Optimal dynamical stabilization

Abstract: Stability is a fundamental concept that refers to a system's ability to return close to its original state after disturbances. The minimal conditions for stability when system parameters vary in time, though common in physics, have been largely overlooked. Here, we study the minimal amount of periodic stiffness a linear mass-spring system requires to remain stable and apply our findings to optimally trap the upside-down state of a compass in a time-varying magnetic field. We show that the ability to return close to its original state only needs to be ensured over small but precisely defined durations within each period for the system to achieve dynamic stability. These precise durations form a discrete set, remarkably predicted by rules analogous to those of quantum mechanics. This unexpected connection opens new avenues for controlling dynamical systems.