A Turing Kernelization Dichotomy for Structural Parameterizations of $\mathcal{F}$-Minor-Free Deletion
Huib Donkers, Bart M.P. Jansen

TL;DR
This paper establishes a dichotomy in kernelization complexity for the -Minor-Free Deletion problem based on the structure of and related graph parameters, showing hardness results and polynomial Turing kernels.
Contribution
It proves -Minor-Free Deletion is MK[2]-hard for certain , and provides polynomial Turing kernels for others, extending the understanding of kernelization boundaries.
Findings
-Minor-Free Deletion is MK[2]-hard for =
Polynomial Turing kernels exist when contains a P3-subgraph-free graph
Hardness results extend to -Subgraph-Free Deletion
Abstract
For a fixed finite family of graphs , the -Minor-Free Deletion problem takes as input a graph and an integer and asks whether there exists a set of size at most such that is -minor-free. For and this encodes Vertex Cover and Feedback Vertex Set respectively. When parameterized by the feedback vertex number of these two problems are known to admit a polynomial kernelization. Such a polynomial kernelization also exists for any containing a planar graph but no forests. In this paper we show that -Minor-Free Deletion parameterized by the feedback vertex number is MK[2]-hard for . This rules out the existence of a polynomial kernel assuming , and also gives evidence that the problem does not…
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