The Fine-Grained Complexity of Graph Homomorphism Parameterized by Clique-Width

IF 0.9 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS ACM Transactions on Algorithms Pub Date : 2024-03-25 DOI:10.1145/3652514
Robert Ganian, Thekla Hamm, Viktoriia Korchemna, Karolina Okrasa, Kirill Simonov
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Abstract

The generic homomorphism problem, which asks whether an input graph \(G\) admits a homomorphism into a fixed target graph \(H\), has been widely studied in the literature. In this article, we provide a fine-grained complexity classification of the running time of the homomorphism problem with respect to the clique-width of \(G\) (denoted \({\operatorname{cw}}\)) for virtually all choices of \(H\) under the Strong Exponential Time Hypothesis. In particular, we identify a property of \(H\) called the signature number \(s(H)\) and show that for each \(H\), the homomorphism problem can be solved in time \(\mathcal{O^{*}}(s(H)^{{\operatorname{cw}}})\). Crucially, we then show that this algorithm can be used to obtain essentially tight upper bounds. Specifically, we provide a reduction that yields matching lower bounds for each \(H\) that is either a projective core or a graph admitting a factorization with additional properties—allowing us to cover all possible target graphs under long-standing conjectures.

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以剪辑宽度为参数的图同态细粒度复杂性
通用同态问题是关于输入图 \(G\) 是否允许同态为固定目标图 \(H\) 的问题,该问题在文献中得到了广泛的研究。在本文中,我们针对强指数时间假设下几乎所有的 \(H\)选择,对同态问题的运行时间与 \(G\)的簇宽度(表示为 \({\operatorname{cw}}\))进行了精细的复杂度分类。我们特别指出了 \(H\)的一个属性,即签名数 \(s(H)\),并证明对于每个 \(H\),同态问题都可以在时间 \(\mathcal{O^{*}}(s(H)^{\operatorname{cw}})\)内求解。最重要的是,我们还证明了这种算法可以用来获得基本严密的上界。具体地说,我们提供了一种还原方法,可以为每个 \(H\) 得到匹配的下界,而这些图要么是投影核,要么是允许因子化的图,并具有额外的性质--这使得我们可以涵盖长期猜想下所有可能的目标图。
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来源期刊
ACM Transactions on Algorithms
ACM Transactions on Algorithms COMPUTER SCIENCE, THEORY & METHODS-MATHEMATICS, APPLIED
CiteScore
3.30
自引率
0.00%
发文量
50
审稿时长
6-12 weeks
期刊介绍: ACM Transactions on Algorithms welcomes submissions of original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis. Most welcome are new algorithms and data structures, new and improved analyses, and complexity results. Specific areas of computation covered by the journal include combinatorial searches and objects; counting; discrete optimization and approximation; randomization and quantum computation; parallel and distributed computation; algorithms for graphs, geometry, arithmetic, number theory, strings; on-line analysis; cryptography; coding; data compression; learning algorithms; methods of algorithmic analysis; discrete algorithms for application areas such as biology, economics, game theory, communication, computer systems and architecture, hardware design, scientific computing
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