We have introduced a novel dynamical inference technique, based on the principle of maximum entropy, which accommodates network rearrangements and overcomes the problem of slow experimental sampling rates. We have used this method to infer the strength and range of alignment forces from data of starling flocks. We have found that local bird alignment occurs on a much faster timescale than neighbour rearrangement. Accordingly, equilibrium inference, which assumes a fixed interaction network, gives results consistent with dynamical inference. We conclude that bird orientations are in a state of local quasi–equilibrium over the interaction length scale, providing firm ground for the applicability of statistical physics in certain active systems.
Contact person: Massimiliano Viale, ISC–CNR Univ. Roma La Sapienza