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In the Potts spin glass model, inspired by the symmetry argument in [arXiv:2310.06745] for the constrained free energy, we study the free energy with self-overlap correction. Similarly, we simplify the Parisi-type formula, originally an…

Probability · Mathematics 2023-12-27 Hong-Bin Chen

Understanding the glassy nature of neural networks is pivotal both for theoretical and computational advances in Machine Learning and Theoretical Artificial Intelligence. Keeping the focus on dense associative Hebbian neural networks, the…

Disordered Systems and Neural Networks · Physics 2022-09-28 Linda Albanese , Francesco Alemanno , Andrea Alessandrelli , Adriano Barra

We study potential presence of statistical-computational gaps (SCG) in symmetric binary perceptrons (SBP) via a parametric utilization of \emph{fully lifted random duality theory} (fl-RDT) [96]. A structural change from decreasingly to…

Machine Learning · Statistics 2026-01-16 Mihailo Stojnic

By the Parisi-Sourlas conjecture, the critical point of a theory with random field (RF) disorder is described by a supersymmeric (SUSY) conformal field theory (CFT), related to a $d-2$ dimensional CFT without SUSY. Numerical studies…

Statistical Mechanics · Physics 2022-08-31 Apratim Kaviraj , Slava Rychkov , Emilio Trevisani

In a previous work [A simplified Parisi Ansatz, Franchini, S., Commun. Theor. Phys., 73, 055601 (2021)] we introduced a simple method to compute the Random Overlap Structure of Aizenmann, Simm and Stars and the full RSB Parisi formula for…

Statistical Mechanics · Physics 2025-10-07 Simone Franchini

We investigate the energy landscape of the spherical mixed even p-spin model near its maximum energy. We relate the distance between pairs of near maxima to the support of the Parisi measure at zero temperature. We then provide an algebraic…

Probability · Mathematics 2017-03-13 Antonio Auffinger , Wei-Kuo Chen

We consider a generalization of the Hopfield model, where the entries of patterns are Gaussian and diluted. We focus on the high-storage regime and we investigate analytically the topological properties of the emergent network, as well as…

Disordered Systems and Neural Networks · Physics 2012-09-28 Elena Agliari , Lorenzo Asti , Adriano Barra , Raffaella Burioni , Guido Uguzzoni

Background Nucleotide sequences contain multiple codes responsible for organism's functioning and structure. They can be investigated by various signal processing methods. These techniques are well suited for indication of frequently…

Quantitative Methods · Quantitative Biology 2007-05-23 Simon Kogan

Pseudospin symmetry (PSS) is a relativistic dynamical symmetry connected with the lower component of the Dirac spinor. Here, we investigate the conservation and breaking of PSS in the single-nucleon resonant states, as an example, using…

Nuclear Theory · Physics 2023-11-23 T. -T. Sun , Z. P. Li , P. Ring

We study the phenomenon of the locking of the order parameter (or synchronization) in spin glasses at low temperatures. When two systems with independent disorders are coupled, their overlaps become similar. A crucial question is how this…

Disordered Systems and Neural Networks · Physics 2026-05-05 Silvio Franz , Giorgio Parisi , Federico Ricci-Tersenghi

The response time of physical computational elements is finite, and neurons are no exception. In hierarchical models of cortical networks each layer thus introduces a response lag. This inherent property of physical dynamical systems…

Neurons and Cognition · Quantitative Biology 2021-10-28 Paul Haider , Benjamin Ellenberger , Laura Kriener , Jakob Jordan , Walter Senn , Mihai A. Petrovici

Statistical mechanics of spin glasses is one of the main strands toward a comprehension of information processing by neural networks and learning machines. Tackling this approach, at the fairly standard replica symmetric level of…

Disordered Systems and Neural Networks · Physics 2023-12-18 Linda Albanese , Andrea Alessandrelli , Alessia Annibale , Adriano Barra

Understanding representational similarity between neural recordings and computational models is essential for neuroscience, yet remains challenging to measure reliably due to the constraints on the number of neurons that can be recorded…

Disordered Systems and Neural Networks · Physics 2025-10-27 Hyunmo Kang , Abdulkadir Canatar , SueYeon Chung

On approaching the dynamical transition temperature, supercooled liquids show heterogeneity over space and time. Static replica theory investigates the dynamical crossover in terms of the free energy landscape (FEL). Two kinds of static…

Statistical Mechanics · Physics 2024-03-19 Hiroshi Frusawa

We consider supersymmetry breaking communicated entirely by the superconformal anomaly in supergravity. This scenario is naturally realized if supersymmetry is broken in a hidden sector whose couplings to the observable sector are…

High Energy Physics - Phenomenology · Physics 2009-10-31 Z. Chacko , Markus A. Luty , Ivan Maksymyk , Eduardo Ponton

The condensed nearest neighbor (CNN) algorithm is a heuristic for reducing the number of prototypical points stored by a nearest neighbor classifier, while keeping the classification rule given by the reduced prototypical set consistent…

Machine Learning · Computer Science 2013-10-01 Eric Christiansen

We study the problem of detecting the presence of a single unknown spike in a rectangular data matrix, in a high-dimensional regime where the spike has fixed strength and the aspect ratio of the matrix converges to a finite limit. This…

Statistics Theory · Mathematics 2018-06-18 Ahmed El Alaoui , Michael I. Jordan

In cond-mat/9907125 the low-temperature behavior of a model for RNA secondary structure was studied. It is claimed that the model exhibits a breaking of the replica symmetry, since the width of the distribution P(q) of overlaps may converge…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander K. Hartmann

Consider a correlated Gaussian random energy model built by successively adding one particle (spin) into the system and imposing the positivity of the associated covariance matrix. We show that the validity of a recently isolated condition…

Disordered Systems and Neural Networks · Physics 2009-11-10 Pierluigi Contucci , Sandro Graffi

This paper presents a constructive algorithm that achieves successful one-shot learning of hidden spike-patterns in a competitive detection task. It has previously been shown (Masquelier et al., 2008) that spike-timing-dependent plasticity…

Neurons and Cognition · Quantitative Biology 2017-08-31 Toby Lightheart , Steven Grainger , Tien-Fu Lu