Revealing Network Connectivity From Dynamics

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

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10 pages, 4 figures

Scientific paper

10.1103/PhysRevLett.98.224101

We present a method to infer network connectivity from collective dynamics in networks of synchronizing phase oscillators. We study the long-term stationary response to temporally constant driving. For a given driving condition, measuring the phase differences and the collective frequency reveals information about how the oscillators are interconnected. Sufficiently many repetitions for different driving conditions yield the entire network connectivity from measuring the dynamics only. For sparsely connected networks we obtain good predictions of the actual connectivity even for formally under-determined problems.

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