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Glassy systems reveal a wide variety of generic behaviors, which lack a unified theoretical description. Here, we study a mean-field model, recently shown to reproduce the universal non-phononic vibrational spectra of glasses, under…

Disordered Systems and Neural Networks · Physics 2025-12-19 Makoto Suda , Edan Lerner , Eran Bouchbinder

The dielectric constant of amorphous solids at low temperatures is governed by the dynamics of tunneling systems, small groups of atoms which tunnel between quasi equivalent potential minima. Recent experiments showed that at temperatures…

Disordered Systems and Neural Networks · Physics 2007-05-23 P. Nalbach

By means of microscopic simulations we show that non-instantaneous adaptation of the driving behaviour to the traffic situation together with the conventional measurement method of flow-density data can explain the observed…

Statistical Mechanics · Physics 2009-11-10 Martin Treiber , Dirk Helbing

The influence of thermal processing on the potential energy, atomic structure, and mechanical properties of metallic glasses is examined using molecular dynamics simulations. We study the three-dimensional binary mixture, which was first…

Soft Condensed Matter · Physics 2019-12-23 Nikolai V. Priezjev

Under normal operations, memristive devices undergo variability in time and space and have internal dynamics. Interplay of memory and stochastic signal processing in memristive devices makes them candidates for performing bio-inspired tasks…

Emerging Technologies · Computer Science 2024-08-01 P. F. Gora , Ewa Gudowska-Nowak

Molecular dynamics simulations are carried out to investigate mechanical properties and porous structure of binary glasses subjected to steady shear. The model vitreous systems were prepared via thermal quench at constant volume to a…

Soft Condensed Matter · Physics 2017-11-29 Nikolai V. Priezjev , Maxim A. Makeev

In this paper, we review several important features of the out-of-equilibrium dynamics of spin glasses. Starting with the simplest experiments, we discuss the scaling laws used to describe the isothermal aging observed in spin glasses after…

Disordered Systems and Neural Networks · Physics 2009-11-10 V. Dupuis , F. Bert , J. -P. Bouchaud , J. Hammann , F. Ladieu , D. Parker , E. Vincent

Using molecular dynamics simulations, we show that a simple model of a glassy material exhibits the shear localization phenomenon observed in many complex fluids. At low shear rates, the system separates into a fluidized shear-band and an…

Soft Condensed Matter · Physics 2011-11-07 F. Varnik , L. Bocquet , J. -L. Barrat , L. Berthier

Equipping agents with memory is essential for solving real-world long-horizon problems. However, most existing agent memory mechanisms rely on static and hand-crafted workflows. This limits the performance and generalization ability of…

Artificial Intelligence · Computer Science 2026-03-30 Yupeng Huo , Yaxi Lu , Zhong Zhang , Haotian Chen , Yankai Lin

We investigate the memory effects under oscillatory shear deformation of amorphous solids through computer simulations. Applications of shear deformations in all orthogonal directions show that encoded memories via this protocol are more…

Soft Condensed Matter · Physics 2023-09-20 Monoj Adhikari , Rishabh Sharma , Smarajit Karmakar

Many robotic tasks, such as human-robot interactions or the handling of fragile objects, require tight control and limitation of appearing forces and moments alongside sensible motion control to achieve safe yet high-performance operation.…

Robotics · Computer Science 2023-03-09 Janine Matschek , Johanna Bethge , Rolf Findeisen

Using numerical simulations it is shown that a random, athermal pack of soft frictional grains will store an arbitrary waveform that is applied as a small time-dependent shear while the system is slowly compressed. When the system is…

Soft Condensed Matter · Physics 2026-03-17 Eamon Dwight , D. Candela

In the traditional framework of spectral learning of stochastic time series models, model parameters are estimated based on trajectories of fully recorded observations. However, real-world time series data often contain missing values, and…

Machine Learning · Computer Science 2018-10-22 Tianlin Liu

The temperature ($T$)-shift protcol of aging in the 3 dimensional (3D) Edwards- Anderson (EA) spin-glass (SG) model is studied through the out-of-phase component of the ac susceptibility simulated by the Monte Carlo method. For processes…

Disordered Systems and Neural Networks · Physics 2009-11-07 Hajime Takayama , Koji Hukushima

The energetic optimization problem, e.g., searching for the optimal switch- ing protocol of certain system parameters to minimize the input work, has been extensively studied by stochastic thermodynamics. In current work, we study this…

Statistical Mechanics · Physics 2010-01-07 Linchen Gong , Ming Li , Zhong-can Ou-yang

Autoregressive models (ARMs) have become the workhorse for sequence generation tasks, since many problems can be modeled as next-token prediction. While there appears to be a natural ordering for text (i.e., left-to-right), for many data…

Machine Learning · Computer Science 2025-07-15 Zhe Wang , Jiaxin Shi , Nicolas Heess , Arthur Gretton , Michalis K. Titsias

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior…

Statistical Mechanics · Physics 2022-02-18 Corneel Casert , Isaac Tamblyn , Stephen Whitelam

The slow dynamics in a glassy hard-sphere system is dominated by cage breaking events, i.e., rearrangements where a particle escapes from the cage formed by its neighboring particles. We study such events for an overdamped colloidal system…

Soft Condensed Matter · Physics 2016-10-26 Matthias Kohl , Andreas Härtel , Michael Schmiedeberg

Molecular dynamics simulations provide theoretical insight into the microscopic behavior of materials in condensed phase and, as a predictive tool, enable computational design of new compounds. However, because of the large temporal and…

Chemical Physics · Physics 2020-06-18 Wujie Wang , Rafael Gómez-Bombarelli

Multiple transient memories, originally discovered in charge-density-wave conductors, are a remarkable and initially counterintuitive example of how a system can store information about its driving. In this class of memories, a system can…

Soft Condensed Matter · Physics 2013-09-27 Nathan C. Keim , Joseph D. Paulsen , Sidney R. Nagel
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