Grass-roots optimization of coupled oscillator networks

Despite the prevalence of biological and physical systems for which synchronization is critical, existing theory for optimizing synchrony depends on global information and does not sufficiently explore local mechanisms that enhance synchronization. Thus, there is a lack of understanding for the self-organized, collective processes that aim to optimize or repair synchronous systems, e.g., the dynamics of paracrine signaling within cardiac cells. Here we present grass-roots optimization of synchronization, which is a multiscale mechanism in which local optimizations of smaller subsystems cooperate to collectively optimize an entire system. Considering models of cardiac tissue and a power grid, we show that grass-roots-optimized systems are comparable to globally optimized systems, but they also have the added benefit of being robust to targeted attacks or subsystem islanding. Our findings motivate and support further investigation into the physics of local mechanisms that can support self-optimization for complex systems.

Automated summary

This study proposes a multiscale mechanism called grass-roots optimization of synchronization, where local optimizations of smaller subsystems cooperate to collectively optimize the entire system. The researchers found that grass-roots-optimized systems are comparable to globally optimized systems and have the additional advantage of being robust against targeted attacks or subsystem islanding. These findings motivate further investigation into the physics of local mechanisms that can support self-optimization for complex systems.