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网络去同步化由非高斯涨落引起。

Network desynchronization by non-Gaussian fluctuations.

机构信息

U.S. Naval Research Laboratory, Code 6792, Plasma Physics Division, Washington, DC 20375, USA.

School of Engineering, University of Applied Sciences of Western Switzerland HES-SO, CH-1951 Sion, Switzerland.

出版信息

Phys Rev E. 2019 Nov;100(5-1):052314. doi: 10.1103/PhysRevE.100.052314.

Abstract

Many networks must maintain synchrony despite the fact that they operate in noisy environments. Important examples are stochastic inertial oscillators, which are known to exhibit fluctuations with broad tails in many applications, including electric power networks with renewable energy sources. Such non-Gaussian fluctuations can result in rare network desynchronization. Here we build a general theory for inertial oscillator network desynchronization by non-Gaussian noise. We compute the rate of desynchronization and show that higher moments of noise enter at specific powers of coupling: either speeding up or slowing down the rate exponentially depending on how noise statistics match the statistics of a network's slowest mode. Finally, we use our theory to introduce a technique that drastically reduces the effective description of network desynchronization. Most interestingly, when instability is associated with a single edge, the reduction is to one stochastic oscillator.

摘要

许多网络必须保持同步,尽管它们在嘈杂的环境中运行。重要的例子是随机惯性振荡器,它在许多应用中都表现出具有广泛尾部的波动,包括带有可再生能源的电力网络。这种非高斯波动会导致罕见的网络失步。在这里,我们通过非高斯噪声构建了惯性振荡器网络失步的一般理论。我们计算了失步的速率,并表明噪声的更高阶矩以特定的耦合幂次进入:根据噪声统计与网络最慢模式的统计如何匹配,要么以指数方式加速,要么减缓速率。最后,我们使用我们的理论引入了一种技术,可大大减少网络失步的有效描述。最有趣的是,当不稳定性与单个边缘相关联时,减少到一个随机振荡器。

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