical sum. Then the method is applied to Generalized Random Energy…

Disordered Systems and Neural Networks · Physics 2009-10-31 D. B. Saakian

In this thesis, we consider several Random Energy Models. This includes Derrida's Random Energy Model (REM) and Generalized Random Energy Model (GREM) and a nonhierarchical version (BK-GREM) by Bolthausen and Kistler. The limiting free…

Probability · Mathematics 2007-11-09 Nabin Kumar Jana

In an earlier work, the statistical physics associated with finite--temperature decoding of code ensembles, along with the relation to their random coding error exponents, were explored in a framework that is analogous to Derrida's random…

Information Theory · Computer Science 2016-11-15 Neri Merhav

We study the random energy model with a hierarchical structure known as the generalized random energy model (GREM). In contrast to the original analysis by the microcanonical ensemble formalism, we investigate the GREM by the canonical…

Disordered Systems and Neural Networks · Physics 2010-11-16 Tomoyuki Obuchi , Kazutaka Takahashi , Koujin Takeda

The Quantum Random Energy Model (QREM) is a random matrix of Anderson-type which describes effects of a transversal magnetic field on Derrida's spin glass. The model exhibits a glass phase as well as a classical and a quantum paramagnetic…

Mathematical Physics · Physics 2023-06-28 Chokri Manai , Simone Warzel

In order to study the activated dynamics of mean-field glasses, which takes place on times of order exp(N), where N is the system size, we introduce a new model, the Correlated Random Energy Model (CREM), that allows for a smooth…

Disordered Systems and Neural Networks · Physics 2018-08-01 Marco Baity-Jesi , Alexandre Achard-de Lustrac , Giulio Biroli

We compute the pressure of the random energy model (REM) and generalized random energy model(GREM) by establishing variational upper and lower bounds. For the upper bound, we generalize Guerra's ``broken replica symmetry bounds",and…

Mathematical Physics · Physics 2015-09-29 Cristian Giardina' , Shannon Starr

A quadratic extension of REM has been treated. Discussed here is the origin of relation of REM to strings and other complex physical phenomena. Two basic features of the REM class of complex phenomena were identified: the double…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. B. Saakian

We introduce a natural nonhierarchical version of Derrida's generalized random energy model. We prove that, in the thermodynamical limit, the free energy is the same as that of a suitably constructed GREM.

Probability · Mathematics 2007-05-23 Erwin Bolthausen , Nicola Kistler

Recently, Bauke and Mertens conjectured that the local statistics of energies in random spin systems with discrete spin space should in most circumstances be the same as in the random energy model. Here we give necessary conditions for this…

Disordered Systems and Neural Networks · Physics 2007-05-23 Anton Bovier , Irina Kurkova

We discuss a generalization of the conditions of validity of the interpolation method for the density of quenched free energy of mean field spin glasses. The condition is written just in terms of the $L^2$ metric structure of the Gaussian…

Mathematical Physics · Physics 2020-12-02 Roberto Boccagna , Davide Gabrielli

We introduce the Generalized Energy Based Model (GEBM) for generative modelling. These models combine two trained components: a base distribution (generally an implicit model), which can learn the support of data with low intrinsic…

Machine Learning · Statistics 2021-12-22 Michael Arbel , Liang Zhou , Arthur Gretton

Methods for studying droplets in models with quenched disorder are critically examined. Low energy excitations in two dimensional models are investigated by finding minimal energy interior excitations and by computing the effect of bulk…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Alan Middleton

We present a numerical study of ground states of the dilute versions of the Sherrington-Kirkpatrick (SK) mean-field spin glass. In contrast to so-called "sparse" mean-field spin glasses that have been studied widely on random networks of…

Disordered Systems and Neural Networks · Physics 2022-04-21 Stefan Boettcher

Recently, Bauke and Mertens conjectured that the local statistics of energies in random spin systems with discrete spin space should in most circumstances be the same as in the random energy model. This was proven in a large class of models…

Disordered Systems and Neural Networks · Physics 2009-11-11 Anton Bovier , Irina Kurkova

In this paper the Random Energy Model(REM) under exponential type environment is considered which includes double exponential and Gaussian cases. Limiting Free Energy is evaluated in these models. Limiting Gibbs' distribution is evaluated…

Probability · Mathematics 2007-05-23 Nabin Kumar Jana

These are notes for a mini-course on the extremes of correlated random fields which I gave in the spring 2013 in Marseille. The first chapter recalls the paradigmatic random energy models with finitely many scales introduced by B. Derrida…

Probability · Mathematics 2014-12-03 Nicola Kistler

We introduce a Random Energy Model on a hierarchical lattice where the interaction strength between variables is a decreasing function of their mutual hierarchical distance, making it a non-mean field model. Through small coupling series…

Statistical Mechanics · Physics 2014-09-09 Michele Castellana , Aurelien Decelle , Silvio Franz , Marc Mezard , Giorgio Parisi
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