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We introduce a class of dissipative quantum spin models with local interactions and without quenched disorder that show glassy behaviour. These models are the quantum analogs of the classical facilitated spin models. Just like their…

Statistical Mechanics · Physics 2012-07-31 Beatriz Olmos , Igor Lesanovsky , Juan P. Garrahan

We introduce and study a model which admits a complex landscape without containing quenched disorder. Continuing our previous investigation we introduce a disordered model which allows us to reconstruct all the main features of the original…

Condensed Matter · Physics 2009-10-22 Enzo Marinari , Giorgio Parisi , Felix Ritort

Rich out of equilibrium collective dynamics of strongly interacting large assemblies emerge in many areas of science. Some intriguing and not fully understood examples are the glassy arrest in atomic, molecular or colloidal systems,…

Statistical Mechanics · Physics 2023-05-03 Leticia F. Cugliandolo

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

Dynamical linked cluster expansions are linked cluster expansions with hopping parameter terms endowed with their own dynamics. This amounts to a generalization from 2-point to point-link-point interactions. An associated graph theory with…

Condensed Matter · Physics 2007-05-23 H. Meyer-Ortmanns , T. Reisz

These lecture notes can be read in two ways. The first two Sections contain a review of the phenomenology of several physical systems with slow nonequilibrium dynamics. In the Conclusions we summarize the scenario derived from the solution…

Condensed Matter · Physics 2007-05-23 Leticia F. Cugliandolo

Kinetically constrained spin models are known to exhibit dynamical behavior mimicking that of glass forming systems. They are often understood as coarse-grained models of glass formers, in terms of some "mobility" field. The identity of…

Disordered Systems and Neural Networks · Physics 2009-11-13 Matthew T. Downton , Malcolm P. Kennett

We propose a high dimensional generalisation of the standard Klein bottle, going beyond those considered previously. We address the problem of generating continuous scalar fields (distributions) and dynamical systems (flows) on such state…

Dynamical Systems · Mathematics 2024-12-18 Peter Grindrod , Ka Man Yim

Most of the analytical studies on spin glasses are performed by using mean-field theory and renormalization group analysis. Analytical studies on finite-dimensional spin glasses are very challenging. In this short note, a possible exten-…

Disordered Systems and Neural Networks · Physics 2018-01-17 Masayuki Ohzeki , Yuta Kudo , Kazuyuki Tanaka

Facilitated or kinetically constrained spin models (KCSM) are a class of interacting particle systems reversible w.r.t. to a simple product measure. Each dynamical variable (spin) is re-sampled from its equilibrium distribution only if the…

Probability · Mathematics 2012-10-04 Nicoletta Cancrini , Fabio Martinelli , Cyril Roberto , Cristina Toninelli

Spin-glasses are universal models that can capture complex behavior of many-body systems at the interface of statistical physics and computer science including discrete optimization, inference in graphical models, and automated reasoning.…

Machine Learning · Computer Science 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

We investigate numerically the dynamics of three different spin models in the aging regime. Each of these models is meant to be representative of a distinct class of aging behavior: coarsening systems, discontinuous spin glasses, and…

Disordered Systems and Neural Networks · Physics 2009-11-10 Andrea Montanari , Federico Ricci-Tersenghi

Our understanding of supercooled liquids and glasses has lagged significantly behind that of simple liquids and crystalline solids. This is in part due to the many possibly relevant degrees of freedom that are present due to the disorder…

Machine Learning · Statistics 2018-08-01 Samuel S. Schoenholz

The physics of glasses can be studied from many viewpoints, from material scientists interested in the development of new materials to statistical physicists inventing new theoretical tools to deal with disordered systems. In these lectures…

Statistical Mechanics · Physics 2007-05-23 Ludovic Berthier

Nonequilibrium statistical mechanics exhibit a variety of complex phenomena far from equilibrium. It inherits challenges of equilibrium, including accurately describing the joint distribution of a large number of configurations, and also…

Statistical Mechanics · Physics 2024-02-08 Ying Tang , Jing Liu , Jiang Zhang , Pan Zhang

We study numerically a disordered model that interpolates among the Sherrington-Kirkpatrick mean field model and the three dimensional Edwards-Anderson spin glass. We find that averages over the disorder of powers of the overlap and of the…

Disordered Systems and Neural Networks · Physics 2009-10-31 E. Marinari

These notes cover one of the topics of the class given in the Les Houches Summer School ``Mathematical statistical physics'' in July 2005. The lectures tried to give a summary of the recent mathematical results about the long-time behaviour…

Probability · Mathematics 2007-05-23 Gerard Ben Arous , Jiri Cerny

We study thermally activated dynamics using functional renormalization within the field theory of randomly pinned elastic systems, a prototype for glasses. It appears through an essentially non-perturbative boundary layer in the running…

Disordered Systems and Neural Networks · Physics 2007-05-23 Leon Balents , Pierre Le Doussal

This paper develops a general data-driven approach to stochastic elastoplastic modelling that leverages atomistic simulation data directly rather than by fitting parameters. The approach is developed in the context of metallic glasses,…

Statistical Mechanics · Physics 2024-10-02 Bin Xu , Zhao Wu , Jiayin Lu , Michael D. Shields , Chris H. Rycroft , Franz Bamer , Michael L. Falk

Deep sequence models are receiving significant interest in current machine learning research. By representing probability distributions that are fit to data using maximum likelihood estimation, such models can model data on general…

Systems and Control · Electrical Eng. & Systems 2024-09-09 Kristian Løvland , Bjarne Grimstad , Lars Struen Imsland
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