A local limit theorem for the edge counts of random induced subgraphs of a random graph

Fuente: arXiv
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Main Authors: Balister, Paul, Powierski, Emil, Scott, Alex, Tan, Jane
Format: Preprint
Published: 2025
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_version_ 1866909557757837312
author Balister, Paul
Powierski, Emil
Scott, Alex
Tan, Jane
author_facet Balister, Paul
Powierski, Emil
Scott, Alex
Tan, Jane
contents Consider a `dense' Erdős--Rényi random graph model $G=G_{n,M}$ with $n$ vertices and $M$ edges, where we assume the edge density $M/\binom{n}{2}$ is bounded away from 0 and 1. Fix $k=k(n)$ with $k/n$ bounded away from 0 and~1, and let $S$ be a random subset of size $k$ of the vertices of $G$. We show that with probability $1-\exp(-n^{Ω(1)})$, $G$ satisfies both a central limit theorem and a local limit theorem for the empirical distribution of the edge count $e(G[S])$ of the subgraph of $G$ induced by $S$, where the distribution is over uniform random choices of the $k$-set $S$.
format Preprint
id arxiv_https___arxiv_org_abs_2503_23164
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A local limit theorem for the edge counts of random induced subgraphs of a random graph
Balister, Paul
Powierski, Emil
Scott, Alex
Tan, Jane
Combinatorics
Probability
Consider a `dense' Erdős--Rényi random graph model $G=G_{n,M}$ with $n$ vertices and $M$ edges, where we assume the edge density $M/\binom{n}{2}$ is bounded away from 0 and 1. Fix $k=k(n)$ with $k/n$ bounded away from 0 and~1, and let $S$ be a random subset of size $k$ of the vertices of $G$. We show that with probability $1-\exp(-n^{Ω(1)})$, $G$ satisfies both a central limit theorem and a local limit theorem for the empirical distribution of the edge count $e(G[S])$ of the subgraph of $G$ induced by $S$, where the distribution is over uniform random choices of the $k$-set $S$.
title A local limit theorem for the edge counts of random induced subgraphs of a random graph
topic Combinatorics
Probability
url https://arxiv.org/abs/2503.23164