Disparity Driven Heterogeneous Nucleation in Finite-Size Adaptive Networks

Akash Yadav, Jan Fialkowski, Rico Berner, V. K. Chandrasekar, D. V. Senthilkumar
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Abstract

Phase transitions are crucial in shaping the collective dynamics of a broad spectrum of natural systems across disciplines. Here, we report two distinct heterogeneous nucleation facilitating single-step and multi-step phase transitions to global synchronization in a finite-size adaptive network due to the trade-off between time scale adaptation and coupling strength disparities. Specifically, small intracluster nucleations coalesce either at the population interface or within the populations resulting in the two distinct phase transitions depending on the degree of the disparities. We find that the coupling strength disparity largely controls the nature of phase transition in the phase diagram irrespective of the adaptation disparity. We provide a mesoscopic description for the cluster dynamics using the collective coordinates approach that brilliantly captures the multicluster dynamics among the populations leading to distinct phase transitions. Further, we also deduce the upper bound for the coupling strength for the existence of two intraclusters explicitly in terms of adaptation and coupling strength disparities. These insights may have implications across domains ranging from neurological disorders to segregation dynamics in social networks.
有限规模自适应网络中由差异驱动的异质核化
相变对于塑造跨学科的各种自然系统的集体动力学至关重要。在这里,我们报告了在有限规模的自适应网络中,由于时间尺度适应和耦合强度差异之间的权衡,两种不同的异质成核促进了向全局同步的单步和多步相变。具体来说,小的簇内成核在种群界面或种群内部凝聚,导致两种不同的相变,具体取决于差异程度。我们发现,耦合强度差异在很大程度上控制着相图中相变的性质,而与适应差异无关。我们利用集体坐标方法对集群动力学进行了等离子体描述,从而出色地捕捉到了导致不同相变的种群间多集群动力学。此外,我们还从适应性和耦合强度差异的角度明确推导出了存在两个内集群的耦合强度上限。这些见解可能会对从神经系统疾病到社会网络中的隔离动力学等各个领域产生影响。
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