Tanaka Takuma, Aoyagi Toshio
Department of Morphological Brain Science, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Oct;78(4 Pt 2):046210. doi: 10.1103/PhysRevE.78.046210. Epub 2008 Oct 20.
The phase order parameter of oscillators on a network is optimized using two different sets of constraints. First, the maximization is achieved by adjusting the coupling strengths among the oscillators without changing the total coupling strength and the natural frequencies of the oscillators. This optimization reveals that a stronger weight tends to be assigned to a connection between two oscillators with greatly different natural frequencies. Second, we vary both coupling strengths and natural frequencies while maximizing the phase order and minimizing the penalty function which prevents the natural frequencies of the oscillators from taking the same value. This optimization reveals that a large total coupling strength makes oscillators take two natural frequencies (two-group state), whereas a small total coupling strength facilitates the convergence of natural frequencies to one single value (one-group state). Small and large penalty parameters make the optimized network take the one- and two-group states, respectively. This phase transition is observed in all-to-all, lattice, and scale-free networks although the clustering coefficient of the strongest links in the optimized network reflects the difference of the underlying network topologies.
使用两组不同的约束条件对网络上振荡器的相位序参量进行优化。首先,在不改变振荡器的总耦合强度和固有频率的情况下,通过调整振荡器之间的耦合强度来实现最大化。这种优化表明,对于固有频率差异很大的两个振荡器之间的连接,往往会赋予更强的权重。其次,我们在最大化相位序并最小化防止振荡器固有频率取相同值的惩罚函数的同时,改变耦合强度和固有频率。这种优化表明,较大的总耦合强度会使振荡器呈现两个固有频率(两组状态),而较小的总耦合强度则有利于固有频率收敛到一个单一值(一组状态)。小的和大的惩罚参数分别使优化后的网络呈现一组和两组状态。尽管优化后网络中最强连接的聚类系数反映了底层网络拓扑结构的差异,但在全对全、晶格和无标度网络中均观察到了这种相变。