Noise bridges dynamical correlation and topology in coupled oscillator networks

TL;DR

This paper demonstrates that noise induces a universal correlation-topology relationship in coupled oscillator networks, enabling accurate network inference from dynamical data across various systems.

Contribution

It reveals a universal, noise-induced correlation-topology correspondence that allows precise network reconstruction from dynamical correlations in diverse oscillator networks.

Findings

High success rate in network link identification

Universal correlation-topology relationship established

Effective in both model and real-world networks

Abstract

We study the relationship between dynamical properties and interaction patterns in complex oscillator networks in the presence of noise. A striking finding is that noise leads to a general, one-to-one correspondence between the dynamical correlation and the connections among oscillators for a variety of node dynamics and network structures. The universal finding enables an accurate prediction of the full network topology based solely on measuring the dynamical correlation. The power of the method for network inference is demonstrated by the high success rate in identifying links for distinct dynamics on both model and real-life networks. The method can have potential applications in various fields due to its generality, high accuracy and efficiency.