English

Emergence of Long-Range Correlations in Random Networks

Physics and Society 2020-12-14 v1 Disordered Systems and Neural Networks

Abstract

We perform an analytical analysis of the long-range degree correlation of the giant component in an uncorrelated random network by employing generating functions. By introducing a characteristic length, we find that a pair of nodes in the giant component is negatively degree-correlated within the characteristic length and uncorrelated otherwise. At the critical point, where the giant component becomes fractal, the characteristic length diverges and the negative long-range degree correlation emerges. We further propose a correlation function for degrees of the ll-distant node pairs, which behaves as an exponentially decreasing function of distance in the off-critical region. The correlation function obeys a power-law with an exponential cutoff near the critical point. The Erd\H{o}s-R\'{e}nyi random graph is employed to confirm this critical behavior.

Keywords

Cite

@article{arxiv.2006.08132,
  title  = {Emergence of Long-Range Correlations in Random Networks},
  author = {Shogo Mizutaka and Takehisa Hasegawa},
  journal= {arXiv preprint arXiv:2006.08132},
  year   = {2020}
}

Comments

9 pages, 2 figures