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• W3106103553 abstract "We consider the Kuramoto model on sparse random networks such as the ErdH{o}s-R'enyi graph or its combination with a regular two-dimensional lattice and study the dynamical scaling behavior of the model at the synchronization transition by large-scale, massively parallel numerical integration. By this method, we obtain an estimate of critical coupling strength more accurate than obtained earlier by finite-size scaling of the stationary order parameter. Our results confirm the compatibility of the correlation-size and the temporal correlation-length exponent with the mean-field universality class. However, the scaling of the order parameter exhibits corrections much stronger than those of the Kuramoto model with all-to-all coupling, making thereby an accurate estimate of the order-parameter exponent hard. We find furthermore that, as a qualitative difference to the model with all-to-all coupling, the effective critical exponents involving the order-parameter exponent, such as the effective decay exponent characterizing the critical desynchronization dynamics show a non-monotonic approach toward the asymptotic value. In the light of these results, the technique of finite-size scaling of limited size data for the Kuramoto model on sparse graphs has to be treated cautiously." @default.
• W3106103553 created "2020-11-23" @default.
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• W3106103553 date "2019-05-24" @default.
• W3106103553 modified "2023-09-26" @default.
• W3106103553 title "Critical dynamics of the Kuramoto model on sparse random networks" @default.
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• W3106103553 doi "https://doi.org/10.1088/1742-5468/ab16c3" @default.
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