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It is traditionally believed that the macroscopic randomness has nothing to do with the micro-level uncertainty. Besides, the sensitive dependence on initial condition (SDIC) of Lorenz chaos has never been considered together with the…

Chaotic Dynamics · Physics 2012-01-10 S. J. Liao

Lyapunov exponents measure the average exponential growth rate of typical linear perturbations in a chaotic system, and the inverse of the largest exponent is a measure of the time horizon over which the evolution of the system can be…

Fluid Dynamics · Physics 2017-11-22 Prakash Mohan , Nicholas Fitzsimmons , Robert D. Moser

Different aspects of the predictability problem in dynamical systems are reviewed. The deep relation among Lyapunov exponents, Kolmogorov-Sinai entropy, Shannon entropy and algorithmic complexity is discussed. In particular, we emphasize…

Chaotic Dynamics · Physics 2009-11-07 G. Boffetta , M. Cencini , M. Falcioni , A. Vulpiani

Chaos and unpredictability are traditionally synonymous, yet large-scale machine learning methods recently have demonstrated a surprising ability to forecast chaotic systems well beyond typical predictability horizons. However, recent works…

Machine Learning · Computer Science 2023-11-27 William Gilpin

The Cahn-Hilliard equation with an externally-prescribed chaotic shear flow is studied in two and three dimensions. The main goal is to compare and contrast the phase separation in two and three dimensions, using high-resolution numerical…

Fluid Dynamics · Physics 2014-12-23 Lennon O'Naraigh , Selma Shun , Aurore Naso

Recent work in dynamical systems theory has shown that many properties that are associated with irreversible processes in fluids can be understood in terms of the dynamical properties of reversible, Hamiltonian systems. That is,…

chao-dyn · Physics 2015-06-24 J. R. Dorfman

To the naked eye, turbulent flows exhibit whirls of many different sizes. To each size, or scale, corresponds a fraction of the total energy resulting from a cascade in five dimensions: scale, time and three-dimensional space. Understanding…

Fluid Dynamics · Physics 2017-10-23 José I. Cardesa , Alberto Vela-Martín , Javier Jiménez

The spiraling of adjacent trajectories in chaotic dynamical systems can be characterized by distribution of local angular velocities of rotation of the displacement vector, which is governed by linearized equations of motion. This…

Chaotic Dynamics · Physics 2007-05-23 P. V. Elyutin

We study flow around a cylinder from a dynamics perspective, using drag and lift as indicators. We observe that the mean drag coefficient bifurcates from the steady case when the Karman vortex street emerges. We also find a jump in the…

Numerical Analysis · Mathematics 2023-11-15 L. Ridgway Scott , Rebecca Durst

This paper is a personal overview of the efforts over the last half century to understand fluid turbulence in terms of simpler coherent units. The consequences of chaos and the concept of coherence are first reviewed, using examples from…

Fluid Dynamics · Physics 2025-11-18 Javier Jimenez

Traffic congestion, a daily frustration for millions and a multi-billion dollar drain on economies, has long resisted deep physical understanding. While simple theoretical models of traffic flow have suggested connections to critical…

Chaotic Dynamics · Physics 2025-07-15 Garyoung Lee , Aryaman Jha , Kurt Wiesenfeld , Jorge Laval

Chaos-based potentials are defined and implemented in the one-dimensional tight-binding model as a way of simulating disorder-controlled crystalline lattices. In this setting, disorder is handled with the aid of the chaoticity parameter.…

Disordered Systems and Neural Networks · Physics 2018-01-25 Weslley Florentino de Oliveira , Giancarlo Queiroz Pellegrino

Local bifurcations of stationary points and limit cycles have successfully been characterized in terms of the critical exponents of these solutions. Lyapunov exponents and their associated covariant Lyapunov vectors have been proposed as…

Chaotic Dynamics · Physics 2018-03-14 Alexis Tantet , Valerio Lucarini , Henk A. Dijkstra

Chaos is widely understood as being a consequence of sensitive dependence upon initial conditions. This is the result of an instability in phase space, which separates trajectories exponentially. Here, we demonstrate that this criterion…

Chaotic Dynamics · Physics 2017-06-28 Marc Pradas , Alain Pumir , Greg Huber , Michael Wilkinson

We analyze probe data obtained from a toroidal magnetized plasma configuration suitable for studies of low-frequency gradient-driven instabilities. These instabilities give rise to field-aligned convection rolls analogous to Rayleigh-Benard…

Plasma Physics · Physics 2009-11-13 Tatjana Zivkovic , Kristoffer Rypdal

This article provides a self-contained comprehensive review of the phenomenon of synchronization in dynamical systems, with a particular focus on chaotic systems in both continuous-time and discrete-time contexts. Synchronization, initially…

Chaotic Dynamics · Physics 2024-12-31 Rosario D. Laureano , Diana A. Mendes , Manuel Alberto M. Ferreira

Although steady, isotropic Darcy flows are inherently laminar and non-mixing, it is well understood that transient forcing via engineered pumping schemes can induce rapid, chaotic mixing in groundwater. In this study we explore the…

Fluid Dynamics · Physics 2019-07-23 Michael Trefry , Daniel Lester , Guy Metcalfe , Junhong Wu

Two-dimensional driven dissipative flows are generally integrable via a conservation law that is singular at equilibria. Nonintegrable dynamical systems are confined to n*3 dimensions. Even driven-dissipative deterministic dynamical systems…

Statistical Mechanics · Physics 2015-06-24 J. L. McCauley

The stability of shear flows of electrically conducting fluids, with respect to finite amplitude three-dimensional localized disturbances is considered. The time evolution of the fluid impulse integral, characterizing such disturbances, for…

Fluid Dynamics · Physics 2016-09-08 V. Levinski , I. Rapoport , J. Cohen

The sensitivity of the random field Ising model to small random perturbations of the quenched disorder is studied via exact ground states obtained with a maximum-flow algorithm. In one and two space dimensions we find a mild form of chaos,…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Alava , H. Rieger