Clustering of exponentially separating trajectories

Abstract

It might be expected that trajectories for a dynamical system which has no negative Lyapunov exponent (implying exponential growth of small separations will not cluster together. However, clustering can occur such that the density $\rho (\Delta x)$ of trajectories within distance $\Delta x$ of a reference trajectory has a power-law divergence, so that $\rho (\Delta x)\sim \Delta x^{-\beta }$ when $\Delta x$ is sufficiently small, for some $0<\beta <1$. We demonstrate this effect using a random map in one dimension. We find no evidence for this effect in the chaotic logistic map, and argue that the effect is harder to observe in deterministic maps.

4 pages, 2 figures