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In this paper we review a recent proposal to understand the long time limit of glassy dynamics in terms of an appropriate Markov Chain. [1]. The advantages of the resulting construction are many. The first one is that it gives a quasi…

Disordered Systems and Neural Networks · Physics 2016-04-19 Silvio Franz , Giorgio Parisi , Federico Ricci-Tersenghi , Pierfrancesco Urbani

Kinetically-constrained models are lattice-gas models that are used for describing glassy systems. By construction, their equilibrium state is trivial and there are no equal-time correlations between the occupancy of different sites. We…

Statistical Mechanics · Physics 2017-03-01 Eial Teomy , Yair Shokef

Efficient skill acquisition, representation, and on-line adaptation to different scenarios has become of fundamental importance for assistive robotic applications. In the past decade, dynamical systems (DS) have arisen as a flexible and…

Robotics · Computer Science 2020-03-27 Matteo Saveriano , Dongheui Lee

The growth of correlation lengths in equilibrium glass-forming liquids near the glass transition is considered a critical finding in the quest to understand the physics of glass formation. These understandings helped us understand various…

Soft Condensed Matter · Physics 2023-08-16 Anoop Mutneja , Smarajit Karmakar

We introduce a family of glassy models having a parameter, playing the role of an interaction range, that may be varied continuously to go from a system of particles in d dimensions to a mean-field version of it. The mean-field limit is…

Statistical Mechanics · Physics 2015-05-27 Romain Mari , Jorge Kurchan

The demand of probabilistic time series forecasting has been recently raised in various dynamic system scenarios, for example, system identification and prognostic and health management of machines. To this end, we combine the advances in…

Machine Learning · Computer Science 2022-05-25 Haitao Liu , Changjun Liu , Xiaomo Jiang , Xudong Chen , Shuhua Yang , Xiaofang Wang

We investigate a number of simple toy models to explore interesting relationships between dynamics and typicality. We start with an infinite model that has been proposed as an illustration of how non-ergodic dynamics can produce interesting…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-12 Aaron Hernley , Andreas Albrecht , Tevian Dray

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

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

We study the off equilibrium dynamics of a mean field disordered systems which can be interpreted both as a long range interaction spin glass and as a particle in a random potential. The statics of this problem is well known and exhibits a…

Condensed Matter · Physics 2009-10-22 S. Franz , M. Mézard

Glasses are traditionally characterized by their rugged landscape of disordered low-energy states and their slow relaxation towards thermodynamic equilibrium. Far from equilibrium, dynamical forms of glassy behavior with anomalous algebraic…

Disordered Systems and Neural Networks · Physics 2026-04-17 Zachary G. Nicolaou , Hangjun Cho , Yuanzhao Zhang , J. Nathan Kutz , Steven L. Brunton

The rapid advancement of generative models, such as Stable Diffusion, raises a key question: how can synthetic data from these models enhance predictive modeling? While they can generate vast amounts of datasets, only a subset meaningfully…

Machine Learning · Statistics 2025-05-09 Jialong Jiang , Wenkang Hu , Jian Huang , Yuling Jiao , Xu Liu

Dynamical systems theory has long provided a foundation for understanding evolving phenomena across scientific domains. Yet, the application of this theory to complex real-world systems remains challenging due to issues in mathematical…

Machine Learning · Computer Science 2024-11-05 Samuel A. Moore , Brian P. Mann , Boyuan Chen

We present results of numerical simulations on a one-dimensional Ising spin glass with long-range interactions. Parameters of the model are chosen such that it is a proxy for a short-range spin glass above the upper critical dimension (i.e.…

Disordered Systems and Neural Networks · Physics 2016-02-17 Matthew Wittmann , A. P. Young

We introduce a new disordered system, the Super-Potts model, which is a more frustrated version of the Potts glass. Its elementary degrees of freedom are variables that can take M values and are coupled via pair-wise interactions. Its exact…

Disordered Systems and Neural Networks · Physics 2015-01-15 Maria Chiara Angelini , Giulio Biroli

Some invariances under perturbations of the spin glass phase are introduced, their proofs outlined and their consequences illustrated as factorisation rules for the overlap distribution. A comparison between the state of the art for mean…

Mathematical Physics · Physics 2012-12-04 Pierluigi Contucci

Many consequential real-world systems, like wind fields and ocean currents, are dynamic and hard to model. Learning their governing dynamics remains a central challenge in scientific machine learning. Dynamic Mode Decomposition (DMD)…

Machine Learning · Computer Science 2025-11-26 Yujin Kim , Sarah Dean

A disordered spin glass model where both static and dynamical properties depend on macroscopic magnetizations is presented. These magnetizations interact via random couplings and, therefore, the typical quenched realization of the system…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Pasquini , M. Serva

Our model of shaken sand, presented in earlier work, has been extended to include a more realistic `glassy' state, i.e., when the sandbox is shaken at very low intensities of vibration. We revisit some of our earlier results, and compare…

Disordered Systems and Neural Networks · Physics 2016-11-23 Peter F. Stadler , Anita Mehta , J. M. Luck

The nature of glassy states in realistic finite dimensions is still under fierce debate. Lattice models can offer valuable insights and facilitate deeper theoretical understanding. Recently, a disordered-interacting lattice model with…

Soft Condensed Matter · Physics 2024-02-01 Bo Li , Chun-Shing Lee , Xin-Yuan Gao , Hai-Yao Deng , Chi-Hang Lam
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