Statistical Physics of Fish Collective Motion

Abstract

We review recent theoretical and empirical advances that recast fish schooling within a statistical-physics framework, emphasizing how heterogeneous and time-dependent interactions govern collective motion. Building on extensions of Vicsek-type models to complex and weighted social networks, we show that topology and link strength qualitatively alter flocking stability and critical thresholds, with empirical weights typically reducing global alignment. High-resolution trajectory inference reveals selective, nonreciprocal responses: individuals preferentially attend to faster neighbors, producing transient, speed-induced leadership rather than fixed hierarchies. At the mesoscopic scale, schools exhibit avalanche-like turning cascades with scale-free size and duration statistics, aftershock clustering, and an Omori-type temporal decay with a short memory. Together, these findings support a unified picture in which collective order and critical-like fluctuations coexist: alignment provides stability while near-critical variability preserves responsiveness. This synthesis highlights fish schools as a tractable experimental model for how living collectives organize, transmit and process information across scales.