English

Gromov's Approximating Tree and the All-Pairs Bottleneck Paths Problem

Computational Geometry 2025-09-30 v2 Computational Complexity Discrete Mathematics Combinatorics Optimization and Control

Abstract

Given a pointed metric space (X,dist,w)(X,\mathsf{dist}, w) on nn points, its Gromov's approximating tree is a 0-hyperbolic pseudo-metric space (X,distT)(X,\mathsf{dist}_T) such that dist(x,w)=distT(x,w)\mathsf{dist}(x,w)=\mathsf{dist}_T(x,w) and dist(x,y)2δlog2ndistT(x,y)dist(x,y)\mathsf{dist}(x, y)-2 \delta \log_2n \leq \mathsf{dist}_T (x, y) \leq \mathsf{dist}(x, y) for all x,yXx, y \in X where δ\delta is the Gromov hyperbolicity of XX. On the other hand, the all pairs bottleneck paths (APBP) problem asks, given an undirected graph with some capacities on its edges, to find the maximal path capacity between each pair of vertices. In this note, we prove: \bullet Computing Gromov's approximating tree for a metric space with n+1n+1 points from its matrix of distances reduces to solving the APBP problem on an connected graph with nn vertices. \bullet There is an explicit algorithm that computes Gromov's approximating tree for a graph from its adjacency matrix in quadratic time. \bullet Solving the APBP problem on a weighted graph with nn vertices reduces to finding Gromov's approximating tree for a metric space with n+1n+1 points from its distance matrix.

Keywords

Cite

@article{arxiv.2408.05338,
  title  = {Gromov's Approximating Tree and the All-Pairs Bottleneck Paths Problem},
  author = {Anders Cornect and Eduardo Martínez-Pedroza},
  journal= {arXiv preprint arXiv:2408.05338},
  year   = {2025}
}

Comments

Version 2. Minor corrections

R2 v1 2026-06-28T18:09:04.925Z