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The paper deals with topical issues of modern mathematical theory of dynamical chaos and its applications. At present, it is customary to assume that dynamical chaos in finitedimensional smooth systems can exist in three different forms.…

Dynamical Systems · Mathematics 2017-12-13 S. V. Gonchenko , A. S. Gonchenko , A. O. Kazakov , A. D. Kozlov

An algorithm for detecting periodic orbits in chaotic systems [Phys. Rev. E, 60 (1999), pp.~6172--6175], which combines the set of stabilising transformations proposed by Schmelcher and Diakonos [Phys. Rev. Lett., 78 (1997), pp.~4733--4736]…

Chaotic Dynamics · Physics 2007-05-23 Jonathan J Crofts , Ruslan L Davidchack

In the framework of a recently developed theory for Hamiltonian chaos, which makes use of the formulation of Newtonian dynamics in terms of Riemannian differential geometry, we obtained analytic values of the largest Lyapunov exponent for…

Chaotic Dynamics · Physics 2007-05-23 Roberto Franzosi , Pietro Poggi , Monica Cerruti-Sola

We compare the divergence of orbits and the reversibility error for discrete time dynamical systems. These two quantities are used to explore the behavior of the global error induced by round off in the computation of orbits. The similarity…

Dynamical Systems · Mathematics 2012-11-15 Davide Faranda , Martin Federico Mestre , Giorgio Turchetti

We present a new method for locating unstable periodic points of one dimensional chaotic maps. This method is based on order statistics. The densities of various maxima of the iterates are discontinuous exactly at unstable periodic points…

chao-dyn · Physics 2009-10-31 M. C. Valsakumar , S. V. M. Satyanarayana , S. Kanmani

Spatio-temporally chaotic dynamics of transitional plane Couette flow may give rise to regular turbulent-laminar stripe patterns with a large-scale pattern wavelength and an oblique orientation relative to the laminar flow direction. A…

Fluid Dynamics · Physics 2019-12-23 Florian Reetz , Tobias M. Schneider

We present simulations of coherent structures in compressible flows near the transition to turbulence using the Dissipative Particle Dynamics (DPD) method. The structures we find are remarkably consistent with experimental observations and…

Model reduction for fluid flow simulation continues to be of great interest across a number of scientific and engineering fields. In a previous work [arXiv:2104.13962], we explored the use of Neural Ordinary Differential Equations (NODE) as…

Machine Learning · Computer Science 2021-07-07 Sourav Dutta , Peter Rivera-Casillas , Orie M. Cecil , Matthew W. Farthing , Emma Perracchione , Mario Putti

A neural network model that exhibits stochastic population bursting is studied by simulation. First return maps of inter-burst intervals exhibit recurrent unstable periodic orbit (UPO)-like trajectories similar to those found in experiments…

Disordered Systems and Neural Networks · Physics 2009-11-07 B. Biswal , C. Dasgupta

I present a data-driven predictive modeling tool that is applicable to high-dimensional chaotic systems with unstable periodic orbits. The basic idea is using deep neural networks to learn coordinate transformations between the trajectories…

Adaptation and Self-Organizing Systems · Physics 2023-12-11 Nazmi Burak Budanur

This paper reviews a line of work on decaying turbulence that began with loop equations and culminated in the Euler ensemble as a candidate statistical attractor. Most observable predictions discussed here-including the decay law, velocity…

High Energy Physics - Theory · Physics 2026-05-01 Alexander Migdal

This article presents Underdamped Particle Swarm Optimization (UEPS), a novel metaheuristic inspired by both the Particle Swarm Optimization (PSO) algorithm and the dynamic behavior of an underdamped system. The underdamped motion acts as…

Neural and Evolutionary Computing · Computer Science 2025-03-17 Matías Ezequiel Hernández Rodríguez

We investigate the convergence towards periodic orbits in discrete dynamical systems. We examine the probability that a randomly chosen point converges to a particular neighborhood of a periodic orbit in a fixed number of iterations, and we…

Dynamical Systems · Mathematics 2014-04-21 Jesús San Martín , Mason A. Porter

In the finite element analysis with fast decoupled time integration scheme for viscoelastic fluid (the Leonov model) flow, we investigate strong nonlinear behavior in 2D creeping contraction flow. The algorithm is applicable in the whole…

Fluid Dynamics · Physics 2011-11-02 Youngdon Kwon

We propose a data-driven algorithm for reconstructing the irregular, chaotic flow dynamics around two side-by-side square cylinders from sparse, time-resolved, velocity measurements in the wake. We use Proper Orthogonal Decomposition (POD)…

Fluid Dynamics · Physics 2022-09-08 Flavio Savarino , George Papadakis

Theoretical foundations of chaos have have been predominantly laid out for finite-dimensional dynamical systems, such as the three-body problem in classical mechanics and the Lorenz model in dissipative systems. In contrast, many real-world…

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

This paper deals with various routes to hyperchaos with all three positive Lyapunov exponents in a three-dimensional quadratic map. The map under consideration displays strong hyperchaoticity in the sense that in a wider range of parameter…

Chaotic Dynamics · Physics 2024-06-13 Sishu Shankar Muni

High-speed stereo PIV-measurements have been performed in a turbulent boundary layer at Re$_{\theta}$ of 9800 in order to elucidate the coherent structures. Snapshot proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD)…

Fluid Dynamics · Physics 2017-04-14 Naseem Ali , Murat Tutkun , Raúl Bayoán Cal

A data-driven algorithm is proposed that employs sparse data from velocity and/or scalar sensors to forecast the future evolution of three dimensional turbulent flows. The algorithm combines time-delayed embedding together with Koopman…

Fluid Dynamics · Physics 2026-03-04 George Papadakis , Shengqi Lu