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In this review article, we discuss connections between the physics of disordered systems, phase transitions in inference problems, and computational hardness. We introduce two models representing the behavior of glassy systems, the spiked…

Disordered Systems and Neural Networks · Physics 2022-12-07 David Gamarnik , Cristopher Moore , Lenka Zdeborová

This article reviews recent studies of mean-field and one dimensional quantum disordered spin systems coupled to different types of dissipative environments. The main issues discussed are: (i) The real-time dynamics in the glassy phase and…

Disordered Systems and Neural Networks · Physics 2009-11-10 Leticia F. Cugliandolo

We introduce a hierarchical class of approximations of the random Ising spin glass in $d$ dimensions. The attention is focused on finite clusters of spins where the action of the rest of the system is properly taken into account. At the…

Disordered Systems and Neural Networks · Physics 2009-10-30 R. Baviera , M. Pasquini , M. Serva

We study energy landscape and dynamics of the three-dimensional Heisenberg Spin Glass model in the paramagnetic phase, i.e. for temperature $T$ larger than the critical temperature $T_\mathrm{c}$. The landscape is non-trivially related to…

Disordered Systems and Neural Networks · Physics 2019-09-24 Marco Baity-Jesi , Victor Martin-Mayor

We study spin glasses with Kac type interaction potential for small but finite inverse interaction range $\gamma$. Using the theoretical setup of coupled replicas, through the replica method we argue that the probability of overlap profiles…

Disordered Systems and Neural Networks · Physics 2009-11-10 Silvio Franz , Fabio Lucio Toninelli

Describing the complex landscape of infinite-dimensional free energy is generally a challenging problem. This difficulty arises from the existence of numerous minimizers and, consequently, a vast number of saddle points. These factors make…

Soft Condensed Matter · Physics 2025-07-15 Keiichiro Kagawa , Takeshi Watanabe , Yasumasa Nishiura

Theoretical challenges in understanding the nature of glass and the glass transition remain significant open questions in statistical and condensed matter physics. As a prototypical example of complex physical systems, glasses and the…

Disordered Systems and Neural Networks · Physics 2026-01-21 Xin-Jia Zhou , Feng Yang , Xiao-Dong Yang , Lin Ma , Zhen-Wei Wu

Over the past decades, a great body of theoretical and mathematical work has been devoted to random-matrix descriptions of open quantum systems. In these notes, based on lectures delivered at the Les Houches Summer School "Stochastic…

Disordered Systems and Neural Networks · Physics 2017-01-09 Henning Schomerus

We review several models of glassy systems where the randomness is self generated, i.e. already an infinitesimal amount of disorder is sufficient to cause a transition to a non-ergodic, glassy state. We discuss the application of the…

Disordered Systems and Neural Networks · Physics 2011-01-05 Maxim Dzero , Joerg Schmalian , Peter G. Wolynes

We analyze the landscape of general smooth Gaussian functions on the sphere in dimension $N$, when $N$ is large. We give an explicit formula for the asymptotic complexity of the mean number of critical points of finite and diverging index…

Probability · Mathematics 2013-12-17 Antonio Auffinger , Gerard Ben Arous

We use a random pinning procedure to study amorphous order in two glassy spin models. On increasing the concentration of pinned spins at constant temperature, we find a sharp crossover (but no thermodynamic phase transition) from bulk…

Statistical Mechanics · Physics 2015-03-19 Robert L. Jack , Ludovic Berthier

Many soft and biological materials display so-called 'soft glassy' dynamics; their constituents undergo anomalous random motions and complex cooperative rearrangements. A recent simulation model of one soft glassy material, a coarsening…

We investigate a model of high-dimensional dynamical variables with all-to-all interactions that are random and non-reciprocal. We characterize its phase diagram and show that the model can exhibit chaotic dynamics. We show that the…

Disordered Systems and Neural Networks · Physics 2025-12-15 Samantha J. Fournier , Alessandro Pacco , Valentina Ros , Pierfrancesco Urbani

In this work we analyse quantitatively the interplay between the loss landscape and performance of descent algorithms in a prototypical inference problem, the spiked matrix-tensor model. We study a loss function that is the negative…

Machine Learning · Computer Science 2020-01-22 Stefano Sarao Mannelli , Florent Krzakala , Pierfrancesco Urbani , Lenka Zdeborová

This PhD thesis is organized as follows. In the first two chapters I will review some basic notions of statistical physics of disordered systems, such as random graph theory, the mean-field approximation, spin glasses and combinatorial…

Disordered Systems and Neural Networks · Physics 2019-10-15 Enrico M. Malatesta

We present a null model for single- and multi-layered complex systems constructed using homogeneous and isotropic random Gaussian maps. By means of a Kac-Rice formalism, we show that the mean number of fixed points can be calculated as the…

Mathematical Physics · Physics 2018-11-14 J. R. Ipsen , P. J. Forrester

Quantifying stochastic processes is essential to understand many natural phenomena, particularly in biology, including cell-fate decision in developmental processes as well as genesis and progression of cancers. While various attempts have…

Statistical Mechanics · Physics 2017-06-28 Ying Tang , Ruoshi Yuan , Gaowei Wang , Xiaomei Zhu , Ping Ao

Diverse equilibrium systems with heterogeneous interactions lie at the edge of stability. Such marginally stable states are dynamically selected as the most abundant ones or as those with the largest basins of attraction. On the other hand,…

Disordered Systems and Neural Networks · Physics 2025-10-10 Carles Martorell , Rubén Calvo , Alessia Annibale , Miguel A. Muñoz

We propose a semiclassical framework for solving open quantum dynamics in driven-dissipative spin systems. Our method consists of generalized spin-wave approximations tailored to describing quantum trajectories unravelled from the master…

Quantum Physics · Physics 2026-04-24 Zejian Li , Anna Delmonte , Rosario Fazio

In agricultural landscapes, the composition and spatial configuration of cultivated and semi-natural elements strongly impact species dynamics, their interactions and habitat connectivity. To allow for landscape structural analysis and…

Populations and Evolution · Quantitative Biology 2020-03-05 Patrizia Zamberletti , Julien Papaïx , Edith Gabriel , Thomas Opitz
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