Dynamics of Boolean Networks with Scale-Free Topology

TL;DR

This paper analyzes how Boolean networks with scale-free topologies exhibit phase transitions depending on the scale-free exponent, showing that such networks are more stable and require less fine-tuning than random networks.

Contribution

It provides an analytical study of phase transitions in scale-free Boolean networks and demonstrates their increased stability compared to random topologies.

Findings

Phase transition occurs for scale-free exponent in (2,2.5).

Scale-free topology reduces the need for fine-tuning for stability.

Input and output topologies are shown to be equivalent.

Abstract

The dynamics of Boolean networks (the N-K model) with scale-free topology are studied here. The existence of a phase transition governed by the value of the scale-free exponent of the network is shown analytically by analyzing the overlap between two distinct trajectories. The phase diagram shows that the phase transition occurs for values of the scale-free exponent in the open interval (2,2.5). Since the Boolean networks under study are directed graphs, the scale-free topology of the input connections and that of the output connections are studied separately. Ultimately these two topologies are shown to be equivalent. An important result of this work is that the fine-tuning usually required to achieve stability in Boolean networks with a totally random topology is no longer necessary when the network topology is scale-free.