Local equilibrium in bird flocks

The correlated motion of flocks is an example of global order emerging from local interactions. An essential di erence with respect to analogous ferromagnetic systems is that flocks are active: animals move relative to each other, dynamically rearranging their interaction network. This non-equilibrium characteristic has been studied theoretically, but its impact on actual animal groups remains to be fully explored experimentally. Here, we introduce 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 use this method to infer the strength and range of alignment forces from data of starling flocks. We find 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.