关于具有不可对角化邻接矩阵的有向图的Babai问题的一个解法

IF 1 2区 数学 Q1 MATHEMATICS Combinatorica Pub Date : 2023-09-29 DOI:10.1007/s00493-023-00068-x
Yuxuan Li, Binzhou Xia, Sanming Zhou, Wenying Zhu
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引用次数: 1

摘要

每个有限图的邻接矩阵都是可对角化的,这一事实在谱图理论中起着重要作用。由于这一事实不适用于有向图,所以很自然地会问它是否适用于具有一定对称性的有向图。人们对这个问题的兴趣可以追溯到20世纪80年代初,当时P.J.Cameron要求存在具有不可对角化邻接矩阵的弧传递有向图。这一点得到了Babai的肯定回答(J图论9:363–3701985)。然后,Babai提出了构造邻接矩阵不可对角化的2-arc-变换有向图和顶点基有向图的开放问题。在本文中,我们通过为每个整数构造一个无限族的s-arc-变换有向图和一个无穷族的顶点原始有向图来解决Babai问题,这两个有向图的邻接矩阵都是不可对角化的。
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A Solution to Babai’s Problems on Digraphs with Non-diagonalizable Adjacency Matrix

The fact that the adjacency matrix of every finite graph is diagonalizable plays a fundamental role in spectral graph theory. Since this fact does not hold in general for digraphs, it is natural to ask whether it holds for digraphs with certain level of symmetry. Interest in this question dates back to the early 1980 s, when P. J. Cameron asked for the existence of arc-transitive digraphs with non-diagonalizable adjacency matrix. This was answered in the affirmative by Babai (J Graph Theory 9:363–370, 1985). Then Babai posed the open problems of constructing a 2-arc-transitive digraph and a vertex-primitive digraph whose adjacency matrices are not diagonalizable. In this paper, we solve Babai’s problems by constructing an infinite family of s-arc-transitive digraphs for each integer \(s\ge 2\), and an infinite family of vertex-primitive digraphs, both of whose adjacency matrices are non-diagonalizable.

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来源期刊
Combinatorica
Combinatorica 数学-数学
CiteScore
1.90
自引率
0.00%
发文量
45
审稿时长
>12 weeks
期刊介绍: COMBINATORICA publishes research papers in English in a variety of areas of combinatorics and the theory of computing, with particular emphasis on general techniques and unifying principles. Typical but not exclusive topics covered by COMBINATORICA are - Combinatorial structures (graphs, hypergraphs, matroids, designs, permutation groups). - Combinatorial optimization. - Combinatorial aspects of geometry and number theory. - Algorithms in combinatorics and related fields. - Computational complexity theory. - Randomization and explicit construction in combinatorics and algorithms.
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