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Accurate prediction of Lagrangian trajectories in turbulent flow remains challenging due to limited temporal information in transport functions. This paper shows that surrounding coherent motions sharing the same dynamics carry enough…

Fluid Dynamics · Physics 2026-05-07 Ali R Khojasteh , Dominique Heitz

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

Maximization of the path information entropy is a clear prescription for constructing models in non-equilibrium statistical mechanics. Here it is shown that, following this prescription under the assumption of arbitrary instantaneous…

Data Analysis, Statistics and Probability · Physics 2016-08-01 Sergio Davis , Diego González

We show that the probability distribution function that best fits the distribution of return times between two consecutive visits of a chaotic trajectory to finite size regions in phase space deviates from the exponential statistics by a…

Chaotic Dynamics · Physics 2015-05-13 Murilo S. Baptista , Dariel M. Maranhao , Jose C. Sartorelli

A deterministic multi-scale dynamical system is introduced and discussed as prototype model for relative dispersion in stationary, homogeneous and isotropic turbulence. Unlike stochastic diffusion models, here trajectory transport and…

Fluid Dynamics · Physics 2017-04-19 Guglielmo Lacorata , Angelo Vulpiani

We propose Lagrangian Descriptors (LDs) as a diagnostic framework for evaluating neural network models of Hamiltonian systems beyond conventional trajectory-based metrics. Standard error measures quantify short-term predictive accuracy but…

Machine Learning · Computer Science 2026-04-02 Abrari Noor Hasmi , Haralampos Hatzikirou , Hadi Susanto

We construct Arnol'd cat map lattice field theories in phase space and configuration space. In phase space we impose that the evolution operator of the linearly coupled maps be an element of the symplectic group, in direct generalization of…

High Energy Physics - Theory · Physics 2023-06-12 Minos Axenides , Emmanuel Floratos , Stam Nicolis

Using large-scale parallel numerical simulations we explore spatiotemporal chaos in Rayleigh-B\'enard convection in a cylindrical domain with experimentally relevant boundary conditions. We use the variation of the spectrum of Lyapunov…

Chaotic Dynamics · Physics 2015-06-03 Alireza Karimi , Mark R. Paul

The asymptotic distance between trajectories $d_{\infty}$, is studied in detail to characterize the occurrence of chaos. We show that this quantity is quite distinct and complementary to the Lyapunov exponents, and it allows for a…

chao-dyn · Physics 2007-05-23 Virgil Baran , Aldo Bonasera

The transport properties of a random velocity field with Kolmogorov spectrum and time correlations defined along Lagrangian trajectories are analyzed. The analysis is carried on in the limit of short correlation times, as a perturbation…

Chaotic Dynamics · Physics 2009-11-07 Piero Olla

Lagrangian coherent structures are effective barriers, sticky regions, that separate phase space regions of different dynamical behavior. The usual way to detect such structures is via finite-time Lyapunov exponents. We show that similar…

Chaotic Dynamics · Physics 2011-02-11 J. D. Szezech , A. B. Schelin , I. L. Caldas , S. R. Lopes , P. J. Morrison , R. L. Viana

Dynamical systems in nature such as fluid flows, heart beat patterns, rainfall variability, stock market price fluctuations, etc. exhibit selfsimilar fractal fluctuations on all scales in space and time. Power spectral analyses of fractal…

General Physics · Physics 2007-05-23 A. M. Selvam

In this work we revisit the geometric approach to chaos in Hamiltonian dynamics, by means of the Jacobi-Levi-Civita equation (JLCE). We inspect numerically two low-dimensional dynamical systems; show that, along chaotic orbits, the…

Chaotic Dynamics · Physics 2026-03-19 L. Salasnich , F. Sattin

We formulate Lagrangian descriptors (LDs) in the path integral framework. Averaging the classical LD over fluctuations about extremal trajectories defines a quantum LD that incorporates quantum effects. Invariant manifolds, which sharply…

Dynamical Systems · Mathematics 2026-04-07 Javier Jiménez-López , V. J. García-Garrido

The classical Birkhoff ergodic theorem in its most popular version says that the time average along a single typical trajectory of a dynamical system is equal to the space average with respect to the ergodic invariant distribution. This…

Dynamical Systems · Mathematics 2017-12-06 Michael Blank

The decay of the overlap between a wave packet evolved with a Hamiltonian H and the same state evolved with H}+$\Sigma $ serves as a measure of the decoherence time $\tau_{\phi}$. Recent experimental and analytical evidence on classically…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 F. M. Cucchietti , H. M. Pastawski , R. Jalabert

We study the Lagrangian flow associated to velocity fields arising from various models of fluid mechanics subject to white-in-time, $H^s$-in-space stochastic forcing in a periodic box. We prove that in many circumstances, these flows are…

Analysis of PDEs · Mathematics 2018-09-19 Jacob Bedrossian , Alex Blumenthal , Samuel Punshon-Smith

Gyrokinetic theory is based on an asymptotic expansion in the small parameter $\epsilon$, defined as the ratio of the gyroradius and the characteristic length of variation of the magnetic field. In this article, this ordering is strictly…

Plasma Physics · Physics 2015-05-19 Felix I. Parra , Ivan Calvo

It is shown that appearance of inertial range of scales, adjacent to distributed chaos range, results in adiabatic invariance of an energy correlation integral for isotropic homogeneous turbulence and for buoyancy driven turbulence (with…

Fluid Dynamics · Physics 2016-11-29 A. Bershadskii

Many complex phenomena, from weather systems to heartbeat rhythm patterns, are effectively modeled as low-dimensional dynamical systems. Such systems may behave chaotically under certain conditions, and so the ability to detect chaos based…

Machine Learning · Computer Science 2021-06-17 Hagai Rappeport , Irit Levin Reisman , Naftali Tishby , Nathalie Q. Balaban
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