New Hardness Results for Graph and Hypergraph Colorings

Joshua Brakensiek, V. Guruswami
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引用次数: 43

Abstract

Finding a proper coloring of a t-colorable graph G with t colors is a classic NP-hard problem when t ≥ 3. In this work, we investigate the approximate coloring problem in which the objective is to find a proper c-coloring of G where c ≥ t. We show that for all t ≥ 3, it is NP-hard to find a c-coloring when c ≤ 2t - 2. In the regime where t is small, this improves, via a unified approach, the previously best known hardness result of c ≤ max{2t - 5, t + 2⌊t/3⌋ - 1} [9, 21, 13]. For example, we show that 6-coloring a 4-colorable graph is NP-hard, improving on the NP-hardness of 5-coloring a 4-colorable graph. We also generalize this to related problems on the strong coloring of hypergraphs. A k-uniform hypergraph H is t-strong colorable (where t ≥ k) if there is a t-coloring of the vertices such that no two vertices in each hyperedge of H have the same color. We show that if t = ⌈3k/2⌉, then it is NP-hard to find a 2-coloring of the vertices of H such that no hyperedge is monochromatic. We conjecture that a similar hardness holds for t = k + 1. We establish the NP-hardness of these problems by reducing from the hardness of the Label Cover problem, via a "dictatorship test" gadget graph. By combinatorially classifying all possible colorings of this graph, we can infer labels to provide to the label cover problem. This approach generalizes the "weak polymorphism" framework of [3], though interestingly our results are "PCP-free" in that they do not require any approximation gap in the starting Label Cover instance.
图和超图着色的新硬度结果
当t≥3时,寻找具有t种颜色的t-可着色图G的适当着色是一个经典的np困难问题。本文研究了以求c≥t时G的适当c-着色为目标的近似着色问题。我们证明了当所有t≥3时,当c≤2t - 2时,找到c-着色是np困难的。在t很小的情况下,通过统一的方法,这改善了以前最著名的硬度结果c≤max{2t - 5, t + 2⌊t/3⌋- 1}[9,21,13]。例如,我们证明了一个4色图的6着色是NP-hard,提高了一个4色图的5着色的NP-hard。并将其推广到有关超图的强着色问题。一个k-均匀超图H是t强可着色的(其中t≥k),如果存在顶点的t着色使得H的每个超边中没有两个顶点具有相同的颜色。我们证明了,如果t = (3k/2),那么找到H的顶点的2-着色使得没有超边是单色的是np -困难的。我们推测,对于t = k + 1,也有类似的硬度。我们通过一个“独裁测试”小图,从标签覆盖问题的硬度降低,建立了这些问题的np -硬度。通过对该图的所有可能的着色进行组合分类,我们可以推断出标签以提供给标签覆盖问题。这种方法推广了[3]的“弱多态性”框架,尽管有趣的是,我们的结果是“无pcp”的,因为它们不需要在开始的Label Cover实例中有任何近似间隙。
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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