论文标题

加权均匀大体的光谱

Spectra of weighted uniform hypertrees

论文作者

Wan, Jiang-Chao, Wang, Yi, Hu, Fu-Tao

论文摘要

令$ t $为$ k $ -tree,配备了加权功能$ \ w:v(t)\ cup e(t)\ rightarrow \ c $,其中$ k \ geq 3 $。加权匹配的$ k $ -tree $(t,\ w)$的加权匹配定义为$$μ(t,\ w,x)= \ sum _ {m \ in \ Mathcal {m} {m}(t)}(t)}(t)}(-1) \ prod_ {v \ in V(t)\ backslash v(m)}(x- \ w(v)),$$,其中$ \ mathcal {m}(m}(t)$表示$ t $的一组匹配项(包括空集)。在本文中,我们调查了加权$ k $ -tree $(t,\ w)$的邻接张量$ \ a(t,\ w)$的特征值。主要结果规定,$ \ w(v)$是v(t)$中每个$ v \的$ \ a(t,\ w)$的特征值,如果$ v(t)$ in v(t)$ in v(t)$中的每个$ v \ n neq \ neq \ w(v)$,则$λ$,则$λ$是$ \ w)of $ \ w) $ t $使$λ$是$μ(t',\ w,x)$的根。此外,$ \ a(t,\ w)$的光谱半径等于$ \ w $是真实且不负的,$μ(t,\ w,x)$的最大根。结果将Clark and Cooper({\ em在Hyperrees的邻接光谱上,Electron。J.Combin。,25(2)(2018)$ \#$ P2.48})扩展到加权$ k $ -trees。作为应用程序,获得了上述laplacian的两个类似物和$ k $树的无价的拉普拉斯张量。

Let $T$ be a $k$-tree equipped with a weighting function $\w: V(T)\cup E(T)\rightarrow \C$, where $k \geq 3$. The weighted matching polynomial of the weighted $k$-tree $(T,\w)$ is defined to be $$ μ(T,\w,x)= \sum_{M \in \mathcal{M}(T)}(-1)^{|M|}\prod_{e \in E(M)}\mathbf{w}(e)^k \prod_{v \in V(T)\backslash V(M)}(x-\w(v)), $$ where $\mathcal{M}(T)$ denotes the set of matchings (including empty set) of $T$. In this paper, we investigate the eigenvalues of the adjacency tensor $\A(T,\w)$ of the weighted $k$-tree $(T,\w)$. The main result provides that $\w(v)$ is an eigenvalue of $\A(T,\w)$ for every $v\in V(T)$, and if $λ\neq \w(v)$ for every $v\in V(T)$, then $λ$ is an eigenvalue of $\A(T,\w)$ if and only if there exists a subtree $T'$ of $T$ such that $λ$ is a root of $μ(T',\w,x)$. Moreover, the spectral radius of $\A(T,\w)$ is equal to the largest root of $μ(T,\w,x)$ when $\w$ is real and nonnegative. The result extends a work by Clark and Cooper ({\em On the adjacency spectra of hypertrees, Electron. J. Combin., 25 (2)(2018) $\#$P2.48}) to weighted $k$-trees. As applications, two analogues of the above work for the Laplacian and the signless Laplacian tensors of $k$-trees are obtained.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源