Parameterized complexity of the f-Critical Set problem

TL;DR

This paper studies the computational complexity of the f-Critical Set problem in graphs, proving NP-completeness, W[1]-hardness, and fixed-parameter tractability results, along with kernelization bounds.

Contribution

It establishes complexity classifications for the f-Critical Set problem, including NP-completeness, W[1]-hardness, FPT algorithms, and kernelization results.

Findings

NP-complete for planar subcubic bipartite graphs with max threshold 2

W[1]-hard when parameterized by treewidth

FPT algorithms for combined parameters and kernelization results

Abstract

Given a graph $G=(V,E)$, and a function $f:V(G) \rightarrow \mathbb{N}$, an $f$-reversible process on $G$ is a dynamical system such that, given an initial vertex labeling $c_0 : V(G) \rightarrow \{0,1\}$, every vertex $v$ changes its label if and only if it has at least $f(v)$ neighbors with the opposite label. The updates occur synchronously in discrete time steps $t=0,1,2,\ldots$. An $f$-critical set of $G$ is a subset of vertices of $G$ whose initial label is $1$ such that, in an $f$-reversible process on $G$, all vertices reach label $1$ within one time step and then remain unchanged. The critical set number $r^c_f(G)$ is the minimum size of an $f$-critical set of $G$. Given a graph $G$, a threshold function $f$, and an integer $k$, the $f$-Critical Set problem asks whether $r^c_f(G) \leq k$. We prove that this problem is NP-complete for planar subcubic bipartite graphs with maximum threshold $m(f) = 2$ and W[1]-hard when parameterized by the treewidth $tw(G)$ of $G$. Additionally, we show that the problem is FPT when parameterized by $tw(G)+m(f)$, $tw(G)+\Delta(G)$, and $k$, where $\Delta(G)$ denotes the maximum degree of $G$. Finally, we present two kernels of sizes $O(k \cdot m(f))$ and $O(k \cdot \Delta(G))$.