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Everything you always wanted to know about the parameterized complexity of Subgraph Isomorphism (but were afraid to ask)

机译:你一直想知道关于subgraph Isomorphism的参数化复杂性的一切(但不敢问)

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摘要

Given two graphs H and G, the Subgraph Isomorphism problem asks if H is isomorphic to a subgraph of G. While NP-hard in general, algorithms exist for various parameterized versions of the problem. However, the literature contains very little guidance on which combinations of parameters can or cannot be exploited algorithmically. Our goal is to systematically investigate the possible parameterized algorithms that can exist for Subgraph Isomorphism.We develop a framework involving 10 relevant parameters for each of H and G (such as treewidth, pathwidth, genus, maximum degree, number of vertices, number of components, etc.), and ask if an algorithm with running time f1_(p_1,p_2,...,p_l).n^f_2(p_(l+1),...,p_k) exists, where each of p_1,...,p_k is one of the 10 parameters depending only on H or G. We show that all the questions arising in this framework are answered by a set of 11 maximal positive results (algorithms) and a set of 17 maximal negative results (hardness proofs); some of these results already appear in the literature, while others are new in this paper.On the algorithmic side, our study reveals for example that an unexpected combination of bounded degree, genus, and feedback vertex set number of G gives rise to a highly nontrivial algorithm for Subgraph Isomorphism. On the hardness side, we present W[1]-hardness proofs under extremely restricted conditions, such as when H is a bounded-degree tree of constant pathwidth and G is a planar graph of bounded pathwidth.
机译:给定两个图H和G,子图同构问题询问H是否与G的子图同构。尽管NP-hard通常是困难的,但存在针对该问题的各种参数版本的算法。但是,文献中很少有关于哪些参数组合可以或不能通过算法利用的指南。我们的目标是系统地研究可能存在于子图同构的参数化算法。我们开发了一个框架,该框架涉及H和G的10个相关参数(例如树宽,路径宽度,属,最大程度,顶点数量,组件数量)等),并询问是否存在运行时间为f1_(p_1,p_2,...,p_l).n ^ f_2(p_(l + 1),...,p_k)的算法,其中每个p_1, ...,p_k是仅取决于H或G的10个参数之一。我们证明,在此框架中出现的所有问题均由一组11个最大正结果(算法)和一组17个最大负结果(硬度证明);其中一些结果已经出现在文献中,而另一些则是本文中的新内​​容。例如,在算法方面,我们的研究表明,G的有界度,类和反馈顶点集数量的意外组合会产生很高的结果。子图同构的非平凡算法。在硬度方面,我们给出了在极端受限条件下的W [1]硬度证明,例如H是恒定路径宽度的有界度树,而G是有路径宽度的平面图。

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