Faster approximation algorithms for computing shortest cycles on weighted graphs
Guillaume Ducoffe

TL;DR
This paper introduces new faster approximation algorithms for computing the girth of weighted graphs, achieving subquadratic runtime with guarantees close to the optimal girth, a significant advancement over previous methods.
Contribution
The paper presents the first subquadratic-time approximation algorithms for girth in weighted graphs, combining novel insights with Hitting Set techniques for improved efficiency.
Findings
Deterministic 2-approximation in O(n^{5/3}+m) time
A O(n^{5/3}\u00b1 log^{O(1)}(1/psilon))-time (4+psilon)-approximation
Randomized O(n^{5/3})-time 4-approximation, derandomized for polynomial weights
Abstract
Given an -vertex -edge graph with non negative edge-weights, the girth of is the weight of a shortest cycle in . For any graph with polynomially bounded integer weights, we present a deterministic algorithm that computes, in -time, a cycle of weight at most twice the girth of . Our approach combines some new insights on the previous approximation algorithms for this problem (Lingas and Lundell, IPL'09; Roditty and Tov, TALG'13) with Hitting Set based methods that are used for approximate distance oracles and date back from (Thorup and Zwick, JACM'05). Then, we turn our algorithm into a deterministic -approximation for graphs with arbitrary non negative edge-weights, at the price of a slightly worse running-time in . Finally, if we insist in removing the…
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