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The inertia of trapping and detrapping of nonequilibrium charge carriers affects the electrochemical and transport properties of both bulk and nanoscopic structures in a very peculiar way. An emerging memory response with a hysteresis in…

Materials Science · Physics 2023-04-10 Victor Lopez-Richard , Rafael Schio Wengenroth Silva , Ovidiu Lipan , Fabian Hartmann

Memory networks are neural networks with an explicit memory component that can be both read and written to by the network. The memory is often addressed in a soft way using a softmax function, making end-to-end training with backpropagation…

Machine Learning · Statistics 2016-05-25 Sarath Chandar , Sungjin Ahn , Hugo Larochelle , Pascal Vincent , Gerald Tesauro , Yoshua Bengio

We examine an assembly of repulsive disks interacting with a random obstacle array under a periodic drive, and find a transition from reversible to irreversible dynamics as a function of drive amplitude or disk density. At low densities and…

Soft Condensed Matter · Physics 2024-02-01 D. Minogue , M. R. Eskildsen , C. Reichhardt , C. J. O. Reichhardt

Elastic instabilities such as buckling and snapping have evolved into a powerful design principle, enabling memory, sequential shape morphing, and computing in metamaterials and devices. Modifying the post-buckling configurations or their…

Soft Condensed Matter · Physics 2025-09-10 Bernat Durà Faulí , Lennard Kwakernaak , Martin van Hecke

We investigate the universality of multi-spin systems in architectures of various symmetries of coupling type and topology. Explicit reachability sets under symmetry constraints are provided. Thus for a given (possibly symmetric)…

Quantum Physics · Physics 2009-05-17 U. Sander , T. Schulte-Herbrueggen

Road network junctions, such as merges and diverges, often act as bottlenecks that initiate and exacerbate congestion. More complex junction configurations lead to more complex driver behaviors, resulting in aggregate congestion patterns…

Computer Science and Game Theory · Computer Science 2019-04-18 Ruolin Li , Negar Mehr , Roberto Horowitz

Large language models confidently produce outdated answers, and no existing method can detect them. We show this is not an engineering failure but a structural one: temporal drift, whether a stored fact has changed since training, is…

Artificial Intelligence · Computer Science 2026-05-12 Rania Elbadry , Ahmed Heakl , Fan Zhang , Dani Bouch , Yuxia Wang , Preslav Nakov , Zhuohan Xie

Multistability is an extraordinary nonlinear property of dynamical systems and can be explored to implement memory and switches. Here we experimentally realize the tristability in a three-mode cavity magnonic system with Kerr nonlinearity.…

Applied Physics · Physics 2021-11-03 Rui-Chang Shen , Yi-Pu Wang , Jie Li , Shi-Yao Zhu , G. S. Agarwal , J. Q. You

We investigate the performance of inhomogeneously broadened spin ensembles as quantum memories under continuous dynamical decoupling. The role of the continuous driving field is two-fold: first, it decouples individual spins from magnetic…

Quantum Physics · Physics 2015-03-20 J. -M. Cai , F. Jelezko , N. Katz , A. Retzker , M. B. Plenio

The relaxation of stochastic systems after sudden perturbations is constrained by speed limits and often reveals memory effects that hinder attempts to accelerate their dynamics. Here we demonstrate Kovacs-type nonmonotonic relaxation in…

Soft Condensed Matter · Physics 2026-03-16 Miguel Ibáñez , Raúl A. Rica-Alarcón , María L. Jiménez

Strong optical drives have been shown to induce transient superconducting-like response in materials above their equilibrium $T_c$. Many of these materials already exhibit short-range superconducting correlations in equilibrium. This…

Many non-equilibrium, active processes are observed at a coarse-grained level, where different microscopic configurations are projected onto the same observable state. Such "lumped" observables display memory, and in many cases the…

Statistical Mechanics · Physics 2024-04-29 Kristian Blom , Kevin Song , Etienne Vouga , Aljaž Godec , Dmitrii E. Makarov

Intelligent agents collect and process information from their dynamically evolving neighbourhood to efficiently navigate through it. However, agent-level intelligence does not guarantee that at the level of a collective; a common example is…

Adaptation and Self-Organizing Systems · Physics 2023-09-25 Danny Raj Masila , Rupesh Mahore

Advanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics…

Optimization and Control · Mathematics 2023-12-19 Gianluca Bianchin , Fabio Pasqualetti

When an interacting many-body system, such as a magnet, is driven in time by an external perturbation, such as a magnetic field,the system cannot respond instantaneously due to relaxational delay. The response of such a system under a…

Statistical Mechanics · Physics 2009-10-31 Bikas K Chakrabarti , Muktish Acharyya

While memory effects have been reported for dense enough disordered systems such as glasses, we show here by a combination of analytical and simulation techniques that they are also intrinsic to the dynamics of dilute granular gases. By…

Statistical Mechanics · Physics 2016-11-17 A. Prados , E. Trizac

A naive model of many networked logistic maps with an excitation type coupling [Neural Networks, vol. 20, 102--108 (2007)], which is an extension of other low dimensional models, has been recently proposed to mimic the waking-sleeping…

Chaotic Dynamics · Physics 2009-06-13 Ricardo Lopez-Ruiz , Daniele Fournier-Prunaret

Systems of globally coupled logistic maps (GCLM) can display complex collective behaviour characterized by the formation of synchronous clusters. In the dynamical clustering regime, such systems possess a large number of coexisting…

Disordered Systems and Neural Networks · Physics 2009-11-07 Susanna C. Manrubia , Ugo Bastolla , Alexander S. Mikhailov

Crystalline materials exhibit an hysteresis behaviour when deformed cyclically. The origins of this tension-compression asymmetry have been fully understood only recently as being caused by an asymmetry in the junction strength and a…

Materials Science · Physics 2023-01-03 Sylvain Queyreau

Despite advances in deep learning, neural networks can only learn multiple tasks when trained on them jointly. When tasks arrive sequentially, they lose performance on previously learnt tasks. This phenomenon called catastrophic forgetting…

Machine Learning · Computer Science 2018-05-29 Nitin Kamra , Umang Gupta , Yan Liu
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