English

The Metric Dimension of Sparse Random Graphs

Combinatorics 2025-05-01 v1 Data Structures and Algorithms Social and Information Networks Probability

Abstract

In 2013, Bollob\'as, Mitsche, and Pralat at gave upper and lower bounds for the likely metric dimension of random Erd\H{o}s-R\'enyi graphs G(n,p)G(n,p) for a large range of expected degrees d=pnd=pn. However, their results only apply when dlog5nd \ge \log^5 n, leaving open sparser random graphs with d<log5nd < \log^5 n. Here we provide upper and lower bounds on the likely metric dimension of G(n,p)G(n,p) from just above the connectivity transition, i.e., where d=pn=clognd=pn=c \log n for some c>1c > 1, up to d=log5nd=\log^5 n. Our lower bound technique is based on an entropic argument which is more general than the use of Suen's inequality by Bollob\'as, Mitsche, and Pralat, whereas our upper bound is similar to theirs.

Keywords

Cite

@article{arxiv.2504.21244,
  title  = {The Metric Dimension of Sparse Random Graphs},
  author = {Josep Díaz and Harrison Hartle and Cristopher Moore},
  journal= {arXiv preprint arXiv:2504.21244},
  year   = {2025}
}

Comments

23 pages, 0 figures

R2 v1 2026-06-28T23:16:08.567Z