论文标题
预测网络的动态几乎不取决于拓扑
Predicting Dynamics on Networks Hardly Depends on the Topology
论文作者
论文摘要
网络上的过程由两个相互依存的部分组成：网络拓扑组成，由节点之间的链接和动力学组成，由某些管理方程指定。这项工作基于过去对动态的观察，考虑了未知网络上未来动态的预测。对于一般的管理方程式，我们提出了一种预测算法，该算法将网络作为中间步骤。在实践中推断网络是不可能的，这是由于条件不良的线性系统。令人惊讶的是，尽管如此，对动态的高度准确预测是可能的：即使推断的网络与真实网络没有拓扑相似性，但两个网络实际上都会产生与将来的动态相同的动态。
Processes on networks consist of two interdependent parts: the network topology, consisting of the links between nodes, and the dynamics, specified by some governing equations. This work considers the prediction of the future dynamics on an unknown network, based on past observations of the dynamics. For a general class of governing equations, we propose a prediction algorithm which infers the network as an intermediate step. Inferring the network is impossible in practice, due to a dramatically ill-conditioned linear system. Surprisingly, a highly accurate prediction of the dynamics is possible nonetheless: Even though the inferred network has no topological similarity with the true network, both networks result in practically the same future dynamics.
