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We study the relationship between dynamical properties and interactionpatterns in complex oscillator networks in the presence of noise. A strikingfinding is that noise leads to a general, one-to-one correspondence between thedynamical correlation and the connections among oscillators for a variety ofnode dynamics and network structures. The universal finding enables an accurateprediction of the full network topology based solely on measuring the dynamicalcorrelation. The power of the method for network inference is demonstrated bythe high success rate in identifying links for distinct dynamics on both modeland real-life networks. The method can have potential applications in variousfields due to its generality, high accuracy and efficiency.

Noise bridges dynamical correlation and topology in coupled oscillator networks