纳米管的随机特征值

Artur Bille, Victor Buchstaber, Pavel Ievlev, Svyatoslav Novikov, Evgeny Spodarev
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引用次数: 0

摘要

六边形晶格及其对偶三角形晶格分别是理解textit{石墨烯}和textit{碳$(p,q)$--纳米管}中原子和环连接性的有力模型。这两种碳同素异形体的化学和物理属性与它们各自的图表示上不同长度 $k\in\mathbb{N}_0$ 的闭合路径的平均数量密切相关。考虑到碳$(p,q)$--纳米管可以看作是由$(p,q)$textit{手性矢量}决定的石墨烯薄片卷成的,我们的发现是基于对\cite{bille2023random}中呈现的六边形和三角形晶格的textit{随机特征值}的研究。这项研究揭示了对于任何给定的(p,q)$textit{手性向量},封闭路径的计数序列形成了由两个独立的均匀分布的函数导出的矩阵序列。针对手性矢量的特定选择,我们给出了包括概率密度函数(PDF)和矩生成函数(MGF)在内的分布关键特征的明确公式。此外,我们还证明了随着$(p,q)$--纳米管的textit{circumference}接近无穷大,即$p+q\rightarrow \infty$,$(p,q)$--纳米管在任何给定长度$k$的闭合路径数量方面趋于向六边形晶格收敛,这表明了底层分布的弱收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Random eigenvalues of nanotubes
The hexagonal lattice and its dual, the triangular lattice, serve as powerful models for comprehending the atomic and ring connectivity, respectively, in \textit{graphene} and \textit{carbon $(p,q)$--nanotubes}. The chemical and physical attributes of these two carbon allotropes are closely linked to the average number of closed paths of different lengths $k\in\mathbb{N}_0$ on their respective graph representations. Considering that a carbon $(p,q)$--nanotube can be thought of as a graphene sheet rolled up in a matter determined by the \textit{chiral vector} $(p,q)$, our findings are based on the study of \textit{random eigenvalues} of both the hexagonal and triangular lattices presented in \cite{bille2023random}. This study reveals that for any given \textit{chiral vector} $(p,q)$, the sequence of counts of closed paths forms a moment sequence derived from a functional of two independent uniform distributions. Explicit formulas for key characteristics of these distributions, including probability density function (PDF) and moment generating function (MGF), are presented for specific choices of the chiral vector. Moreover, we demonstrate that as the \textit{circumference} of a $(p,q)$--nanotube approaches infinity, i.e., $p+q\rightarrow \infty$, the $(p,q)$--nanotube tends to converge to the hexagonal lattice with respect to the number of closed paths for any given length $k$, indicating weak convergence of the underlying distributions.
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