No abstract

The mean Poincaré recurrence time as well as the Lyapunov time are measured for the Fermi–Ulam model. It is confirmed that the mean recurrence time is dependent on the size of the window chosen in the phase space where particles are allowed to return. The fractal dimension of the region is determined by the slope of the recurrence time against the size of the window and two numerical values are measured: (i) [Formula: see text] confirming normal diffusion for chaotic regions far from periodic domains and (ii) [Formula: see text] leading to anomalous diffusion measured inside islands of stability and invariant curves corresponding to regular orbits, a signature of local trapping of an ensemble of particles. The Lyapunov time is the inverse of the Lyapunov exponent. Therefore, the Lyapunov time is measured over different domains in the phase space through a direct determination of the Lyapunov exponent.

We investigate the localization of invariant spanning curves for a family of two-dimensional area-preserving mappings described by the dynamical variables [Formula: see text] and [Formula: see text] by using Slater’s criterion. The Slater theorem says there are three different return times for an irrational translation over a circle in a given interval. The returning time, which measures the number of iterations a map needs to return to a given periodic or quasi periodic region, has three responses along an invariant spanning curve. They are related to a continued fraction expansion used in the translation and obey the Fibonacci sequence. The rotation numbers for such curves are related to a noble number, leading to a devil’s staircase structure. The behavior of the rotation number as a function of invariant spanning curves located by Slater’s criterion resulted in an expression of a power law in which the absolute value of the exponent is equal to the control parameter [Formula: see text] that controls the speed of the divergence of [Formula: see text] in the limit the action [Formula: see text] is sufficiently small.