Asymptotic normality of embedding distributions of some families of graphs

Fuente: arXiv
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Détails bibliographiques
Auteurs principaux: Chen, Yichao, Fang, Wenjie, Gao, Zhicheng, Zhang, Jinlian
Format: Preprint
Publié: 2025
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author Chen, Yichao
Fang, Wenjie
Gao, Zhicheng
Zhang, Jinlian
author_facet Chen, Yichao
Fang, Wenjie
Gao, Zhicheng
Zhang, Jinlian
contents Computing the embedding distribution of a given graph is a fundamental question in topological graph theory. In this article, we extend our viewpoint to a sequence of graphs and consider their asymptotic embedding distributions, which are often the normal distribution. We establish the asymptotic normality of several families of graphs by developing adapted tools and frameworks. We expect that these tools and frameworks can be used on other families of graphs to establish the asymptotic normality of their embedding distributions. Several open questions and conjectures are also raised in our investigation.
format Preprint
id arxiv_https___arxiv_org_abs_2507_15751
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Asymptotic normality of embedding distributions of some families of graphs
Chen, Yichao
Fang, Wenjie
Gao, Zhicheng
Zhang, Jinlian
Combinatorics
05A15, 05A16, 05C10
Computing the embedding distribution of a given graph is a fundamental question in topological graph theory. In this article, we extend our viewpoint to a sequence of graphs and consider their asymptotic embedding distributions, which are often the normal distribution. We establish the asymptotic normality of several families of graphs by developing adapted tools and frameworks. We expect that these tools and frameworks can be used on other families of graphs to establish the asymptotic normality of their embedding distributions. Several open questions and conjectures are also raised in our investigation.
title Asymptotic normality of embedding distributions of some families of graphs
topic Combinatorics
05A15, 05A16, 05C10
url https://arxiv.org/abs/2507.15751