English

Community structure of the pseudofractal web

Physics and Society 2026-07-03 v1 Disordered Systems and Neural Networks Combinatorics

Abstract

The Ramsey community number rκr_\kappa is the smallest network size at which a graph is better described by a partition into communities than by no partition, under a prescribed detection rule. On a scale-free graph this question is confounded: a block model can split the network merely to absorb its degree distribution. I compute rκr_\kappa analytically for the deterministic pseudofractal scale-free web of Dorogovtsev, Goltsev, and Mendes, separating genuine community structure from degree heterogeneity with two closed-form detection rules. Under a plain Bernoulli stochastic block model, the web's natural recursive bipartition is unpreferred while small and breaks at rκ=1095r_\kappa=1095 nodes, with a log-evidence growing as (ln323ln2)n(\ln 3-\tfrac{2}{3}\ln 2)n. Under a degree-corrected model tested against the configuration-model null, the same partition survives, breaking far earlier at rκ=42r_\kappa=42, with a log-evidence growing as (2ln343ln2)n(2\ln 3-\tfrac{4}{3}\ln 2)n -- exactly twice the plain slope, and independent of the prior. Degree correction reverses the ordering of the candidate cuts, demoting the hub-leaf split and elevating the recursive one. Because the web is self-similar, the best description is not two communities but a nested hierarchy: the degree-corrected evidence keeps rising as the partition is refined, and is maximised at of order n\sqrt{n} communities of n\sim\sqrt{n} nodes. A purely local recursive rule thus builds true hierarchical community structure, over and above the scale-free degree sequence it also produces, in an exactly solvable setting.

Keywords

Cite

@article{arxiv.2607.03010,
  title  = {Community structure of the pseudofractal web},
  author = {Alexei Vazquez},
  journal= {arXiv preprint arXiv:2607.03010},
  year   = {2026}
}

Comments

7 pages, 5 figures