Converse Symmetry Breaking

Symmetry breaking--the phenomenon in which the symmetry of a system is not inherited by its stable states--underlies pattern formation, superconductivity, and numerous other effects. In this talk, I will report on the recently established possibility of converse symmetry breaking, an emergent network phenomenon in which the stable states are symmetric only when the system itself is not. In particular, I will present an experimental demonstration of this phenomenon as well as concrete applications to network optimization and control. The presentation will also discuss how converse symmetry breaking challenges the fundamental and widely held assumption that identical agents are necessarily more likely to exhibit similar behavior. I will show that it can, in fact, give rise to beneficial effects of heterogeneity in numerous complex systems in which interacting entities are required to exhibit coordinated behavior. Through this presentation, I hope to convey that our research in network science is now not only benefiting from statistical and nonlinear physics, but also fostering foundational discoveries in these areas.