Synchronization is critical for system function in applications ranging from cardiac pacemakers to power grids. Existing optimization techniques rely largely on global information, and while they induce certain local properties, those alone do not yield optimal systems. Therefore, while useful for designing man-made systems, existing theory provides limited insight into self-optimization of naturally-occurring systems that rely on local information and offer limited potential for decentralized optimization. Here we present a method for grass-roots optimization of synchronization, which is a multiscale mechanism involving local optimizations of smaller subsystems that are coordinated to collectively optimize an entire system, and the dynamics of such systems are particularly robust to islanding or targeted attacks. In addition to shedding light on self-optimization in natural systems, grass-roots optimization can also support the parallelizable and scalable engineering of man-made systems.
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