稀疏图的缺陷性和聚类选择性

Kevin Hendrey, D. Wood
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引用次数: 11

摘要

摘要(不正确的)图着色如果每个单色子图最多有d个最大度,则存在缺陷d;如果每个单色分量最多有c个顶点,则存在聚类c。研究了具有最大平均度的图的缺陷列表着色和聚类列表着色问题。我们证明了每个最大平均度小于(2d+2)/(d+2)k的图都是具有缺陷d的k-可选图。这改进了Havet和Sereni (J. graph Theory, 2006)的类似结果。对于最大平均度为m的图的聚类选择性,以前不知道颜色数目的(1- ~ ~)m界。上面d=1的结果解决了这个问题。这意味着每一个最大平均度为m的图$\lfloor{\frac{3}{4}m+1}\rfloor$-可选择聚类2。这扩展了Kopreski和Yu(离散数学)的结果。, 2017)到可选择性的设置。然后,我们证明了两个关于聚类选择性的结果,探索了颜色数量和聚类之间的权衡。特别地,我们证明了每一个最大平均度为m的图在聚类为9时是$\lfloor{\frac{7}{10}m+1}\rfloor$-可选的,在聚类为O(m)时是$\lfloor{\frac{2}{3}m+1}\rfloor$-可选的。作为一个例子,后面的结果表明,每一个双平面图是8-可选择的有界聚类。这是地球-月球问题的集群版本中最著名的结果。结果扩展到我们只考虑具有至少若干个顶点的子图的最大平均度的设置。介绍了几种应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defective and clustered choosability of sparse graphs
Abstract An (improper) graph colouring has defect d if each monochromatic subgraph has maximum degree at most d, and has clustering c if each monochromatic component has at most c vertices. This paper studies defective and clustered list-colourings for graphs with given maximum average degree. We prove that every graph with maximum average degree less than (2d+2)/(d+2)k is k-choosable with defect d. This improves upon a similar result by Havet and Sereni (J. Graph Theory, 2006). For clustered choosability of graphs with maximum average degree m, no (1-ɛ)m bound on the number of colours was previously known. The above result with d=1 solves this problem. It implies that every graph with maximum average degree m is $\lfloor{\frac{3}{4}m+1}\rfloor$-choosable with clustering 2. This extends a result of Kopreski and Yu (Discrete Math., 2017) to the setting of choosability. We then prove two results about clustered choosability that explore the trade-off between the number of colours and the clustering. In particular, we prove that every graph with maximum average degree m is $\lfloor{\frac{7}{10}m+1}\rfloor$-choosable with clustering 9, and is $\lfloor{\frac{2}{3}m+1}\rfloor$-choosable with clustering O(m). As an example, the later result implies that every biplanar graph is 8-choosable with bounded clustering. This is the best known result for the clustered version of the earth–moon problem. The results extend to the setting where we only consider the maximum average degree of subgraphs with at least some number of vertices. Several applications are presented.
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