TY - JOUR
T1 - Synchronization in the Kuramoto model
T2 - A dynamical gradient network approach
AU - Chen, Maoyin
AU - Shang, Yun
AU - Zou, Yong
AU - Kurths, Juergen
PY - 2008/2/11
Y1 - 2008/2/11
N2 - We propose a dynamical gradient network approach to consider the synchronization in the Kuramoto model. Our scheme to adaptively adjust couplings is based on the dynamical gradient networks, where the number of links in each time interval is the same as the number of oscillators, but the links in different time intervals are also different. The gradient network in the (n+1)th time interval is decided by the oscillator dynamics in the nth time interval. According to the gradient network in the (n+1)th time interval, only one inlink's coupling for each oscillator is adjusted by a small incremental coupling. During the transition to synchronization, the intensities for all oscillators are identical. Direct numerical simulations fully verify that the synchronization in the Kuramoto model is realized effectively, even if there exist delayed couplings and external noise.
AB - We propose a dynamical gradient network approach to consider the synchronization in the Kuramoto model. Our scheme to adaptively adjust couplings is based on the dynamical gradient networks, where the number of links in each time interval is the same as the number of oscillators, but the links in different time intervals are also different. The gradient network in the (n+1)th time interval is decided by the oscillator dynamics in the nth time interval. According to the gradient network in the (n+1)th time interval, only one inlink's coupling for each oscillator is adjusted by a small incremental coupling. During the transition to synchronization, the intensities for all oscillators are identical. Direct numerical simulations fully verify that the synchronization in the Kuramoto model is realized effectively, even if there exist delayed couplings and external noise.
U2 - 10.1103/PhysRevE.77.027101
DO - 10.1103/PhysRevE.77.027101
M3 - Article
SN - 1539-3755
VL - 77
JO - Physical Review. E, Statistical, Nonlinear and Soft Matter Physics
JF - Physical Review. E, Statistical, Nonlinear and Soft Matter Physics
IS - 2
M1 - 027101
ER -