Physics Department, Williams College, 33 Lab Campus Drive, Williamstown, Massachusetts 01267, USA.
Phys Rev Lett. 2022 Mar 4;128(9):098301. doi: 10.1103/PhysRevLett.128.098301.
From the flashes of fireflies to Josephson junctions and power infrastructure, networks of coupled phase oscillators provide a powerful framework to describe synchronization phenomena in many natural and engineered systems. Most real-world networks are under the influence of noisy, random inputs, potentially inhibiting synchronization. While noise is unavoidable, here we show that there exist optimal noise patterns which minimize desynchronizing effects and even enhance order. Specifically, using analytical arguments we show that in the case of a two-oscillator model, there exists a sharp transition from a regime where the optimal synchrony-enhancing noise is perfectly anticorrelated, to one where the optimal noise is correlated. More generally, we then use numerical optimization methods to demonstrate that there exist anticorrelated noise patterns that optimally enhance synchronization in large complex oscillator networks. Our results may have implications in networks such as power grids and neuronal networks, which are subject to significant amounts of correlated input noise.
从萤火虫的闪光到约瑟夫森结和电力基础设施，耦合相振荡器网络为描述许多自然和工程系统中的同步现象提供了一个强大的框架。大多数现实世界的网络都受到噪声、随机输入的影响，这可能会抑制同步。虽然噪声是不可避免的，但在这里我们表明，存在最优噪声模式，可以最小化去同步效应，甚至增强有序性。具体来说，我们使用分析论证表明，在两个振荡器模型的情况下，存在从最佳同步增强噪声完全反相关的区域到最佳噪声相关的区域的急剧转变。更一般地，我们然后使用数值优化方法来证明在大型复杂振荡器网络中存在最佳增强同步的反相关噪声模式。我们的结果可能对电网和神经元网络等网络产生影响，这些网络会受到大量相关输入噪声的影响。
