English

A Turing Kernelization Dichotomy for Structural Parameterizations of $\mathcal{F}$-Minor-Free Deletion

Data Structures and Algorithms 2019-07-17 v2 Computational Complexity

Abstract

For a fixed finite family of graphs F\mathcal{F}, the F\mathcal{F}-Minor-Free Deletion problem takes as input a graph GG and an integer \ell and asks whether there exists a set XV(G)X \subseteq V(G) of size at most \ell such that GXG-X is F\mathcal{F}-minor-free. For F={K2}\mathcal{F}=\{K_2\} and F={K3}\mathcal{F}=\{K_3\} this encodes Vertex Cover and Feedback Vertex Set respectively. When parameterized by the feedback vertex number of GG these two problems are known to admit a polynomial kernelization. Such a polynomial kernelization also exists for any F\mathcal{F} containing a planar graph but no forests. In this paper we show that F\mathcal{F}-Minor-Free Deletion parameterized by the feedback vertex number is MK[2]-hard for F={P3}\mathcal{F} = \{P_3\}. This rules out the existence of a polynomial kernel assuming NPcoNP/polyNP \subseteq coNP/poly, and also gives evidence that the problem does not admit a polynomial Turing kernel. Our hardness result generalizes to any F\mathcal{F} not containing a P3P_3-subgraph-free graph, using as parameter the vertex-deletion distance to treewidth mintw(F)mintw(\mathcal{F}), where mintw(F)mintw(\mathcal{F}) denotes the minimum treewidth of the graphs in F\mathcal{F}. For the other case, where F\mathcal{F} contains a P3P_3-subgraph-free graph, we present a polynomial Turing kernelization. Our results extend to F\mathcal{F}-Subgraph-Free Deletion.

Keywords

Cite

@article{arxiv.1906.05565,
  title  = {A Turing Kernelization Dichotomy for Structural Parameterizations of $\mathcal{F}$-Minor-Free Deletion},
  author = {Huib Donkers and Bart M. P. Jansen},
  journal= {arXiv preprint arXiv:1906.05565},
  year   = {2019}
}
R2 v1 2026-06-23T09:52:29.352Z