English

Large deviation and anomalous fluctuations scaling in degree assortativity on configuration networks

Statistical Mechanics 2021-11-05 v3 Physics and Society

Abstract

By constructing a multicanonical Monte Carlo simulation, we obtain the full probability distribution ρN(r)\rho_N(r) of the degree assortativity coefficient rr on configuration networks of size NN by using the multiple histogram reweighting method. We suggest that ρN(r)\rho_N(r) obeys a large deviation principle, ρN(rrN)eNξI(rrN)\rho_N \left(r-r_N^* \right) \asymp {e^{ - {N^\xi }I\left( {r- r_N^* } \right)}}, where the rate function II is convex and possesses its unique minimum at r=rNr=r_N^*, and ξ\xi is an exponent that scales ρN\rho_N's with NN. We show that ξ=1\xi=1 for Poisson random graphs, and ξ1\xi\geq1 for scale-free networks in which ξ\xi is a decreasing function of the degree distribution exponent γ\gamma. Our results reveal that the fluctuations of rr exhibits an anomalous scaling with NN in highly heterogeneous networks.

Keywords

Cite

@article{arxiv.1907.13330,
  title  = {Large deviation and anomalous fluctuations scaling in degree assortativity on configuration networks},
  author = {Hanshuang Chen and Feng Huang and Chuansheng Shen and Guofeng Li and Haifeng Zhang},
  journal= {arXiv preprint arXiv:1907.13330},
  year   = {2021}
}

Comments

9 pages, 9 figures