The connection between physics and social learning in drone swarms. Core challenges of swarm social learning (right) relate to well-developed areas of physics (left). How a discovery propagates through a drone swarm is determined in part by how information spreads in a dynamic interaction network, in which the topology changes as drones move. A drone deciding whether to trust a social signal includes problems of noise, measurement error, and uncertainty propagation: the same concepts used to analyse imperfect sensors and stochastic processes. The exploitation–exploration trade-off of an individual drone in a swarm is closely related to the interaction problem underlying coherence in many-body systems. All these challenges are further shaped by physical constraints—energy budgets, communication bandwidth, and flight kinematics—which are inherent to the system rather than externally imposed. Physics does not resolve these challenges in drone swarms, but it provides concepts and formalisms to address them precisely.