English

Multiplexity amplifies geometry in networks

Physics and Society 2026-02-24 v2 Disordered Systems and Neural Networks

Abstract

Many real-world network are multilayer, with nontrivial correlations across layers. Here we show that these correlations amplify geometry in networks. We focus on mutual clustering--a measure of the amount of triangles that are present in all layers among the same triplets of nodes--and find that this clustering is abnormally high in many real-world networks, even when clustering in each individual layer is weak. We explain this unexpected phenomenon using a simple multiplex network model with latent geometry: links that are most congruent with this geometry are the ones that persist across layers, amplifying the cross-layer triangle overlap. This result reveals a different dimension in which multilayer networks are radically distinct from their constituent layers.

Keywords

Cite

@article{arxiv.2505.17688,
  title  = {Multiplexity amplifies geometry in networks},
  author = {Jasper van der Kolk and Dmitri Krioukov and Marián Boguñá and M. Ángeles Serrano},
  journal= {arXiv preprint arXiv:2505.17688},
  year   = {2026}
}

Comments

10 pages, 3 figures (Supplementary Information 18 pages)

R2 v1 2026-07-01T02:33:31.271Z