  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.

Disordered Systems and Neural Networks;Neurons and Cognition