Three-in-a-Tree in Near Linear Time

TL;DR

This paper presents a near-linear time algorithm for the three-in-a-tree problem, significantly improving the efficiency of detecting specific induced subgraphs in graphs, with implications for graph recognition tasks.

Contribution

It introduces a new, stronger characterization of the problem, enabling an $ ilde{O}(m)$ time algorithm that surpasses previous polynomial-time solutions.

Findings

Achieved near-linear time complexity for the three-in-a-tree problem.

Enabled faster algorithms for recognizing perfect graphs and detecting specific subgraphs.

Provided a simpler proof of the original characterization.

Abstract

The three-in-a-tree problem is to determine if a simple undirected graph contains an induced subgraph which is a tree connecting three given vertices. Based on a beautiful characterization that is proved in more than twenty pages, Chudnovsky and Seymour [Combinatorica 2010] gave the previously only known polynomial-time algorithm, running in $O(mn^2)$ time, to solve the three-in-a-tree problem on an $n$-vertex $m$-edge graph. Their three-in-a-tree algorithm has become a critical subroutine in several state-of-the-art graph recognition and detection algorithms. In this paper we solve the three-in-a-tree problem in $\tilde{O}(m)$ time, leading to improved algorithms for recognizing perfect graphs and detecting thetas, pyramids, beetles, and odd and even holes. Our result is based on a new and more constructive characterization than that of Chudnovsky and Seymour. Our new characterization is stronger than the original, and our proof implies a new simpler proof for the original characterization. The improved characterization gains the first factor $n$ in speed. The remaining improvement is based on dynamic graph algorithms.