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Related papers: Large deviations and heterogeneities in a driven k…

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The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This…

Statistical Mechanics · Physics 2017-03-08 Stefano Bo , Antonio Celani

We study the appearance of large-scale dynamical heterogeneities in a simplified model of a driven, dissipative granular system. Simulations of steady-state gravity-driven flows of inelastically colliding hard disks show the formation of…

Soft Condensed Matter · Physics 2009-11-11 Allison Ferguson , Bulbul Chakraborty

Kinetically constrained models (KCM) are reversible interacting particle systems on $\mathbb Z^d$ with continuous time Markov dynamics of Glauber type, which represent a natural stochastic (and non-monotone) counterpart of the family of…

Probability · Mathematics 2018-11-14 Fabio Martinelli , Robert Morris , Cristina Toninelli

A flow model is developed for dense shear-driven granular flow. As described in the geomechanics literature, a critical state condition is reached after sufficient shearing beyond an initial static packing. During further shearing at the…

Soft Condensed Matter · Physics 2018-12-20 Matthew R. Kuhn

In this paper we consider in detail the properties of dynamical heterogeneity in lattice glass models (LGMs). LGMs are lattice models whose dynamical rules are based on thermodynamic, as opposed to purely kinetic, considerations. We devise…

Statistical Mechanics · Physics 2012-10-02 Richard K. Darst , David R. Reichman , Giulio Biroli

We use a neural network ansatz originally designed for the variational optimization of quantum systems to study dynamical large deviations in classical ones. We obtain the scaled cumulant-generating function for the dynamical activity of…

Statistical Mechanics · Physics 2021-09-22 Corneel Casert , Tom Vieijra , Stephen Whitelam , Isaac Tamblyn

High-dimensional recordings of dynamical processes are often characterized by a much smaller set of effective variables, evolving on low-dimensional manifolds. Identifying these latent dynamics requires solving two intertwined problems:…

Machine Learning · Computer Science 2026-01-21 Manuel Hinz , Maximilian Mauel , Patrick Seifner , David Berghaus , Kostadin Cvejoski , Ramses J. Sanchez

When classical systems fail to explore their entire configurational space, intriguing macroscopic phenomena like aging and glass formation may emerge. Also closed quanto-mechanical systems may stop wandering freely around the whole Hilbert…

Statistical Mechanics · Physics 2012-02-07 Giuseppe Carleo , Federico Becca , Marco Schiró , Michele Fabrizio

Consider the macroscale modelling of microscale spatiotemporal dynamics. Here we develop a new approach to ensure coarse scale discrete models preserve important self-adjoint properties of the fine scale dynamics. The first part explores…

Cellular Automata and Lattice Gases · Physics 2008-11-06 A. J. Roberts

Complex fluids exhibit structure on a wide range of length and time scales, and hierarchical approaches are necessary to investigate all facets of their often unusual properties. The study of idealized coarse-grained models at different…

Soft Condensed Matter · Physics 2008-10-23 Friederike Schmid

A continuum model for self-organized dynamics is numerically investigated. The model describes systems of particles subject to alignment interaction and short-range repulsion. It consists of a non-conservative hyperbolic system for the…

Mathematical Physics · Physics 2015-06-05 Pierre Degond , Jiale Hua

We consider kinetic vehicular traffic flow models of BGK type. Considering different spatial and temporal scales, those models allow to derive a hierarchy of traffic models including a hydrodynamic description. In this paper, the kinetic…

Numerical Analysis · Mathematics 2021-08-18 Michael Herty , Elisa Iacomini

In this work we develop a theoretical framework for the localization of flow in the steadily flowing regime of sheared disordered solids with inertial dynamics on a microscopic scale. To this aim we perform rheology studies at fixed shear…

Soft Condensed Matter · Physics 2018-12-11 Vishwas V Vasisht , Magali Le Goff , Kirsten Martens , Jean-Louis Barrat

The evolution of magnetic fields is studied using simulations of forced helical turbulence with strong imposed shear. After some initial exponential growth, the magnetic field develops a large scale travelling wave pattern. The resulting…

Astrophysics · Physics 2009-10-31 Axel Brandenburg , Alberto Bigazzi , Kandaswamy Subramanian

An overview of the related topics of anomalous coarsening and glassy dynamics is given. In anomalous coarsening, the typical domain size of an ordered phase grows more slowly with time than the power law dependence that is usually observed,…

Statistical Mechanics · Physics 2009-11-07 M. R. Evans

We perform molecular dynamics simulations to characterize the occurrence of inhomogeneous shear flows in soft jammed materials. We use rough walls to impose a simple shear flow and study the athermal motion of jammed assemblies of soft…

Soft Condensed Matter · Physics 2012-02-23 Pinaki Chaudhuri , Ludovic Berthier , Lydéric Bocquet

We report computer simulations of oscillatory athermal quasi-static shear deformation of dense amorphous samples of a three dimensional model glass former. A dynamical transition is observed as the amplitude of the deformation is varied:…

Disordered Systems and Neural Networks · Physics 2015-06-15 Davide Fiocco , Giuseppe Foffi , Srikanth Sastry

Employing large deviation theory, we explore current fluctuations of underdamped Brownian motion for the paradigmatic example of a single particle in a one dimensional periodic potential. Two different approaches to the large deviation…

Statistical Mechanics · Physics 2018-03-12 Lukas P. Fischer , Patrick Pietzonka , Udo Seifert

Self-propelled particles with hydrodynamic interactions (microswimmers) have previously been shown to produce long-range ordering phenomena. Many theoretical explanations for these collective phenomena are connected to instabilities in the…

Soft Condensed Matter · Physics 2017-05-03 Yuzhou Qian , Peter R. Kramer , Patrick T. Underhill

Recent works have explored the use of momentum in local methods to enhance distributed SGD. This is particularly appealing in Federated Learning (FL), where momentum intuitively appears as a solution to mitigate the effects of statistical…

Machine Learning · Computer Science 2025-11-26 Riccardo Zaccone , Sai Praneeth Karimireddy , Carlo Masone