Saved in:
Bibliographic Details
Main Authors: Joos, Felix, Mattos, Letícia
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2512.08899
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915664192602112
author Joos, Felix
Mattos, Letícia
author_facet Joos, Felix
Mattos, Letícia
contents The Prague dimension of a graph $G$ is defined as the minimum number of complete graphs whose direct product contains $G$ as an induced subgraph. Introduced in the 1970s by Nešetřil, Pultr, and Rödl -- and motivated by the work of Dushnik and Miller, as well as by the induced Ramsey theorem -- determining the Prague dimension of a graph is a notoriously hard problem. In this paper, we show that for all $\varepsilon > 0$ and $p$ such that $ n^{-1+\varepsilon} \le p \le n^{-\varepsilon}$, with high probability the Prague dimension of $G_{n,p}$ is $Θ_{\varepsilon}(pn)$, which improves upon a recent result by Molnar, Rödl, Sales and Schacht. Inspired by the work of Bennett and Bohman, our approach centres on analysing a random greedy process that builds an independent set of size $Ω(p^{-1}\log pn)$ by iteratively selecting vertices uniformly at random from the common non-neighbourhood of those already chosen. Using the differential equation method, we show that every non-edge is essentially equally likely to be covered by this process, which is key to establishing our bound.
format Preprint
id arxiv_https___arxiv_org_abs_2512_08899
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the Prague dimension of sparse random graphs
Joos, Felix
Mattos, Letícia
Combinatorics
The Prague dimension of a graph $G$ is defined as the minimum number of complete graphs whose direct product contains $G$ as an induced subgraph. Introduced in the 1970s by Nešetřil, Pultr, and Rödl -- and motivated by the work of Dushnik and Miller, as well as by the induced Ramsey theorem -- determining the Prague dimension of a graph is a notoriously hard problem. In this paper, we show that for all $\varepsilon > 0$ and $p$ such that $ n^{-1+\varepsilon} \le p \le n^{-\varepsilon}$, with high probability the Prague dimension of $G_{n,p}$ is $Θ_{\varepsilon}(pn)$, which improves upon a recent result by Molnar, Rödl, Sales and Schacht. Inspired by the work of Bennett and Bohman, our approach centres on analysing a random greedy process that builds an independent set of size $Ω(p^{-1}\log pn)$ by iteratively selecting vertices uniformly at random from the common non-neighbourhood of those already chosen. Using the differential equation method, we show that every non-edge is essentially equally likely to be covered by this process, which is key to establishing our bound.
title On the Prague dimension of sparse random graphs
topic Combinatorics
url https://arxiv.org/abs/2512.08899