On the binary and Boolean rank of regular matrices

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Ishay Haviv , Michal Parnas
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引用次数: 0

Abstract

A 0,1 matrix is said to be regular if all of its rows and columns have the same number of ones. We prove that for infinitely many integers k, there exists a square regular 0,1 matrix with binary rank k, such that the Boolean rank of its complement is kΩ˜(logk). This settles, in a strong form, a question of Pullman (1988) [27] and a conjecture of Hefner et al. (1990) [18]. The result can be viewed as a regular analogue of a recent result of Balodis et al. (2021) [2], motivated by the clique vs. independent set problem in communication complexity and by the (disproved) Alon-Saks-Seymour conjecture in graph theory. As an application of the produced regular matrices, we obtain regular counterexamples to the Alon-Saks-Seymour conjecture and prove that for infinitely many integers k, there exists a regular graph with biclique partition number k and chromatic number kΩ˜(logk).

正则矩阵的二进制和布尔秩
如果0,1矩阵的所有行和列都有相同数量的1,则称其为正则矩阵。我们证明了对于无穷多个整数k,存在一个二元秩为k的平方正则0,1矩阵,使得其补码的布尔秩为kΩ~(log⁡k) 。这以强有力的形式解决了Pullman(1988)[27]的问题和Hefner等人(1990)[18]的猜想。该结果可以被视为Balodis等人最近的一个结果的正则类似物。(2021)[2],其动机是通信复杂性中的集团与独立集问题,以及图论中的(已推翻的)Alon Saks Seymour猜想。作为生成的正则矩阵的一个应用,我们得到了Alon-Saks-Seymour猜想的正则反例,并证明了对于无限多个整数k,存在一个具有bilique分位数k和色数kΩ~(log⁡k) 。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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