Off-Diagonal Commonality of Graphs via Entropy

IF 0.9 3区 数学 Q2 MATHEMATICS
Natalie Behague, Natasha Morrison, Jonathan A. Noel
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引用次数: 0

Abstract

SIAM Journal on Discrete Mathematics, Volume 38, Issue 3, Page 2335-2360, September 2024.
Abstract. A graph [math] is common if the limit as [math] of the minimum density of monochromatic labeled copies of [math] in an edge coloring of [math] with red and blue is attained by a sequence of quasirandom colorings. We apply an information-theoretic approach to show that certain graphs obtained from odd cycles and paths via gluing operations are common. In fact, for every pair [math] of such graphs, there exists [math] such that an appropriate linear combination of red copies of [math] and blue copies of [math] is minimized by a quasirandom coloring in which [math] edges are red; such a pair [math] is said to be [math]-common. Our approach exploits a strengthening of the common graph property for odd cycles that was recently proved using Schur convexity. We also exhibit a [math]-common pair [math] such that [math] is uncommon.
通过熵实现图形的非对角共性
SIAM 离散数学杂志》,第 38 卷,第 3 期,第 2335-2360 页,2024 年 9 月。 摘要。如果一个图[math]的红蓝边着色中[math]的单色标注副本的最小密度的极限是通过一连串的准随机着色达到的,那么这个图[math]就是常见的。我们运用信息论的方法证明,通过胶合操作从奇数循环和路径得到的某些图形是常见的。事实上,对于每一对[math]这样的图,都存在这样的[math],即[math]的红色副本和[math]的蓝色副本的适当线性组合通过准随机着色最小化,其中[math]的边是红色的;这样的一对[math]被称为[math]共同图。我们的方法利用了最近用舒尔凸性证明的奇数循环共用图属性的强化。我们还展示了一对[math]-common 的[math],这样的[math]是不常见的。
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
124
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Discrete Mathematics (SIDMA) publishes research papers of exceptional quality in pure and applied discrete mathematics, broadly interpreted. The journal''s focus is primarily theoretical rather than empirical, but the editors welcome papers that evolve from or have potential application to real-world problems. Submissions must be clearly written and make a significant contribution. Topics include but are not limited to: properties of and extremal problems for discrete structures combinatorial optimization, including approximation algorithms algebraic and enumerative combinatorics coding and information theory additive, analytic combinatorics and number theory combinatorial matrix theory and spectral graph theory design and analysis of algorithms for discrete structures discrete problems in computational complexity discrete and computational geometry discrete methods in computational biology, and bioinformatics probabilistic methods and randomized algorithms.
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