关于非负矩阵的最大扩展

IF 1.1 3区 数学 Q1 MATHEMATICS
Linear Algebra and its Applications Pub Date : 2026-02-15 Epub Date: 2025-11-17 DOI:10.1016/j.laa.2025.11.012
Susie Lu, John Urschel
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引用次数: 0

摘要

给定一个有向图G, G的扩展是其邻接矩阵的任意两个特征值之间的最大距离。在2022年,Breen、Riasanovsky、Tait和Urschel提出了一个问题:什么样的n顶点有向图能使传播最大化,以及这个图是否无向。我们证明了更一般的结果,即任意n×n非负矩阵A的最大‖A‖≤1的扩展不超过2n/3,该结果紧于一个可加因子,且当n是3的倍数时精确。进一步地,我们的结果表明具有最大扩展的矩阵总是对称的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the maximum spread of non-negative matrices
Given a directed graph G, the spread of G is the largest distance between any two eigenvalues of its adjacency matrix. In 2022, Breen, Riasanovsky, Tait, and Urschel asked what n-vertex directed graph maximizes spread, and whether this graph is undirected. We prove the more general result that the spread of any n×n non-negative matrix A with ‖A‖max≤1 is at most 2n/3, which is tight up to an additive factor and exact when n is a multiple of three. Furthermore, our results show that the matrix with maximum spread is always symmetric.
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来源期刊
CiteScore
2.20
自引率
9.10%
发文量
333
审稿时长
13.8 months
期刊介绍: Linear Algebra and its Applications publishes articles that contribute new information or new insights to matrix theory and finite dimensional linear algebra in their algebraic, arithmetic, combinatorial, geometric, or numerical aspects. It also publishes articles that give significant applications of matrix theory or linear algebra to other branches of mathematics and to other sciences. Articles that provide new information or perspectives on the historical development of matrix theory and linear algebra are also welcome. Expository articles which can serve as an introduction to a subject for workers in related areas and which bring one to the frontiers of research are encouraged. Reviews of books are published occasionally as are conference reports that provide an historical record of major meetings on matrix theory and linear algebra.
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