Greedy optimization for growing spatially embedded oscillatory networks
arXiv:2109.08759 · doi:10.1103/PhysRevE.106.034304
Abstract
The coupling of some types of oscillators requires the mediation of a physical link between them, rendering the distance between oscillators a critical factor to achieve synchronization. In this paper we propose and explore a greedy algorithm to grow spatially embedded oscillator networks. The algorithm is constructed in such a way that nodes are sequentially added seeking to minimize the cost of the added links' length and optimize the linear stability of the growing network. We show that, for appropriate parameters, the stability of the resulting network, measured in terms of the dynamics of small perturbations and the correlation length of the disturbances, can be significantly improved with a minimal added length cost. In addition, we analyze numerically the topological properties of the resulting networks and find that, while being more stable, their degree distribution is approximately exponential and independent of the algorithm parameters. Moreover, we find that other topological parameters related with network resilience and efficiency are also affected by the proposed algorithm. Finally, we extend our findings to more general classes of networks with different sources of heterogeneity. Our results are a first step in the development of algorithms for the directed growth of oscillatory networks with desirable stability, dynamical and topological properties.
arXiv comment13 pages, 9 figures
References in corpus (15)
- Structural Vulnerability of the North American Power Grid
- Synchronization in Complex Oscillator Networks and Smart Grids
- Analysis of a power grid using the Kuramoto-like model
- Robustness of the European power grids under intentional attack
- Optimal synchronization of complex networks
- Hysteretic transitions in the Kuramoto model with inertia
- A Random Growth Model for Power Grids and Other Spatially Embedded Infrastructure Networks
- Control of coupled oscillator networks with application to microgrid technologies
- Robustness of Synchrony in Complex Networks and Generalized Kirchhoff Indices
- Exotic Multifractal Conductance Fluctuations in Graphene
- Optimizing Synchronization Stability of the Kuramoto Model in Complex Networks and Power Grids
- Optimal synchronization of directed complex networks
- Stable chaos in fluctuation driven neural circuits
- Decreased resilience in power grids under dynamically induced vulnerabilities
- Chaos stabilizes synchronization in systems of coupled inner-ear hair cells