Stickiness in generic low-dimensional Hamiltonian systems: A recurrence-time statistics approach

TL;DR

This paper investigates the structure and effects of stickiness in chaotic regions of Hamiltonian systems using recurrence-time statistics, revealing how stickiness causes correlations and deviations from random diffusion models.

Contribution

It introduces a recurrence-time based method to identify sticky regions and quantifies stickiness using the variable S across different Hamiltonian systems.

Findings

Stickiness causes correlations in cell visits in chaotic regions.

Recurrence time distributions in sticky areas are mixtures of exponentials.

The variable S effectively measures the degree of stickiness.

Abstract

We analyze the structure and stickiness in the chaotic components of generic Hamiltonian systems with divided phase space. Following the method proposed recently in Lozej and Robnik [Phys. Rev. E 98, 022220 (2018)], the sticky regions are identified using the statistics of recurrence times of a single chaotic orbit into cells dividing the phase space into a grid. We perform extensive numerical studies of three example systems: the Chirikov standard map, the family of Robnik billiards, and the family of lemon billiards. The filling of the cells is compared to the random model of chaotic diffusion, introduced in Robnik et al. [J. Phys. A: Math. Gen. 30, L803 (1997)] for the description of transport in the phase spaces of ergodic systems. The model is based on the assumption of completely uncorrelated cell visits because of the strongly chaotic dynamics of the orbit and the distribution of recurrence times is exponential. In generic systems the stickiness induces correlations in the cell visits. The distribution of recurrence times exhibits a separation of timescales because of the dynamical trapping. We model the recurrence time distributions to cells inside sticky areas as a mixture of exponential distributions with different decay times. We introduce the variable S, which is the ratio between the standard deviation and the mean of the recurrence times as a measure of stickiness. We use S to globally assess the distributions of recurrence times. We find that in the bulk of the chaotic sea S=1, while S>1 in areas of stickiness. We present the results in the form of animated grayscale plots of the variable S in the largest chaotic component for the three example systems, included as supplemental material to this paper.