Structural robustness of networks with degree-degree correlations between second-nearest neighbors.

ABSTRACT: We numerically investigate the robustness of networks with degree-degree correlations between nodes separated by distance l = 2 in terms of shortest path length. The degree-degree correlation between the l-th nearest neighbors can be quantified by Pearson's correlation coefficient rl for the degrees of two nodes at distance l. We introduce l-th nearest-neighbor correlated random networks (l-NNCRNs) that are degree-degree correlated at less than or equal to the l-th nearest neighbor scale and maximally random at farther scales. We generate 2-NNCRNs with various r1 and r2 using two steps of random edge rewiring based on the Metropolis-Hastings algorithm and compare their robustness against failures of nodes and edges. As typical cases of homogeneous and heterogeneous degree distributions, we

SUBMITTER: Fujiki Y 

PROVIDER: S-EPMC12680194 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature