Grass-roots optimization of coupled oscillator networks
Abstract
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/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.
Cite
@article{arxiv.2109.07426,
title = {Grass-roots optimization of coupled oscillator networks},
author = {Pranick R. Chamlagai and Dane Taylor and Per Sebastian Skardal},
journal= {arXiv preprint arXiv:2109.07426},
year = {2022}
}