{"title":"Matroid Horn functions","authors":"Kristóf Bérczi , Endre Boros , Kazuhisa Makino","doi":"10.1016/j.jcta.2023.105838","DOIUrl":null,"url":null,"abstract":"<div><p>Hypergraph Horn functions were introduced as a subclass of Horn functions that can be represented by a collection of circular implication rules. These functions possess distinguished structural and computational properties. In particular, their characterizations in terms of implicate-duality and the closure operator provide extensions of matroid duality and the Mac Lane<!--> <!-->–<!--> <!-->Steinitz exchange property of matroid closure, respectively.</p><p>In the present paper, we introduce a subclass of hypergraph Horn functions that we call <em>matroid Horn</em> functions. We provide multiple characterizations of matroid Horn functions in terms of their canonical and complete CNF representations. We also study the Boolean minimization problem for this class, where the goal is to find a minimum size representation of a matroid Horn function given by a CNF representation. While there are various ways to measure the size of a CNF, we focus on the <em>number of circuits</em> and <em>circuit clauses</em>. We determine the size of an optimal representation for binary matroids, and give lower and upper bounds in the uniform case. For uniform matroids, we show a strong connection between our problem and Turán systems that might be of independent combinatorial interest.</p></div>","PeriodicalId":50230,"journal":{"name":"Journal of Combinatorial Theory Series A","volume":"203 ","pages":"Article 105838"},"PeriodicalIF":0.9000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0097316523001061/pdfft?md5=55c70db92d34f783b8e0189c2f8d7950&pid=1-s2.0-S0097316523001061-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Theory Series A","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0097316523001061","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
Hypergraph Horn functions were introduced as a subclass of Horn functions that can be represented by a collection of circular implication rules. These functions possess distinguished structural and computational properties. In particular, their characterizations in terms of implicate-duality and the closure operator provide extensions of matroid duality and the Mac Lane – Steinitz exchange property of matroid closure, respectively.
In the present paper, we introduce a subclass of hypergraph Horn functions that we call matroid Horn functions. We provide multiple characterizations of matroid Horn functions in terms of their canonical and complete CNF representations. We also study the Boolean minimization problem for this class, where the goal is to find a minimum size representation of a matroid Horn function given by a CNF representation. While there are various ways to measure the size of a CNF, we focus on the number of circuits and circuit clauses. We determine the size of an optimal representation for binary matroids, and give lower and upper bounds in the uniform case. For uniform matroids, we show a strong connection between our problem and Turán systems that might be of independent combinatorial interest.
超图角函数是角函数的一个子类,可以用一组圆形隐含规则表示。这些函数具有独特的结构和计算特性。特别是,它们在隐含对偶性和闭包算子方面的描述分别提供了矩阵对偶性的扩展和矩阵闭包的Mac Lane - Steinitz交换性质。本文引入了超图角函数的一个子类,我们称之为矩阵角函数。我们根据矩阵角函数的正则和完全CNF表示,给出了矩阵角函数的多种表征。我们还研究了该类的布尔最小化问题,其目标是找到由CNF表示给出的矩阵Horn函数的最小大小表示。虽然有各种方法来测量CNF的大小,但我们主要关注电路和电路子句的数量。我们确定了二元拟阵的最优表示的大小,并给出了均匀情况下的下界和上界。对于一致拟阵,我们展示了我们的问题和Turán系统之间的紧密联系,这些系统可能具有独立的组合兴趣。
期刊介绍:
The Journal of Combinatorial Theory publishes original mathematical research concerned with theoretical and physical aspects of the study of finite and discrete structures in all branches of science. Series A is concerned primarily with structures, designs, and applications of combinatorics and is a valuable tool for mathematicians and computer scientists.