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Hauptverfasser: Addario-Berry, Louigi, Angel, Omer, Lugosi, Gábor, Rácz, Miklós Z., Schramm, Tselil
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2602.07669
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author Addario-Berry, Louigi
Angel, Omer
Lugosi, Gábor
Rácz, Miklós Z.
Schramm, Tselil
author_facet Addario-Berry, Louigi
Angel, Omer
Lugosi, Gábor
Rácz, Miklós Z.
Schramm, Tselil
contents In this paper, we study the problem of detecting the presence of a planted perfect matching or spanning tree in an Erdős--Rényi random graph. More precisely, we study the hypothesis testing problem where the statistician observes a graph on $n$ vertices. Under the null hypothesis, the graph is a realization of an Erdős--Rényi random graph $G(n,q)$, while under the alternative hypothesis, the graph is the union of an Erdős--Rényi random graph and a random perfect matching (or random spanning tree). In order to avoid trivial detection by counting edges, we adjust the alternative hypothesis so that the expected number of edges under both distributions coincides. We prove that in both problems, when $q\gg n^{-1/2}$, no test can perform better than random guessing, while for $q\ll n^{-1/2}$, there exist computationally efficient tests that guess correctly with high probability.
format Preprint
id arxiv_https___arxiv_org_abs_2602_07669
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The statistical threshold for planted matchings and spanning trees
Addario-Berry, Louigi
Angel, Omer
Lugosi, Gábor
Rácz, Miklós Z.
Schramm, Tselil
Statistics Theory
In this paper, we study the problem of detecting the presence of a planted perfect matching or spanning tree in an Erdős--Rényi random graph. More precisely, we study the hypothesis testing problem where the statistician observes a graph on $n$ vertices. Under the null hypothesis, the graph is a realization of an Erdős--Rényi random graph $G(n,q)$, while under the alternative hypothesis, the graph is the union of an Erdős--Rényi random graph and a random perfect matching (or random spanning tree). In order to avoid trivial detection by counting edges, we adjust the alternative hypothesis so that the expected number of edges under both distributions coincides. We prove that in both problems, when $q\gg n^{-1/2}$, no test can perform better than random guessing, while for $q\ll n^{-1/2}$, there exist computationally efficient tests that guess correctly with high probability.
title The statistical threshold for planted matchings and spanning trees
topic Statistics Theory
url https://arxiv.org/abs/2602.07669