论文标题
部分可观测时空混沌系统的无模型预测
Faster network disruption from layered oscillatory dynamics
论文作者
论文摘要
非线性复杂网络耦合系统通常具有多个稳定的平衡状态。在扰动或由于环境噪声所致，将系统从其初始平衡中推开，并取决于游览的方向和幅度，可能会经历向另一个平衡的过渡。最近被证明了[M. Tyloo，J。Phys。复杂的。 3 03LT01（2022）]，分层的复杂网络可能会显示出放大的波动。在这里，我研究了具有系统特异性相关性的噪声如何影响非线性耦合振荡器的第一个逃生时间。有趣的是，我表明，波动的强烈扩增不仅是对网络良好功能的威胁，而且还威胁到噪声沿Laplacian矩阵的最低特征模式的噪声的空间和时间相关性。我分析了合成网络上的第一个逃生时间，并比较源自分层动力学的噪声到不相关的噪声。
Nonlinear complex network-coupled systems typically have multiple stable equilibrium states. Following perturbations or due to ambient noise, the system is pushed away from its initial equilibrium and, depending on the direction and the amplitude of the excursion, might undergo a transition to another equilibrium. It was recently demonstrated [M. Tyloo, J. Phys. Complex. 3 03LT01 (2022)], that layered complex networks may exhibit amplified fluctuations. Here I investigate how noise with system-specific correlations impacts the first escape time of nonlinearly coupled oscillators. Interestingly, I show that, not only the strong amplification of the fluctuations is a threat to the good functioning of the network, but also the spatial and temporal correlations of the noise along the lowest-lying eigenmodes of the Laplacian matrix. I analyze first escape times on synthetic networks and compare noise originating from layered dynamics, to uncorrelated noise.
