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Related papers: Exploring high-dimensional random landscapes: from…

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We study rough high-dimensional landscapes in which an increasingly stronger preference for a given configuration emerges. Such energy landscapes arise in glass physics and inference. In particular we focus on random Gaussian functions, and…

Disordered Systems and Neural Networks · Physics 2019-01-09 Valentina Ros , Gerard Ben Arous , Giulio Biroli , Chiara Cammarota

Our goal is to discuss in detail the calculation of the mean number of stationary points and minima for random isotropic Gaussian fields on a sphere as well as for stationary Gaussian random fields in a background parabolic confinement.…

Mathematical Physics · Physics 2015-11-24 Yan V Fyodorov

We review recent developments on the characterization of random landscapes in high-dimension. We focus in particular on the problem of characterizing the landscape topology and geometry, discussing techniques to count and classify its…

Disordered Systems and Neural Networks · Physics 2023-04-12 Valentina Ros , Yan V. Fyodorov

We define a new family of random spin models with one-dimensional structure, finite-range multi-spin interactions, and bounded average degree (number of interactions in which each spin participates). Unfrustrated ground states can be…

Statistical Mechanics · Physics 2009-04-13 Andrea Montanari , Antoine Sinton

We compute the distribution of triplets of stationary points in the energy landscape of the spherical p-spin model, by evaluating the quenched three-point complexity by means of the Kac-Rice formalism. We show the occurrence of transitions…

Disordered Systems and Neural Networks · Physics 2025-03-12 Alessandro Pacco , Alberto Rosso , Valentina Ros

Glassy behavior is one of the main open problems in condensed matter physics. In this thesis, we approach the problem by studying spin-glasses and colloids, using several complementary strategies. From the point of view of model building,…

Disordered Systems and Neural Networks · Physics 2013-09-10 B. Seoane

In these lectures I will present an introduction to the modern way of studying the properties of glassy systems. I will start from soluble models of increasing complications, the Random Energy Model, the $p$-spins interacting model and I…

Disordered Systems and Neural Networks · Physics 2009-10-30 Giorgio Parisi

The purpose of this manuscript is to review my recent activity on three main research topics. The first concerns the nature of low temperature amorphous solids and their relation with the spin glass transition in a magnetic field. This is…

Disordered Systems and Neural Networks · Physics 2024-05-13 Pierfrancesco Urbani

Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

We give an asymptotic evaluation of the complexity of spherical p-spin spin-glass models via random matrix theory. This study enables us to obtain detailed information about the bottom of the energy landscape, including the absolute minimum…

Probability · Mathematics 2011-11-08 A. Auffinger , G. Ben Arous , J. Cerny

We use the Kac-Rice formula and results from random matrix theory to obtain the average number of critical points of a family of high-dimensional empirical loss functions, where the data are correlated $d$-dimensional Gaussian vectors,…

Machine Learning · Computer Science 2026-01-14 Theodoros G. Tsironis , Aris L. Moustakas

This paper discusses the dynamical properties of $p$-spin models with Kac kind interactions. For large but finite interaction range $R$ one finds two different time scales for relaxation. A first relaxation roughly independent of $R$ where…

Statistical Mechanics · Physics 2008-09-16 Silvio Franz

We present a statistical method for complex energy landscape exploration which provides information on the metastable states--or valleys--actually explored by an unperturbed aging process following a quench. Energy fluctuations of record…

Statistical Mechanics · Physics 2009-11-10 Jesper Dall , Paolo Sibani

The complex dynamics of an increasing number of systems is attributed to the emergence of a rugged energy landscape with an exponential number of metastable states. To develop this picture into a predictive dynamical theory I discuss how to…

Disordered Systems and Neural Networks · Physics 2021-09-15 Tommaso Rizzo

In these notes we discuss tools and concepts that emerge when studying high-dimensional random landscapes, i.e., random functions on high-dimensional spaces. As an illustrative example, we consider an inference problem in two forms:…

Disordered Systems and Neural Networks · Physics 2025-08-12 Valentina Ros

We study the dynamics of a quantum $p$-spin glass model starting from initial states defined in microcanonical shells, in a classical regime. We compute different chaos estimators, such as the Lyapunov exponent and the Kolmogorov-Sinai…

Disordered Systems and Neural Networks · Physics 2023-11-17 Lorenzo Correale , Anatoli Polkovnikov , Marco Schirò , Alessandro Silva

The spherical p-spin model is not only a fundamental model in statistical mechanics of disordered system, but has recently gained popularity since many hard problems in machine learning can be mapped on it. Thus the study of the out of…

Disordered Systems and Neural Networks · Physics 2020-09-02 Giampaolo Folena , Silvio Franz , Federico Ricci-Tersenghi

Systems with a complex dynamics like glasses or models of biological evolution are often pictured in terms of complex landscapes, with a large number of possible collective states. We show on the example of a stochastic spin model with…

Disordered Systems and Neural Networks · Physics 2026-02-03 Laura Guislain , Eric Bertin

In these notes the main theoretical concepts and techniques in the field of mean-field spin-glasses are reviewed in a compact and pedagogical way, for the benefit of the graduate and undergraduate student. One particular spin-glass model is…

Disordered Systems and Neural Networks · Physics 2009-11-11 Tommaso Castellani , Andrea Cavagna

This Ph.D. thesis is divided in two parts. The first one concerns the equilibrium properties of glassy systems. Some aspects of the phenomenology of glasses and of theories attempting to describe them are reviewed in chapter 1. A study of…

Disordered Systems and Neural Networks · Physics 2007-05-23 F. Zamponi
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