Journal of Computer and System Sciences ( IF 1.1 ) Pub Date : 2021-03-03 , DOI: 10.1016/j.jcss.2021.02.005 Huib Donkers , Bart M.P. Jansen
For a fixed finite family of graphs , the -Minor-Free Deletion problem takes as input a graph G and integer ℓ and asks whether a size-ℓ vertex set X exists such that is -minor-free. -Minor-Free Deletion and -Minor-Free Deletion encode Vertex Cover and Feedback Vertex Set respectively. When parameterized by the feedback vertex number of G these two problems are known to admit a polynomial kernelization. We show -Minor-Free Deletion parameterized by the feedback vertex number is -hard. This rules out the existence of a polynomial kernel assuming . Our hardness result generalizes to any containing only graphs with a connected component of at least 3 vertices, using as parameter the vertex-deletion distance to treewidth , where denotes the minimum treewidth of the graphs in . For all other families we present a polynomial Turing kernelization. Our results extend to -Subgraph-Free Deletion.
中文翻译:
图灵核化二分法用于结构的参数化 -次要删除
对于固定的有限图族 , 这 -Minor免费缺失问题作为输入的曲线图G ^和整数ℓ并询问一个大小-是否ℓ顶点集合X存在,使得 是 -次要的。 -次要删除和-次要-自由删除分别对“顶点覆盖”和“反馈顶点集”进行编码。当由G的反馈顶点数进行参数化时,这两个问题已知可以进行多项式核化。我们展示由反馈顶点编号参数化的-次要-自由删除为-难的。这排除了多项式内核的存在。我们的硬度结果可以推广到任何 仅包含具有至少3个顶点的连通分量的图,并使用到树宽的顶点删除距离作为参数 , 在哪里 表示图中的最小树宽 。对于其他所有家庭我们提出了多项式图灵核化。我们的结果扩展到-Subgraph-Free删除。