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We decompose the anomalous diffusive behavior found in a model of aging into its fundamental constitutive causes. The model process is a sum of increments that are iterates of a chaotic dynamical system, the Pomeau-Manneville map. The…

Statistical Mechanics · Physics 2018-11-08 Philipp G. Meyer , Vidushi Adlakha , Holger Kantz , Kevin E. Bassler

We extend the standard droplet scaling theory for isothermal aging in spin glasses assuming that the effective stiffness constant of droplets as large as extended defects is vanishingly small. A novel dynamical order parameter and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Hajime Yoshino , Koji Hukushima , Hajime Takayama

The Pitman-Yor process is a random discrete measure. The random weights or masses follow the two-parameter Poisson-Dirichlet distribution with parameters $0<\alpha<1, \theta>-\alpha$. The parameters $\alpha$ and $\theta$ correspond to the…

Probability · Mathematics 2016-02-29 Shui Feng , Fuqing Gao , Youzhou Zhou

Learning dynamics from dissipative chaotic systems is notoriously difficult due to their inherent instability, as formalized by their positive Lyapunov exponents, which exponentially amplify errors in the learned dynamics. However, many of…

Machine Learning · Computer Science 2024-06-07 Yair Schiff , Zhong Yi Wan , Jeffrey B. Parker , Stephan Hoyer , Volodymyr Kuleshov , Fei Sha , Leonardo Zepeda-Núñez

We consider the dynamics of an arbitrary quantum system coupled to a large arbitrary and fully quantum mechanical environment through a random interaction. We establish analytically and check numerically the typicality of this dynamics, in…

Quantum Physics · Physics 2017-07-26 Grégoire Ithier , Florent Benaych-Georges

We study the intermittent dynamics and the fluctuations of the dynamic correlation function of a simple aging system. Given its size $L$ and its coherence length $\xi$, the system can be divided into $N$ independent subsystems, where…

Disordered Systems and Neural Networks · Physics 2016-08-31 Estelle Pitard

Consider a chaotic dynamical system generating Brownian motion-like diffusion. Consider a second, non-chaotic system in which all particles localize. Let a particle experience a random combination of both systems by sampling between them in…

Chaotic Dynamics · Physics 2019-05-01 Y. Sato , R. Klages

Continuous-time random walks are generalisations of random walks frequently used to account for the consistent observations that many molecules in living cells undergo anomalous diffusion, i.e. subdiffusion. Here, we describe the…

Analysis of PDEs · Mathematics 2015-03-31 Hugues Berry , Thomas Lepoutre , Álvaro Mateos González

Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors. Quantifying the data freshness through age of information (AoI), in this paper, we jointly design sampling…

Information Theory · Computer Science 2023-12-19 Yali Cao , Yinglei Teng , Mei Song , Nan Wang

A network of $N$ elements is studied in terms of a deterministic globally coupled map which can be chaotic. There exists a range of values for the parameters of the map where the number of different macroscopic configurations is very large,…

Condensed Matter · Physics 2009-10-28 A. Crisanti , M. Falcioni , A. Vulpiani

We study two classes of dynamical systems with holes: expanding maps of the interval and Collet-Eckmann maps with singularities. In both cases, we prove that there is a natural absolutely continuous conditionally invariant measure $\mu$…

Dynamical Systems · Mathematics 2014-12-09 Henk Bruin , Mark Demers , Ian Melbourne

In Willems' behavioral systems theory, a dynamical system is identified with the set of all trajectories compatible with its laws of motion. In the linear time-invariant setting this trajectory set is a linear subspace, and its algebraic…

Optimization and Control · Mathematics 2026-05-08 Victor M. Preciado

We propose the existence of a new universality in classical chaotic systems when the number of degrees of freedom is large: the statistical property of the Lyapunov spectrum is described by Random Matrix Theory. We demonstrate it by…

High Energy Physics - Theory · Physics 2018-03-13 Masanori Hanada , Hidehiko Shimada , Masaki Tezuka

The record age tau_k, defined as the time between the k-th and k+1-st record-breaking events, is a central observable of extreme-value statistics. In Markovian processes, the absence of memory makes tau_k independent of k. How memory breaks…

Statistical Mechanics · Physics 2026-05-06 J. Brémont , R. Voituriez , O. Bénichou

In this paper we develop the theory of discrete averaging designed to study discrete time dynamical systems defined by iterates of a map. The discrete averaging uses weighted averages over a segment of trajectory to find an autonomous…

Dynamical Systems · Mathematics 2026-03-12 Vassili Gelfreich , Arturo Vieiro

This paper summarises a numerical investigation of phase mixing in time-independent Hamiltonian systems that admit a coexistence of regular and chaotic phase space regions, allowing also for low amplitude perturbations idealised as periodic…

Astrophysics · Physics 2007-05-23 Henry E. Kandrup , Steven J. Novotny

Nonequilibrium surface autocorrelation and autoresponse functions are studied numerically in semi-infinite critical systems in the dynamical scaling regime. Dynamical critical behaviour is examined for a nonconserved order parameter in…

Statistical Mechanics · Physics 2009-11-10 Michel Pleimling

We consider a class of Crump-Mode-Jagers processes with interaction, constructed by removing a newly born offspring with a probability that depends on the age structure of the population at its birth time. We prove a law of large numbers…

Probability · Mathematics 2025-11-14 Félix Foutel-Rodier , Emmanuel Schertzer

We explore the aging transition in a network of globally coupled Stuart-Landau oscillators under a discrete time-dependent coupling. In this coupling, the connections among the oscillators are turned ON and OFF in a systematic manner,…

Adaptation and Self-Organizing Systems · Physics 2022-04-06 K. Sathiyadevi , D. Premraj , Tanmoy Banerjee , Zhigang Zheng , M. Lakshmanan

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl
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