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Studies have been made on the phase transition phenomena of an oscillator network model based on a standard Hebb learning rule like the Hopfield model. The relative phase informations---the in-phase and anti-phase, can be embedded in the…

Disordered Systems and Neural Networks · Physics 2014-09-08 Toru Aonishi

In the Sherrington-Kirkpatrick (SK) and related mixed $p$-spin models, there is interest in understanding replica symmetry breaking at low temperatures. For this reason, the so-called AT line proposed by de Almeida and Thouless as a…

Probability · Mathematics 2025-07-09 Erik Bates , Leila Sloman , Youngtak Sohn

By using a simple interpolation argument, in previous work we have proven the existence of the thermodynamic limit, for mean field disordered models, including the Sherrington-Kirkpatrick model, and the Derrida p-spin model. Here we extend…

Disordered Systems and Neural Networks · Physics 2007-05-23 Francesco Guerra

In Bayesian inference, computing the posterior distribution from the data is typically a non-trivial problem, which usually requires approximations such as mean-field approaches or numerical methods, like the Monte Carlo Markov Chain. Being…

Disordered Systems and Neural Networks · Physics 2025-07-29 Alfredo Braunstein , Louise Budzynski , Matteo Mariani , Federico Ricci-Tersenghi

Replica Symmetry Breaking is a fascinating phenomenon of spin glasses model which could have consequences also in other field of studies. Although there are several studies regarding the stability between the Replica Symmetric and first…

Disordered Systems and Neural Networks · Physics 2024-10-02 Linda Albanese

The Hopfield model is a paradigmatic model of neural networks that has been analyzed for many decades in the statistical physics, neuroscience, and machine learning communities. Inspired by the manifold hypothesis in machine learning, we…

Disordered Systems and Neural Networks · Physics 2023-05-01 Matteo Negri , Clarissa Lauditi , Gabriele Perugini , Carlo Lucibello , Enrico Malatesta

Dense associative memory, a fundamental instance of modern Hopfield networks, can store a large number of memory patterns as equilibrium states of recurrent networks. While the stationary-state storage capacity has been investigated, its…

Disordered Systems and Neural Networks · Physics 2025-10-29 Kazushi Mimura , Jun'ichi Takeuchi , Yuto Sumikawa , Yoshiyuki Kabashima , Anthony C. C. Coolen

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using auto-associative networks such as the Hopfield model. This kind of model reliably converges…

Neurons and Cognition · Quantitative Biology 2016-05-18 James P. Roach , Leonard M Sander , Michal R. Zochowski

Neural networks are supposed to recognise blurred images (or patterns) of $N$ pixels (bits) each. Application of the network to an initial blurred version of one of $P$ pre-assigned patterns should converge to the correct pattern. In the…

Statistical Mechanics · Physics 2009-11-07 Dietrich Stauffer , Amnon Aharony , Luciano da Fontoura Costa , Joan Adler

We study the critical properties of the weakly disordered two-dimensional Ising and Baxter models in terms of the renormalization group (RG) theory generalized to take into account the replica symmetry breaking (RSB) effects. Recently it…

Condensed Matter · Physics 2009-10-28 D. E. Feldman , A. V. Izyumov , Viktor Dotsenko

We introduce a three-dimensional vectorial extension of the Hopfield associative-memory model in which each neuron is a unit vector on $S^2$ and synaptic couplings are $3\times 3$ blocks generated through a vectorial Hebbian rule. The…

Disordered Systems and Neural Networks · Physics 2025-12-10 F. Gallavotti , A. Zaccone

According to the droplet picture of spin glasses, the low-temperature phase of spin glasses should be replica symmetric. However, analysis of the stability of this state suggested that it was unstable and this instability lends support to…

Disordered Systems and Neural Networks · Physics 2015-06-25 M. A. Moore

The full mean-field solution of spin glass models with a continuous order-parameter function is not directly available and approximate schemes must be used to assess its properties. The averaged physical quantities are to be represented via…

Disordered Systems and Neural Networks · Physics 2013-03-27 V. Janis , A. Kauch , A. Klic

Using numerical self-consistent solutions of a sequence of finite replica symmetry breakings (RSB) and Wilson's renormalization group but with the number of RSB-steps playing a role of decimation scales, we report evidence for a non-trivial…

Disordered Systems and Neural Networks · Physics 2009-11-11 R. Oppermann , D. Sherrington

In this work, we first revise some extensions of the standard Hopfield model in the low storage limit, namely the correlated attractor case and the multitasking case recently introduced by the authors. The former case is based on a…

Disordered Systems and Neural Networks · Physics 2012-05-23 Elena Agliari , Adriano Barra , Andrea De Antoni , Andrea Galluzzi

An encryption of a signal ${\bf s}\in\mathbb{R^N}$ is a random mapping ${\bf s}\mapsto \textbf{y}=(y_1,\ldots,y_M)^T\in \mathbb{R}^M$ which can be corrupted by an additive noise. Given the Encryption Redundancy Parameter (ERP) $\mu=M/N\ge…

Disordered Systems and Neural Networks · Physics 2019-06-11 Yan V Fyodorov

Re-entrance is a novel feature where the phase boundaries of a system exhibit a succession of transitions between two phases A and B, like A-B-A-B, when just one parameter is varied monotonically. This type of re-entrance is displayed by…

Quantum Gases · Physics 2015-06-05 M. Pino , J. Prior , A. M. Somoza , D. Jaksch , S. R. Clark

Spontaneous symmetry breaking (SSB) occurs when a many-body system governed by a symmetric Hamiltonian, and prepared in a symmetry-broken state by the application of a field coupling to its order parameter $O$, retains a finite $O$ value…

Strongly Correlated Electrons · Physics 2024-12-23 Filippo Caleca , Saverio Bocini , Fabio Mezzacapo , Tommaso Roscilde

We study the Hopfield model on a random graph in scaling regimes where the average number of connections per neuron is a finite number and where the spin dynamics is governed by a synchronous execution of the microscopic update rule…

Condensed Matter · Physics 2016-08-16 I. Pérez Castillo , N. S. Skantzos

Spin glass theory, as a paradigm for describing disordered magnetic systems, constitutes a prominent subject of study within statistical physics. Replica symmetry breaking (RSB), as one of the pivotal concepts for the understanding of spin…

Disordered Systems and Neural Networks · Physics 2023-12-19 Yifei Qi , Longqun Ni , Zhenyu Ye , Jiaojiao Zhang , Xingyu Bao , Pan Wang , Yunjiang Rao , Ernesto P. Raposo , Anderson S. L. Gomes , Zinan Wang
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