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Strong Detection Threshold for Correlated Erd\H{o}s-R\'enyi Graphs with Constant Average Degree

Probability 2025-06-17 v1

Abstract

Consider a pair of correlated Erd\H{o}s-R\'enyi graphs G(n,λn;s)\mathcal G(n,\tfrac{\lambda}{n};s) that are subsampled from a common parent Erd\H{o}s-R\'enyi graph with average degree λ\lambda and subsampling probability ss. We establish a sharp information-theoretic threshold for the detection problem between this model and two independent Erd\H{o}s-R\'enyi graphs G(n,λn)\mathcal G(n,\tfrac{\lambda}{n}), showing that strong detection is information-theoretically possible if and only if s>min{1λ,α}s>\min\{ \tfrac{1}{\sqrt{\lambda}}, \sqrt{\alpha} \} where α0.338\alpha\approx 0.338 is the Otter's constant. Our result resolves a constant gap between arXiv:2203.14573 and arXiv:2008.10097.

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Cite

@article{arxiv.2506.12752,
  title  = {Strong Detection Threshold for Correlated Erd\H{o}s-R\'enyi Graphs with Constant Average Degree},
  author = {Chenxu Feng},
  journal= {arXiv preprint arXiv:2506.12752},
  year   = {2025}
}

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14 pages