论文标题

图形的随机嵌入:大多数图中的预期面数是对数的

Random Embeddings of Graphs: The Expected Number of Faces in Most Graphs is Logarithmic

论文作者

Loth, Jesse Campion, Halasz, Kevin, Masařík, Tomáš, Mohar, Bojan, Šámal, Robert

论文摘要

通过在每个顶点周围选择一个随机的局部旋转来获得连接的图形$ g $的随机2细胞嵌入。在此设置下,相应2细胞嵌入的面部数量或属变为随机变量。已经对两个特定图形类别的两个特定图形类别的随机嵌入式嵌入了$ n $ loop的花束和连接两个顶点的$ n $并行边缘的随机嵌入,并且已经进行了广泛的研究,并得到了充分理解。但是,关于更多一般图表知之甚少。本文的结果解释了为什么蒙特卡洛方法无法用于近似图的最小属。 Stahl在他的突破性工作[置入分区对,JCTB 1991]中,开发了“随机拓扑图理论”的基础。直到今天,他的大多数结果一直没有超越。在我们的工作中,我们分析了图$ g $的随机嵌入(等效属)的预期面孔数量。最近显示,对于任何图$ g $,最多的面孔数量是线性的。我们表明,实际的面孔数量$ f(g)$几乎总是要小得多。特别是,我们证明: 1)$ \ frac {1} {2} \ ln n -2 <\ mathbb {e} [f(k_n)] \ le 3.65 \ ln n n +o(1)$。 2)对于随机图,$ g(n,p)$($ p = p(n)$),我们有$ \ mathbb {e} [f(g(n,p))] \ le \ le \ ln^2 n+\ frac {1} {1} {p} $。 3)对于仅包含图的随机模型$ b(n,δ)$,其最高度最高为$δ$,我们通过证明所期望的面部为$θ(\ log n)$来获得更强的界限。

A random 2-cell embedding of a connected graph $G$ in some orientable surface is obtained by choosing a random local rotation around each vertex. Under this setup, the number of faces or the genus of the corresponding 2-cell embedding becomes a random variable. Random embeddings of two particular graph classes, those of a bouquet of $n$ loops and those of $n$ parallel edges connecting two vertices, have been extensively studied and are well-understood. However, little is known about more general graphs. The results of this paper explain why Monte Carlo methods cannot work for approximating the minimum genus of graphs. In his breakthrough work [Permutation-partition pairs, JCTB 1991], Stahl developed the foundation of "random topological graph theory". Most of his results have been unsurpassed until today. In our work, we analyze the expected number of faces of random embeddings (equivalently, the average genus) of a graph $G$. It was very recently shown that for any graph $G$, the expected number of faces is at most linear. We show that the actual expected number of faces $F(G)$ is almost always much smaller. In particular, we prove: 1) $\frac{1}{2}\ln n - 2 < \mathbb{E}[F(K_n)] \le 3.65 \ln n +o(1)$. 2) For random graphs $G(n,p)$ ($p=p(n)$), we have $\mathbb{E}[F(G(n,p))] \le \ln^2 n+\frac{1}{p}$. 3) For random models $B(n,Δ)$ containing only graphs, whose maximum degree is at most $Δ$, we obtain stronger bounds by showing that the expected number of faces is $Θ(\log n)$.

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