Path Contraction Faster than $2^n$

TL;DR

This paper presents a faster exact exponential time algorithm for the Path Contraction problem, improving the runtime from 2^n to approximately 1.99987^n, and introduces a related algorithm for 3-Disjoint Connected Subgraphs.

Contribution

It introduces a significantly improved exponential time algorithm for Path Contraction and a new algorithm for 3-Disjoint Connected Subgraphs, using the latter as a sub-routine.

Findings

Path Contraction algorithm runs in 1.99987^n time.

New algorithm for 3-Disjoint Connected Subgraphs runs in 1.88^n time.

Faster algorithms demonstrate progress in exponential time complexity for graph contraction problems.

Abstract

A graph $G$ is contractible to a graph $H$ if there is a set $X \subseteq E(G)$, such that $G/X$ is isomorphic to $H$. Here, $G/X$ is the graph obtained from $G$ by contracting all the edges in $X$. For a family of graphs $\cal F$, the $\mathcal{F}$-\textsc{Contraction} problem takes as input a graph $G$ on $n$ vertices, and the objective is to output the largest integer $t$, such that $G$ is contractible to a graph $H \in {\cal F}$, where $|V(H)|=t$. When $\cal F$ is the family of paths, then the corresponding $\mathcal{F}$-\textsc{Contraction} problem is called \textsc{Path Contraction}. The problem \textsc{Path Contraction} admits a simple algorithm running in time $2^{n}\cdot n^{\mathcal{O}(1)}$. In spite of the deceptive simplicity of the problem, beating the $2^{n}\cdot n^{\mathcal{O}(1)}$ bound for \textsc{Path Contraction} seems quite challenging. In this paper, we design an exact exponential time algorithm for \textsc{Path Contraction} that runs in time $1.99987^n\cdot n^{\mathcal{O}(1)}$. We also define a problem called \textsc{$3$-Disjoint Connected Subgraphs}, and design an algorithm for it that runs in time $1.88^n\cdot n^{\mathcal{O}(1)}$. The above algorithm is used as a sub-routine in our algorithm for {\sc Path Contraction}