Self-organization is frequently observed in active collectives, from ant rafts to molecular motor assemblies. General principles describing self-organization away from equilibrium have been challenging to identify. We offer a unifying framework that models the behavior of complex systems as largely random, while capturing their driven response properties. Such a “low-rattling principle” enables prediction and control of fine-tuned emergent properties in disordered mechanical networks, random spin glasses, and robot swarms.
Jeremy England is a Principal Research Scientist in the Department of Physics at the Georgia Institute of Technology. He serves as a Senior Director in Artificial Intelligence and Machine Learning at GlaxoSmithKline. From 2011 to 2019, he was Assistant and then Associate Professor in the Department of Physics at MIT, where he led a research group in studying the nonequilibrium statistical mechanics of life-like self-organization.