Institut für Theoretische Physik, Technische Universität Berlin, 10623 Berlin, Germany.
Chaos. 2022 Dec;32(12):121106. doi: 10.1063/5.0123886.
We show that multiplexing (Here, the term "multiplexing" means a special network topology where a one-layer network is connected to another one-layer networks through coupling between replica nodes. In the present paper, this term does not refer to the signal processing issues and telecommunications.) allows us to control noise-induced dynamics of multilayer networks in the regime of stochastic resonance. We illustrate this effect on an example of two- and multi-layer networks of bistable overdamped oscillators. In particular, we demonstrate that multiplexing suppresses the effect of stochastic resonance if the periodic forcing is present in only one layer. In contrast, multiplexing allows us to enhance the stochastic resonance if the periodic forcing and noise are present in all the interacting layers. In such a case, the impact of multiplexing has a resonant character: the most pronounced effect of stochastic resonance is achieved for an appropriate intermediate value of coupling strength between the layers. Moreover, multiplexing-induced enhancement of the stochastic resonance can become more pronounced for the increasing number of coupled layers. To visualize the revealed phenomena, we use the evolution of the dependence of the signal-to-noise ratio on the noise intensity for varying strength of coupling between the layers.
我们表明，复用（这里，术语“复用”是指一种特殊的网络拓扑结构，其中一层网络通过复制节点之间的耦合连接到另一个一层网络。在本文中，这个术语不是指信号处理问题和电信。）允许我们在随机共振的情况下控制多层网络中的噪声诱导动力学。我们以双稳过阻尼振荡器的两层和多层网络为例来说明这种效应。具体来说，我们证明，如果周期性强迫仅存在于一层中，复用会抑制随机共振的效果。相比之下，如果周期性强迫和噪声存在于所有相互作用的层中，复用可以增强随机共振。在这种情况下，复用的影响具有共振特性：对于层之间耦合强度的适当中间值，可以实现随机共振的最显著效果。此外，随着耦合层数量的增加，复用诱导的随机共振增强可以更加明显。为了可视化所揭示的现象，我们使用信号与噪声比随噪声强度变化的依赖关系的演化来表示不同层之间耦合强度的变化。
