Removal lemmas and approximate homomorphisms

IF 0.9 4区 数学 Q3 COMPUTER SCIENCE, THEORY & METHODS Combinatorics, Probability & Computing Pub Date : 2021-04-23 DOI:10.1017/s0963548321000572
J. Fox, Yufei Zhao
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引用次数: 1

Abstract

We study quantitative relationships between the triangle removal lemma and several of its variants. One such variant, which we call the triangle-free lemma, states that for each $\epsilon>0$ there exists M such that every triangle-free graph G has an $\epsilon$ -approximate homomorphism to a triangle-free graph F on at most M vertices (here an $\epsilon$ -approximate homomorphism is a map $V(G) \to V(F)$ where all but at most $\epsilon \left\lvert{V(G)}\right\rvert^2$ edges of G are mapped to edges of F). One consequence of our results is that the least possible M in the triangle-free lemma grows faster than exponential in any polynomial in $\epsilon^{-1}$ . We also prove more general results for arbitrary graphs, as well as arithmetic analogues over finite fields, where the bounds are close to optimal.
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去除引理与近似同态
我们研究了三角形去除引理和它的几个变体之间的定量关系。其中一种变体,我们称之为无三角引理,说明对于每个$\epsilon>0$存在M,使得每个无三角形图G在最多M个顶点上与无三角形图F具有$\epsilon$ -近似同态(这里的$\epsilon$ -近似同态是一个映射$V(G) \to V(F)$,其中G的除最多$\epsilon \left\lvert{V(G)}\right\rvert^2$边外的所有边都映射到F的边)。我们的结果的一个结果是,在无三角形引论中,最小可能的M比任何多项式中的指数增长更快在$\epsilon^{-1}$。我们还证明了任意图的更一般的结果,以及有限域上的算术类似,其中边界接近最优。
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来源期刊
Combinatorics, Probability & Computing
Combinatorics, Probability & Computing 数学-计算机:理论方法
CiteScore
2.40
自引率
11.10%
发文量
33
审稿时长
6-12 weeks
期刊介绍: Published bimonthly, Combinatorics, Probability & Computing is devoted to the three areas of combinatorics, probability theory and theoretical computer science. Topics covered include classical and algebraic graph theory, extremal set theory, matroid theory, probabilistic methods and random combinatorial structures; combinatorial probability and limit theorems for random combinatorial structures; the theory of algorithms (including complexity theory), randomised algorithms, probabilistic analysis of algorithms, computational learning theory and optimisation.
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