论文标题
部分可观测时空混沌系统的无模型预测
Mean-field nature of synchronization stability in networks with multiple interaction layers
论文作者
论文摘要
许多现实世界系统的组件之间的相互作用最好由具有多层层的网络建模。已经提出了不同的理论来解释多层连接如何影响动态系统中同步的线性稳定性。但是,最终的方程式在计算上很昂贵,因此很难(即使不是不可能)解决大型系统。为了弥合这一差距,我们为具有多个相互作用层的网络开发了平均景点的同步理论。通过假设标准层,我们可以获得与确切结果相当的同步稳定性的准确评估。实际上,即使对于具有非常不同层的网络,我们理论的准确性仍然很高,因此提出了一个关于多层网络同步稳定性的平均场地性质的一般问题。此外,我们方法的计算复杂性仅在节点的数量上是二次的,从而允许研究其研究的系统。
The interactions between the components of many real-world systems are best modelled by networks with multiple layers. Different theories have been proposed to explain how multilayered connections affect the linear stability of synchronization in dynamical systems. However, the resulting equations are computationally expensive, and therefore difficult, if not impossible, to solve for large systems. To bridge this gap, we develop a mean-field theory of synchronization for networks with multiple interaction layers. By assuming quasi-identical layers, we obtain accurate assessments of synchronization stability that are comparable with the exact results. In fact, the accuracy of our theory remains high even for networks with very dissimilar layers, thus posing a general question about the mean-field nature of synchronization stability in multilayer networks. Moreover, the computational complexity of our approach is only quadratic in the number of nodes, thereby allowing the study of systems whose investigation was thus far precluded.