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In this paper we apply the method of Lagrangian descriptors as an indicator to study the chaotic and regular behavior of trajectories in the phase space of the classical double pendulum system. In order to successfully quantify the degree…

Dynamical Systems · Mathematics 2024-03-13 Javier Jiménez López , V. J. García-Garrido

We predict theoretically and verify experimentally the suppression of chaos in the Lorenz system driven by a high-frequency periodic or stochastic parametric force. We derive the theoretical criteria for chaos suppression and verify that…

Chaotic Dynamics · Physics 2009-11-10 Chol-Ung Choe , Hartmut Benner , Yuri S. Kivshar

Lagrangian descriptors (LDs) based on the arc length of orbits previously demonstrated their utility in delineating structures governing the dynamics. Recently, a chaos indicator based on the second derivatives of the LDs, referred to as…

Chaotic Dynamics · Physics 2025-02-05 Alexandru Căliman , Jérôme Daquin , Anne-Sophie Libert

Instabilities in 1D spatially extended systems are studied with the aid of both temporal and spatial Lyapunov exponents. A suitable representation of the spectra allows a compact description of all the possible disturbances in tangent…

chao-dyn · Physics 2009-10-28 Stefano Lepri , Antonio Politi , Alessandro Torcini

Adaptive controllers are designed to synchronize two different chaotic systems with uncertainties, including unknown parameters, internal and external perturbations. Lyapunov stability theory is applied to prove that under some conditions…

Chaotic Dynamics · Physics 2009-09-30 Jianping Cai , Zhengzhong Yuan

Chaos, or exponential sensitivity to small perturbations, appears everywhere in nature. Moreover, chaos is predicted to play diverse functional roles in living systems. A method for detecting chaos from empirical measurements should…

Quantitative Methods · Quantitative Biology 2020-01-13 Daniel Toker , Friedrich T. Sommer , Mark D'Esposito

We prove the existence of multiple noise-induced transitions in the Lasota-Mackey map, which is a class of one dimensional random dynamical system with additive noise. The result is achieved by the help of rigorous computer assisted…

Chaotic Dynamics · Physics 2022-01-26 Takumi Chihara , Yuzuru Sato , Isaia Nisoli , Stefano Galatolo

This paper addresses the challenge of a particular class of noisy state observations in Markov Decision Processes (MDPs), a common issue in various real-world applications. We focus on modeling this uncertainty through a confusion matrix…

Machine Learning · Computer Science 2023-12-15 Amirhossein Afsharrad , Sanjay Lall

We study how spatiotemporal chaos in dynamical systems can be controlled by stochastically returning them to their initial conditions. Focusing on discrete nonlinear maps, we analyze how key measures of chaos -- the Lyapunov exponent and…

Statistical Mechanics · Physics 2026-02-25 Camille Aron , Manas Kulkarni

We present a systematic study of moment evolution in multidimensional stochastic difference systems, focusing on characterizing systems whose low-order moments diverge in the neighborhood of a stable fixed point. We consider systems with a…

Mathematical Physics · Physics 2009-11-10 Dennis M. Wilkinson

The tangent dynamics of the Lyapunov modes and their dynamics as generated numerically - {\it the numerical dynamics} - is considered. We present a new phenomenological description of the numerical dynamical structure that accurately…

Chaotic Dynamics · Physics 2009-11-13 D. J. Robinson , G. P. Morriss

While the notion of chaos is well established for dynamical systems on manifolds, it is not so for dynamical systems over discrete spaces with $ N $ variables, as binary neural networks and cellular automata. The main difficulty is the…

Chaotic Dynamics · Physics 2009-11-11 F. Benatti , A. Verjovski , F. Zertuche

This paper introduces a new global dynamics and chaos indicator based on the method of Lagrangian Descriptor apt for discriminating ordered and deterministic chaotic motions in multidimensional systems. The selected implementation of this…

We demonstrate that Lagrangian flow for the 2D Boussinesq equations under degenerate noise exhibit chaotic behavior characterized by the strict positivity of the top Lyapunov exponent, where the degenerate noise acts only on a few Fourier…

Dynamical Systems · Mathematics 2026-03-31 Dengdi Chen , Yan Zheng

Recently, a general data driven numerical framework has been developed for learning and modeling of unknown dynamical systems using fully- or partially-observed data. The method utilizes deep neural networks (DNNs) to construct a model for…

Machine Learning · Computer Science 2022-05-18 Victor Churchill , Dongbin Xiu

This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty. A key challenge in designing controllers with stability guarantees for…

Systems and Control · Electrical Eng. & Systems 2024-08-06 Kehan Long , Jorge Cortes , Nikolay Atanasov

We present a survey of the theory of the Lyapunov Characteristic Exponents (LCEs) for dynamical systems, as well as of the numerical techniques developed for the computation of the maximal, of few and of all of them. After some historical…

Chaotic Dynamics · Physics 2010-03-24 Charalampos Skokos

The efficient detection of chaotic behavior in orbits of a complex dynamical system is an active domain of research. Several indicators have been proposed in the past, and new ones have recently been developed in view of improving the…

Dynamical Systems · Mathematics 2023-07-05 A. Bazzani , M. Giovannozzi , C. E. Montanari , G. Turchetti

The agenda of Dissipative Quantum Chaos is to create a toolbox which would allow us to categorize open quantum systems into "chaotic" and "regular" ones. Two approaches to this categorization have been proposed recently. One of them is…

Quantum Physics · Physics 2022-04-20 Igor Yusipov , Mikhail Ivanchenko

Deterministic chaos permits a precise notion of a "perfect measurement" as one that, when obtained repeatedly, captures all of the information created by the system's evolution with minimal redundancy. Finding an optimal measurement is…

Machine Learning · Computer Science 2024-03-21 Kieran A. Murphy , Dani S. Bassett