Recognizing and realizing cactus metrics

TL;DR

This paper introduces cactus metrics, a new class of metrics realizable by cactus graphs, and provides an algorithm to recognize and compute their optimal realizations efficiently.

Contribution

It defines cactus metrics, proves their unique optimal realization, and presents an $O(n^3)$ recognition and realization algorithm.

Findings

Cactus metrics have unique optimal realizations.

An $O(n^3)$ algorithm can recognize and realize cactus metrics.

Cactus metrics generalize tree metrics for more complex data modeling.

Abstract

The problem of realizing finite metric spaces in terms of weighted graphs has many applications. For example, the mathematical and computational properties of metrics that can be realized by trees have been well-studied and such research has laid the foundation of the reconstruction of phylogenetic trees from evolutionary distances. However, as trees may be too restrictive to accurately represent real-world data or phenomena, it is important to understand the relationship between more general graphs and distances. In this paper, we introduce a new type of metric called a cactus metric, that is, a metric that can be realized by a cactus graph. We show that, just as with tree metrics, a cactus metric has a unique optimal realization. In addition, we describe an algorithm that can recognize whether or not a metric is a cactus metric and, if so, compute its optimal realization in $O(n^3)$ time, where $n$ is the number of points in the space.