Better Synchronizability Predicted by Crossed Double Cycle
classification
❄️ cond-mat.stat-mech
keywords
crossedeigenratiosynchronizabilityaveragebetterdistancedoubleadjusting
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In this brief report, we propose a network model named crossed double cycles, which are completely symmetrical and can be considered as the extensions of nearest-neighboring lattices. The synchronizability, measured by eigenratio $R$, can be sharply enhanced by adjusting the only parameter, crossed length $m$. The eigenratio $R$ is shown very sensitive to the average distance $L$, and the smaller average distance will lead to better synchronizability. Furthermore, we find that, in a wide interval, the eigenratio $R$ approximately obeys a power-law form as $R\sim L^{1.5}$.
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