论文标题
随机kuramoto模型的图形均值限制和同步
Graphop Mean-Field Limits and Synchronization for the Stochastic Kuramoto Model
论文作者
论文摘要
耦合振荡器网络的模型在描述生物学和技术系统中的集体同步动态方面起着重要作用。 Kuramoto模型描述了振荡器的相位演变,并解释了从不连贯到相干振荡的过渡,这些振荡在简化的假设中,包括全能的耦合,并均匀强度。但是,现实世界网络通常显示出异质的连通性和耦合权重,从而影响这种过渡的关键阈值。我们为随机的库拉莫托型相振荡器模型制定了一般平均场理论(vlasov-focker Planck方程),使用平均场限制中的图形图理论,适用于具有异质连接性和耦合强度的耦合图/网络。考虑对称的奇数耦合函数,我们在数学上证明了不连贯互动跃迁的临界阈值的确切公式。我们使用网络模型的大小有限大小表示来数值测试预测的阈值。对于大量的图形模型,我们发现数值测试与从平均场理论获得的预测阈值非常吻合。但是,对于足够稀疏的图形结构而言,实践中的预测更加困难。我们的发现开放了未来的研究途径,可以深入了解异质系统的平均场理论。
Models of coupled oscillator networks play an important role in describing collective synchronization dynamics in biological and technological systems. The Kuramoto model describes oscillator's phase evolution and explains the transition from incoherent to coherent oscillations under simplifying assumptions including all-to-all coupling with uniform strength. Real world networks, however, often display heterogeneous connectivity and coupling weights that influence the critical threshold for this transition. We formulate a general mean field theory (Vlasov-Focker Planck equation) for stochastic Kuramoto-type phase oscillator models, valid for coupling graphs/networks with heterogeneous connectivity and coupling strengths, using graphop theory in the mean field limit. Considering symmetric odd-valued coupling functions, we mathematically prove an exact formula for the critical threshold for the incoherence-coherence transition. We numerically test the predicted threshold using large finite-size representations of the network model. For a large class of graph models, we find that the numerical tests agree very well with the predicted threshold obtained from mean field theory. However, the prediction is more difficult in practice for graph structures that are sufficiently sparse. Our findings open future research avenues toward a deeper understanding of mean-field theories for heterogeneous systems.