Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > math > arXiv:2510.01949

Help | Advanced Search

Mathematics > Combinatorics

arXiv:2510.01949 (math)
[Submitted on 2 Oct 2025 ]

Title: On Kotzig's conjecture in random graphs

Title: 关于随机图中的Kotzig猜想

Authors:Stefan Glock, Amedeo Sgueglia
Abstract: In 1963, Anton Kotzig famously conjectured that $K_{n}$, the complete graph of order $n$, where $n$ is even, can be decomposed into $n-1$ perfect matchings such that every pair of these matchings forms a Hamilton cycle. The problem is still wide open and here we consider a variant of it for the binomial random graph $G(n,p)$. We prove that, for every fixed $k$, there exists a constant $C=C(k)$ such that, when $p\ge \frac{C \log n}{n}$, with high probability, $G(n,p)$ contains $k$ edge-disjoint perfect matchings with the property that every pair of them forms a Hamilton cycle. In fact, our main result is a very precise counting result for $K_n$. We show that, given any $k$ edge-disjoint perfect matchings $M_1,\dots,M_k$, the probability that a uniformly random perfect matching $M^*$ in $K_n$ has the property that $M^*\cup M_i$ forms a Hamilton cycle for each $i\in [k]$ is $\Theta_k(n^{-k/2})$. This is proved by building on a variety of methods, including a random process analysis, the absorption method, the entropy method and the switching method. The result on the binomial random graph follows from a slight strengthening of our counting result via the recent breakthroughs on the expectation threshold conjecture.
Abstract: 1963年,安东·科茨基著名地猜想,$K_{n}$,阶数为$n$的完全图,其中$n$是偶数,可以分解为$n-1$个完美匹配,使得每对这些匹配形成一个哈密顿循环。 这个问题仍然开放,这里我们考虑它在二项随机图$G(n,p)$中的变体。 我们证明,对于每个固定的$k$,存在一个常数$C=C(k)$,使得当$p\ge \frac{C \log n}{n}$时,高概率下$G(n,p)$包含$k$个边不相交的完美匹配,且每对之间形成一个哈密顿回路。事实上,我们的主要结果是对$K_n$的非常精确的计数结果。 我们证明,给定任何$k$个边不相交的完美匹配$M_1,\dots,M_k$,一个在$K_n$中均匀随机的完美匹配$M^*$使得$M^*\cup M_i$对每个$i\in [k]$形成一个哈密顿循环的概率是$\Theta_k(n^{-k/2})$。 这是通过多种方法的结合来证明的,包括随机过程分析、吸收法、熵法和切换法。 二项式随机图的结果是通过对我们的计数结果进行轻微加强,并利用最近在期望阈值猜想上的突破得出的。
Comments: 29 pages, 5 figures
Subjects: Combinatorics (math.CO)
Cite as: arXiv:2510.01949 [math.CO]
  (or arXiv:2510.01949v1 [math.CO] for this version)
  https://doi.org/10.48550/arXiv.2510.01949
arXiv-issued DOI via DataCite

Submission history

From: Amedeo Sgueglia [view email]
[v1] Thu, 2 Oct 2025 12:15:50 UTC (165 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • HTML (experimental)
  • TeX Source
view license
Current browse context:
math
< prev   |   next >
new | recent | 2025-10
Change to browse by:
math.CO

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号