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arXiv 1503.04539cond-mat.stat-mechnlin.CD
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哈密顿平均场模型:网络结构对同步动力学的影响

The Hamiltonian Mean Field model: effect of network structure on synchronization dynamics

Yogesh S. Virkar, Juan G. Restrepo, James D. Meiss

摘要:

耦合惯性哈密顿转子的哈密顿平均场(HMF)模型是具有长程相互作用的系统中保守动力学的原型。我们考虑的情况下,转子之间的相互作用所描述的加权邻接矩阵的网络。通过研究非相干态的线性稳定性,我们发现,当耦合常数$K$与邻接矩阵的最大特征值成反比时,非相干态向同步态的跃迁发生。我们推导了一组局部序参量的封闭方程组,并利用这些方程研究了网络异质性对转子同步的影响。我们发现,对于值的$K$刚刚超过过渡到同步的同步程度是高度依赖于网络的异质性,但对于大值的$K$的同步程度是强大的网络的度分布的异质性的变化。我们的研究结果与Erdös-Renyi网络和网络的幂律度分布的数值模拟。

英文摘要:

The Hamiltonian Mean Field (HMF) model of coupled inertial, Hamiltonian rotors is a prototype for conservative dynamics in systems with long-range interactions. We consider the case where the interactions between the rotors are governed by a network described by a weighted adjacency matrix. By studying the linear stability of the incoherent state, we find that the transition to synchrony occurs at a coupling constant $K$ inversely proportional to the largest eigenvalue of the adjacency matrix. We derive a closed system of equations for a set of local order parameters and use these equations to study the effect of network heterogeneity on the synchronization of the rotors. We find that for values of $K$ just beyond the transition to synchronization the degree of synchronization is highly dependent on the network's heterogeneity, but that for large values of $K$ the degree of synchronization is robust to changes in the heterogeneity of the network's degree distribution. Our results are illustrated with numerical simulations on Erdös-Renyi networks and networks with power-law degree distributions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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