Where and when orbits of chaotic systems prefer to go. (12th April 2019)

• Record Type: Journal Article
• Authors: Bolding, M; Bunimovich, L A
• Is Part Of: Nonlinearity. Volume 32:Number 5(2019:May)
• Page Start: 1731
• Page End: 1771
• Publication Date: 2019-04-12
• Subjects: dynamical systems -- chaos -- stochastic systems; Primary: 37A50 -- Secondary: 37A60; Nonlinear theories -- Periodicals; Mathematical analysis -- Periodicals; Mathematical analysis; Nonlinear theories; Periodicals; 515
• DOI: 10.1088/1361-6544/ab0c34
• Languages: English
• ISSNs: 0951-7715

Abstract

Abstract: We prove that transport in the phase space of the 'most strongly chaotic' dynamical systems has three different stages. Consider a finite Markov partition (coarse graining) of the phase space of such a system. In the first short time interval there is a hierarchy with respect to the values of the first hitting probabilities for the elements of and therefore finite time predictions can be made about which element of the Markov partition trajectories will be most likely to hit first at a given moment. In the third long time interval, which goes to infinity, there is an opposite hierarchy of the first hitting probabilities for the elements of and therefore again finite time predictions can be made. In the second intermediate time interval there is no hierarchy in the set of all elements of the Markov partition. We also obtain estimates on the length of the short time interval and show that its length is growing with refinement of the Markov partition which shows that practically only this interval should be taken into account in many cases. These results demonstrate that finite time predictions for the evolution of strongly chaotic dynamical systems are possible. In particular, one can predict that an orbit is more likely to first enter one subset of phase space than another at a given moment in time. Moreover, these results suggest an algorithm which accelerates the process of escape through 'holes' in the phase space of dynamical systems with strongly chaotic behavior.