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Optimization of synchronizability in multiplex networks by rewiring one layer

机译:通过重新加热一层优化多路复用网络中的同步性

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The mathematical framework of multiplex networks has been increasingly realized as a more suitable framework for modeling real-world complex systems. In this work, we investigate the optimization of synchronizability in multiplex networks by evolving only one layer while keeping other layers fixed. Our main finding is to show the conditions under which the efficiency of convergence to the most optimal structure is almost as good as the case where both layers are rewired during an optimization process. In particular, interlayer coupling strength responsible for the integration between the layers turns out to be a crucial factor governing the efficiency of optimization even for the cases when the layer going through the evolution has nodes interacting much more weakly than those in the fixed layer. Additionally, we investigate the dependency of synchronizability on the rewiring probability which governs the network structure from a regular lattice to the random networks. The efficiency of the optimization process preceding evolution driven by the optimization process is maximum when the fixed layer has regular architecture, whereas the optimized network is more synchronizable for the fixed layer having the rewiring probability lying between the small-world transition and the random structure.
机译:多路复用网络的数学框架越来越实现为更合适的建模现实世界复杂系统的框架。在这项工作中,我们通过仅在保持其他层固定的同时仅演变一层来调查多路复用网络中同步性的优化。我们的主要发现是展示了对最佳结构的收敛效率的条件几乎与在优化过程中重新连接的情况一样好。特别地,负责层之间的集成的中间层耦合强度据指导甚至在通过进化的层的情况下的情况下的优化效率的关键因素具有比固定层中的那些更弱得更弱的节点。另外,我们研究了同步性对重新布线概率的依赖性,该概率控制从常规格对随机网络的网络结构。当固定图层具有常规架构时,由优化过程驱动的进化的优化过程的效率最大,而优化的网络对于具有在小世界转换和随机结构之间的重新布线概率的固定层更同步。

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