New bounds on the modularity of $G(n,p)$
Abstract
Modularity is a parameter indicating the presence of community structure in the graph. Nowadays it lies at the core of widely used clustering algorithms. We study the modularity of the most classical random graph, binomial . In 2020 McDiarmid and Skerman proved, taking advantage of the spectral graph theory and a specific subgraph construction by Coja-Oghlan from 2007, that there exists a constant such that with high probability the modularity of is at most . The obtained constant is very big and not easily computable. We improve upon this result showing that a constant under may be derived here. Interesting is the fact that it might be obtained by basic probabilistic tools. We also address the lower bound on the modularity of and improve the results of McDiarmid and Skerman from 2020 using estimates of bisections of random graphs derived by Dembo, Montanari, and Sen in 2017.
Cite
@article{arxiv.2504.16254,
title = {New bounds on the modularity of $G(n,p)$},
author = {Katarzyna Rybarczyk and Małgorzata Sulkowska},
journal= {arXiv preprint arXiv:2504.16254},
year = {2025}
}
Comments
16 pages