Synchronizability of chaotic logistic maps in delayed complex networks

TL;DR

This paper investigates how the distribution of delay times and network topology affect the synchronization behavior of chaotic logistic map networks, revealing conditions for steady-state and time-dependent synchronization regimes.

Contribution

It provides a detailed analysis of the impact of delay heterogeneity, network connectivity, and topology on synchronization in chaotic logistic map networks, including thresholds and feedback effects.

Findings

Heterogeneous delays lead to steady-state synchronization.

Homogeneous delays result in time-dependent (periodic or chaotic) synchronization.

A threshold connectivity level is necessary for synchronization regardless of delay distribution.

Abstract

We study a network of coupled logistic maps whose interactions occur with a certain distribution of delay times. The local dynamics is chaotic in the absence of coupling and thus the network is a paradigm of a complex system. There are two regimes of synchronization, depending on the distribution of delays: when the delays are sufficiently heterogeneous the network synchronizes on a steady-state (that is unstable for the uncoupled maps); when the delays are homogeneous, it synchronizes in a time-dependent state (that is either periodic or chaotic). Using two global indicators we quantify the synchronizability on the two regimes, focusing on the roles of the network connectivity and the topology. The connectivity is measured in terms of the average number of links per node, and we consider various topologies (scale-free, small-world, star, and nearest-neighbor with and without a central hub). With weak connectivity and weak coupling strength, the network displays an irregular oscillatory dynamics that is largely independent of the topology and of the delay distribution. With heterogeneous delays, we find a threshold connectivity level below which the network does not synchronize, regardless of the network size. This minimum average number of neighbors seems to be independent of the delay distribution. We also analyze the effect of self-feedback loops and find that they have an impact on the synchronizability of small networks with large coupling strengths. The influence of feedback, enhancing or degrading synchronization, depends on the topology and on the distribution of delays.