CHIRP: Recovering Network Topology from Coupling-Response Profiles

Synchronized trajectories can arise from a direct link, an indirect path, or a shared source. Oscillator experiments often sweep coupling strength only to describe the approach to synchronization. We instead write each phase-difference coefficient as a dose-independent term plus a term that changes with the known dose, and rank candidate edges by the second term. A single dose leaves the two terms collinear; varying the dose separates them. We bound the coefficient error and the condition for recovering the edge set. Choices were fixed on five physical networks and applied once to fifteen held-out graphs of 28 chaotic electronic oscillators. The locked estimator ranks edges above each declared baseline. Cutting the raw traces to a 3 s budget before filtering still gives higher average precision than a single-dose model under that same raw-time budget. Otsu's rule selects a graph from the ranking without using the known number of edges. In synthetic trials, average precision falls in a confounded scenario that adds a constant-amplitude common drive together with other disturbances, and falls again when the dose response is nonlinear. These results suggest that a calibrated intervention can make topology easier to identify than an observational fit when the intervention is structurally relevant and approximately affine over the fitted range.