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Symmetry breaking--the phenomenon in which the symmetry of a system is not inherited by its stable states--underlies pattern formation, superconductivity, and numerous other effects. Recent theoretical work has established the possibility…

Adaptation and Self-Organizing Systems · Physics 2021-09-24 Ferenc Molnar , Takashi Nishikawa , Adilson E. Motter

We discuss the concept of Pure State of the Replica Symmetry Breaking ansatz in finite and infinite spin systems without averaging on the disorder, nor using replicas. Consider a system of n spins $\sigma\in\Omega^{n}$ with the usual set…

Statistical Mechanics · Physics 2025-08-06 Simone Franchini

Distributions of data or sensory stimuli often enjoy underlying invariances. How and to what extent those symmetries are captured by unsupervised learning methods is a relevant question in machine learning and in computational neuroscience.…

Disordered Systems and Neural Networks · Physics 2020-06-24 Moshir Harsh , Jérôme Tubiana , Simona Cocco , Remi Monasson

We study a simple extended model of oscillator neural networks capable of storing sparsely coded phase patterns, in which information is encoded both in the mean firing rate and in the timing of spikes. Applying the methods of statistical…

Disordered Systems and Neural Networks · Physics 2009-10-31 Masaki Nomura , Toshio Aoyagi

High-order extensions of the Hopfield model are known to exhibit dramatically enhanced storage capacity at equilibrium, while their dynamical retrieval properties remain less well understood. In our previous work, we carried out a dynamical…

Statistical Mechanics · Physics 2026-04-06 Yuto Sumikawa , Yoshiyuki Kabashima

There is a rich history of expressing the limiting free energy of mean-field spin glasses as a variational formula over probability measures on $[0,1]$, where the measure represents the similarity (or "overlap") of two independently sampled…

Mathematical Physics · Physics 2025-07-09 Erik Bates , Youngtak Sohn

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 describe a novel method which allows the treatment of high orders of replica-symmetry-breaking (RSB) at low temperatures as well as at T=0 directly, without a need for approximations or scaling assumptions. It yields the low temperature…

Disordered Systems and Neural Networks · Physics 2013-05-29 Manuel J. Schmidt , Reinhold Oppermann

Models of interacting complex systems provide the fundamental statistical physics reference frame for the study and the understanding of associative memories, machine learning, and the dynamics of neural networks. On the other hand,…

We report large effects of Parisi replica permutation symmetry breaking (RPSB) on elementary excitations of fermionic systems with frustrated magnetic interactions. The electronic density of states is obtained exactly in the zero…

Disordered Systems and Neural Networks · Physics 2009-10-31 R. Oppermann , B. Rosenow

Associative memory, a form of content-addressable memory, facilitates information storage and retrieval in many biological and physical systems. In statistical mechanics models, associative memory at equilibrium is represented through…

Disordered Systems and Neural Networks · Physics 2022-03-08 Agnish Kumar Behera , Madan Rao , Srikanth Sastry , Suriyanarayanan Vaikuntanathan

The random energy model (REM) is the simplest spin glass model which exhibits replica symmetry breaking. It is well known since the 80's that its overlaps are non-selfaveraging and that their statistics satisfy the predictions of the…

Disordered Systems and Neural Networks · Physics 2024-08-28 Bernard Derrida , Peter Mottishaw

A scaling theory of replica symmetry breaking (RSB) in the SK-model is presented in the framework of critical phenomena for the scaling regime of small inverse RSB-orders, small temperatures, small magnetic fields, and near opposite…

Disordered Systems and Neural Networks · Physics 2009-11-13 Reinhold Oppermann , Manuel J. Schmidt

Recognizing symmetries in data allows for significant boosts in neural network training, which is especially important where training data are limited. In many cases, however, the exact underlying symmetry is present only in an idealized…

High Energy Physics - Phenomenology · Physics 2025-04-07 Seth Nabat , Aishik Ghosh , Edmund Witkowski , Gregor Kasieczka , Daniel Whiteson

A single McCulloch-Pitts neuron, that is, the simple perceptron is studied, with focus on the region beyond storage capacity. It is shown that Parisi's hierarchical ansatz for the overlap matrix of the synaptic couplings with so called…

Disordered Systems and Neural Networks · Physics 2015-06-24 G. Gyorgyi , P. Reimann

We derive, within the replica formalism, a generalisation of the Crisanti-Sommers formula to describe the large deviation function (LDF) ${\cal L}(e)$ for the speed-$N$ atypical fluctuations of the intensive ground-state energy $e$ of a…

Statistical Mechanics · Physics 2024-12-17 Bertrand Lacroix-A-Chez-Toine , Yan V. Fyodorov , Pierre Le Doussal

We consider mean-field vector spin glasses with possibly non-convex interactions. Up to a small perturbation of the parameters defining the model, the asymptotic behavior of the Gibbs measure is described in terms of a critical point of an…

Probability · Mathematics 2026-01-06 Hong-Bin Chen , Jean-Christophe Mourrat

One of the key predictions of Parisi's broken replica symmetry theory of spin glasses is the existence of a phase transition in an applied field to a state with broken replica symmetry. This transition takes place at the de Almeida-Thouless…

Disordered Systems and Neural Networks · Physics 2024-12-12 Bharadwaj Vedula , M. A. Moore , Auditya Sharma

The fermionic Ising spin glass models in a transverse field are investigated in a Grassmann path integral formalism. The Parisi's scheme of one-step replica symmetry breaking (RSB) is used within the static ansatz. This formalism has…

Strongly Correlated Electrons · Physics 2009-11-11 F. M. Zimmer , S. G. Magalhaes

In this work we study numerically the out of equilibrium dynamics of the Hopfield model for associative memory inside its spin-glass phase. Besides its interest as a neural network model it can also be considered as a prototype of fully…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. A. Montemurro , F. A. Tamarit , D. A. Stariolo , S. A. Cannas