论文标题
通过二进制距离矩阵鉴定单孔和双孔连贯性含量模式
Identification of single- and double-well coherence-incoherence patterns by the binary distance matrix
论文作者
论文摘要
对嵌合体状态或更普遍的一致性 - 不一致模式的研究导致了几种用于识别和表征的工具的开发。在这项工作中，我们扩展了特征值分解方法，以区分单孔和双孔模式。通过应用我们的方法，我们能够在非局部耦合的Chua电路和非局部耦合的立方映射的环中识别以下四种类型的动态模式：单孔集群，单孔连贯 - 含量 - 结合模式，双孔群集和双孔均匀的连贯性 - 和双孔的连贯性 - 含量。在Chua电路的环网络中，我们研究了在时空模式上添加中央节点的影响。我们的结果表明，增加与中央节点的耦合有利于单孔相干 - 成分状态的发生。我们观察到，吸引盆地的边界类似于分形和棘手的结构
The study of chimera states or, more generally, coherence-incoherence patterns has led to the development of several tools for their identification and characterization. In this work, we extend the eigenvalue decomposition method to distinguish between single-well and double-well patterns. By applying our method, we are able to identify the following four types of dynamical patterns in a ring of nonlocally coupled Chua circuits and nonlocally coupled cubic maps: single-well cluster, single-well coherence-incoherence pattern, double-well cluster, and double-well coherence-incoherence. In a ring-star network of Chua circuits, we investigate the influence of adding a central node on the spatio-temporal patterns. Our results show that increasing the coupling with the central node favors the occurrence of single-well coherence-incoherence states. We observe that the boundaries of the attraction basins resemble fractal and riddled structures
