On the Parameterized Approximability of Contraction to Classes of Chordal Graphs

06/18/2020 ∙ by Spoorthy Gunda, et al. ∙ 0

A graph operation that contracts edges is one of the fundamental operations in the theory of graph minors. Parameterized Complexity of editing to a family of graphs by contracting k edges has recently gained substantial scientific attention, and several new results have been obtained. Some important families of graphs, namely the subfamilies of chordal graphs, in the context of edge contractions, have proven to be significantly difficult than one might expect. In this paper, we study the F-Contraction problem, where F is a subfamily of chordal graphs, in the realm of parameterized approximation. Formally, given a graph G and an integer k, F-Contraction asks whether there exists X ⊆ E(G) such that G/X ∈ F and |X| ≤ k. Here, G/X is the graph obtained from G by contracting edges in X. We obtain the following results for the F-Contraction problem. (1) We show that Clique Contraction admits a polynomial-size approximate kernelization scheme (PSAKS). (2) We give a (2+ϵ)-approximate polynomial kernel for Split Contraction (which also implies a factor (2+ϵ)--approximation algorithm for Split Contraction). Furthermore, we show that, assuming Gap-ETH, there is no (5/4-δ)--approximation algorithm for Split Contraction. Here, ϵ, δ>0 are fixed constants. (3) Chordal Contraction is known to be . We complement this result by observing that the existing W[2]-hardness reduction can be adapted to show that, assuming ≠ W[1], there is no F(k)--approximation algorithm for Chordal Contraction. Here, F(k) is an arbitrary function depending on k alone.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.