Cut-Equivalent Trees are Optimal for Min-Cut Queries
Amir Abboud, Robert Krauthgamer, Ohad Trabelsi

TL;DR
This paper proves that cut-equivalent trees are essentially optimal for min-cut queries, establishing near-linear time construction equivalence and introducing robust approximation techniques that improve max-flow computations.
Contribution
The paper shows the equivalence between near-linear time construction of cut-equivalent trees and efficient min-cut query data structures, and introduces approximation methods for faster max-flow algorithms.
Findings
Cut-equivalent trees can be constructed in near-linear time if and only if efficient min-cut query data structures exist.
A $(1+ ext{epsilon})$-approximate flow-equivalent tree can be built in $n^{2+o(1)}$ time using approximation algorithms.
This leads to the first near-quadratic time $(1+ ext{epsilon})$-approximate All-Pairs Max-Flow algorithm.
Abstract
Min-Cut queries are fundamental: Preprocess an undirected edge-weighted graph, to quickly report a minimum-weight cut that separates a query pair of nodes . The best data structure known for this problem simply builds a cut-equivalent tree, discovered 60 years ago by Gomory and Hu, who also showed how to construct it using minimum -cut computations. Using state-of-the-art algorithms for minimum -cut (Lee and Sidford, FOCS 2014) arXiv:1312.6713, one can construct the tree in time , which is also the preprocessing time of the data structure. (Throughout, we focus on polynomially-bounded edge weights, noting that faster algorithms are known for small/unit edge weights.) Our main result shows the following equivalence: Cut-equivalent trees can be constructed in near-linear time if and only if there is a data structure for Min-Cut queries with…
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