图的Aα-指数的独立数的锐界

IF 0.9 4区 数学 Q3 MATHEMATICS, APPLIED
Wan-ting Sun, Li-xia Yan, Shu-chao Li, Xue-chao Li
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引用次数: 0

摘要

给定图G,G的邻接矩阵和度对角矩阵分别用a(G)和D(G)表示。2017年,Nikiforov[24]提出了Aα-矩阵:Aα(G)=αD(G)+(1−α)A(G),其中α∈[0,1]。这个新矩阵的最大特征值称为G的A,对于α∈[0,1),我们刻画了独立数为i的n顶点图中具有最小Aα索引的图,其中\(i=1,\,\,\left\lfloor{{n\over 2}}}\right\lfloor,\left \lceil{n\over2}}\right\ rceil,\,\lft\lflor{n\Over2}}\right\rfloor+1,n-3,n-2,n-1\),而对于i=2,我们考虑了\(\alpha\in[0,{3\over 4}]\)的相同问题。此外,我们确定了具有给定独立数的n个顶点上具有最大Aα-指数(α∈[0,1))的唯一图(resp.tree),而对于具有给定独立号的n顶点二部图,我们用\(\alpha\in[{1\over2},1)\刻画了具有最大A Aα-指数的唯一图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sharp Bounds on the Aα-index of Graphs in Terms of the Independence Number

Given a graph G, the adjacency matrix and degree diagonal matrix of G are denoted by A(G) and D(G), respectively. In 2017, Nikiforov[24] proposed the Aα-matrix: Aα(G) = αD(G) + (1 − α)A(G), where α ∈ [0, 1]. The largest eigenvalue of this novel matrix is called the Aα-index of G. In this paper, we characterize the graphs with minimum Aα-index among n-vertex graphs with independence number i for α ∈ [0, 1), where \(i = 1,\,\,\left\lfloor {{n \over 2}} \right\rfloor,\left\lceil {{n \over 2}} \right\rceil,\,\left\lfloor {{n \over 2}} \right\rfloor + 1,n - 3,n - 2,n - 1\), whereas for i = 2 we consider the same problem for \(\alpha \in [0,{3 \over 4}]\). Furthermore, we determine the unique graph (resp. tree) on n vertices with given independence number having the maximum Aα-index with α ∈ [0, 1), whereas for the n-vertex bipartite graphs with given independence number, we characterize the unique graph having the maximum Aα-index with \(\alpha \in [{1 \over 2},1)\).

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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
70
审稿时长
3.0 months
期刊介绍: Acta Mathematicae Applicatae Sinica (English Series) is a quarterly journal established by the Chinese Mathematical Society. The journal publishes high quality research papers from all branches of applied mathematics, and particularly welcomes those from partial differential equations, computational mathematics, applied probability, mathematical finance, statistics, dynamical systems, optimization and management science.
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