Binary dynamics on star networks under external perturbations

TL;DR

This paper investigates binary opinion dynamics on star networks under external influences, revealing how network topology affects phase transitions and equilibrium states, with analytical insights into the role of the central node.

Contribution

It provides analytical solutions for binary dynamics on star networks, highlighting the impact of the central node and comparing results with fully connected and scale-free networks.

Findings

Disordered to ordered transition observed as external fixed nodes decrease

Equilibrium distribution splits into two peaks in star networks

Different transition behaviors between star and fully connected networks

Abstract

We study a binary dynamical process that is a representation of the voter model with opinion makers. The process models an election with two candidates but can also describe the frequencies of a biallelic gene in a population or atoms with two spin orientations in a magnetic material. The system is represented by a network whose nodes have internal states labeled 0 or 1, and nodes that are connected can influence each other. The network is perturbed by a set of external nodes whose states are fixed in 0 or 1 and that can influence all nodes of the network. The fixed nodes play the role of opinion makers in the voter model, mutation rates in population genetics or temperature in a magnetic material. The quantity of interest is the probability $\rho(m,t)$ that $m$ nodes are in state 1 at time $t$. Here we study this process on star networks and compare the results with those obtained for networks that are fully connected. In both cases a transition from disordered to ordered equilibrium states is observed as the number of external fixed nodes becomes small, but it differs significantly between the two network topologies. For fully connected networks the probability distribution becomes uniform at the critical point, which is independent of the network size. For star networks, on the other hand, the equilibrium distribution $\rho(m)$ splits in two peaks, reflecting the two possible states of the central node. We obtain approximate analytical solutions that hold near the transition and that clarify the role of the central node in the process. We show that the different character of the transition also manifest itself in the magnetization of system, obtained in the limit of large $N$. Finally, extending the analysis to two star networks we compare our results with simulations in scalefree networks, detecting the presence of hubs.