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We derive the zero-temperature phase diagram of spin glass models with a generic fraction of ferromagnetic interactions on the Bethe lattice. We use the cavity method at the level of one-step replica symmetry breaking (1RSB) and we find…

Disordered Systems and Neural Networks · Physics 2009-11-10 Tommaso Castellani , Florent Krzakala , Federico Ricci-Tersenghi

The retrieval behavior and thermodynamic properties of symmetrically diluted Q-Ising neural networks are derived and studied in replica-symmetric mean-field theory generalizing earlier works on either the fully connected or the symmetrical…

Disordered Systems and Neural Networks · Physics 2009-11-07 W. K. Theumann , R. Erichsen

We study the low temperature properties of p-spin glass models with finite connectivity and of some optimization problems. Using a one-step functional replica symmetry breaking Ansatz we can solve exactly the saddle-point equations for…

Disordered Systems and Neural Networks · Physics 2009-11-07 S. Franz , M. Leone , F. Ricci-Tersenghi , R. Zecchina

The thermodynamic and retrieval properties of the Ashkin-Teller neural network model storing an infinite number of patterns are examined in the replica-symmetric mean-field approximation. In particular, for linked patterns…

Disordered Systems and Neural Networks · Physics 2009-10-31 D. Bolle , P. Kozlowski

The statistical mechanics of a two-state Ising spin-glass model with finite random connectivity, in which each site is connected to a finite number of other sites, is extended in this work within the replica technique to study the phase…

Statistical Mechanics · Physics 2011-06-20 R. Erichsen , W. K. Theumann

We study the competition between ferromagnetic and spin glass phases using a system of coupled infinite-range Ising and Sherrington-Kirkpatrick models. We obtain the replica-symmetric solution for the free energy of this system in terms of…

Disordered Systems and Neural Networks · Physics 2023-06-28 Fateme Izadi , Reza Sepehrinia

Continuous attractor neural networks generate a set of smoothly connected attractor states. In memory systems of the brain, these attractor states may represent continuous pieces of information such as spatial locations and head directions…

Disordered Systems and Neural Networks · Physics 2019-01-16 Chi Chung Alan Fung , Tomoki Fukai

We investigate thermodynamic phase transitions of the joint presence of spin glass (SG) and random field (RF) using a random graph model that allows us to deal with the quenched disorder. Therefore, the connectivity becomes a controllable…

Disordered Systems and Neural Networks · Physics 2021-02-24 R. Erichsen , A. Silveira , S. G. Magalhaes

Infinite-range spin-glass models with Levy-distributed interactions show a spin-glass transition with similarities to both the Sherrington-Kirkpatrick model and to disordered spin systems on finite connectivity random graphs. Despite the…

Disordered Systems and Neural Networks · Physics 2009-11-13 K. Janzen , A. K. Hartmann , A. Engel

The global phase diagram of the Ashkin-Teller spin glass is calculated in d = 3 spatial dimensions by renormalization-group theory. Depending on the value of the positive or negative four-spin interaction, qualitatively different topologies…

Disordered Systems and Neural Networks · Physics 2025-07-08 Alican Saray , A. Nihat Berker

This work presents a statistical mechanics characterization of neural networks, motivated by the replica symmetry breaking (RSB) phenomenon in spin glasses. A Hopfield-type spin glass model is constructed from a given feedforward neural…

Disordered Systems and Neural Networks · Physics 2025-08-12 Jun Li

We study a model of associative memory based on a neural network with small-world structure. The efficacy of the network to retrieve one of the stored patterns exhibits a phase transition at a finite value of the disorder. The more ordered…

Adaptation and Self-Organizing Systems · Physics 2009-11-10 Luis G. Morelli , Guillermo Abramson , Marcelo N. Kuperman

We extend a recently introduced class of exactly solvable models for recurrent neural networks with competition between 1D nearest neighbour and infinite range information processing. We increase the potential for further frustration and…

Disordered Systems and Neural Networks · Physics 2009-10-31 N. S. Skantzos , A. C. C. Coolen

We study how the dynamics of a class of discrete dynamical system models for neuronal networks depends on the connectivity of the network. Specifically, we assume that the network is an Erd\H{o}s-R\'{enyi} random graph and analytically…

Dynamical Systems · Mathematics 2014-04-23 Winfried Just , Sungwoo Ahn

The zero temperature phase diagram of spin glasses on finite connectivity graphs is investigated, with or without magnetic field and/or ferromagnetic bias, for mean field (using the cavity method) and Edwards-Anderson (using numerical…

Disordered Systems and Neural Networks · Physics 2009-11-10 Florent Krzakala

We study graded response attractor neural networks with asymmetrically extremely dilute interactions and Langevin dynamics. We solve our model in the thermodynamic limit using generating functional analysis, and find (in contrast to the…

Disordered Systems and Neural Networks · Physics 2016-08-31 J. P. L. Hatchett , A. C. C. Coolen

We study the Ising spin glass model on scale-free networks generated by the static model using the replica method. Based on the replica-symmetric solution, we derive the phase diagram consisting of the paramagnetic (P), ferromagnetic (F),…

Statistical Mechanics · Physics 2009-11-11 D. -H. Kim , G. J. Rodgers , B. Kahng , D. Kim

We study the equilibrium and dynamical properties of a spherical version of the frustrated Blume-Emery-Griffiths model at mean field level for attractive particle-particle coupling (K>0). Beyond a second order transition line from a…

Statistical Mechanics · Physics 2009-11-10 A. Caiazzo , A. Coniglio , M. Nicodemi

We study spin glasses on random lattices with finite connectivity. In the infinite connectivity limit they reduce to the Sherrington Kirkpatrick model. In this paper we investigate the expansion around the high connectivity limit. Within…

Disordered Systems and Neural Networks · Physics 2009-11-07 Giorgio Parisi , Francesca Tria

We perform a stationary state replica analysis for a layered network of Ising spin neurons, with recurrent Hebbian interactions within each layer, in combination with strictly feed-forward Hebbian interactions between successive layers.…

Condensed Matter · Physics 2009-10-28 A. C. C. Coolen , L. Viana