标题： 基于序方法的爆炸性同步局部预测器 显示英文标题

标题： Local predictors of explosive synchronization with ordinal methods

摘要： 我们建议使用在哨兵中心节点测量的序数模式转移（OPT）熵作为预测各种动态系统网络中同步爆炸性转变的潜在预测因子。 我们的结果表明，OPT熵度量超越了传统的早期预警信号（EWS）度量，并且可能对可用于预测临界转变的工具有价值。 特别是，我们研究了扩散耦合相位振荡器和混沌Rössler系统的网络。 作为映射，我们考虑了在星形和无标度配置中耦合的Chialvo映射的神经网络。 此外，我们将此度量应用于在混沌状态下运行的电子电路网络的时间序列数据。 显示英文摘要

摘要： We propose to use the ordinal pattern transition (OPT) entropy measured at sentinel central nodes as a potential predictor of explosive transitions to synchronization in networks of various dynamical systems with increasing complexity. Our results demonstrate that the OPT entropic measure surpasses traditional early warning signals (EWS) measures and could be valuable to the tools available for predicting critical transitions. In particular, we investigate networks of diffusively coupled phase oscillators and chaotic R\"ossler systems. As maps, we consider a neural network of Chialvo maps coupled in star and scale-free configurations. Furthermore, we apply this measure to time series data obtained from a network of electronic circuits operating in the chaotic regime.