Where and When Orbits of Strongly Chaotic Systems Prefer to Go

TL;DR

This paper analyzes the behavior of strongly chaotic dynamical systems, revealing three stages of phase space transport, and demonstrates that finite-time predictions about orbit locations are feasible, with implications for escape algorithms.

Contribution

It introduces a detailed analysis of the hierarchy of first passage probabilities over different time scales and proposes an algorithm to accelerate escape in strongly chaotic systems.

Findings

Finite time predictions are possible in strongly chaotic systems.

Hierarchy of first passage probabilities changes over time.

An algorithm for faster escape through phase space holes is suggested.

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) $\xi$ of the phase space of such a system. In the first short times interval there is a hierarchy with respect to the values of the first passage probabilities for the elements of $\xi$ 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 times interval, which goes to infinity, there is an opposite hierarchy of the first passage probabilities for the elements of $\xi$ and therefore again finite time predictions can be made. In the second intermediate times 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 times 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.