Near-Optimal Spanners for General Graphs in (Nearly) Linear Time
Hung Le, Shay Solomon

TL;DR
This paper introduces near-linear time algorithms for constructing sparse, light, and near-optimal spanners in weighted graphs, improving efficiency over previous methods while maintaining near-optimal sparsity and lightness.
Contribution
The paper presents deterministic algorithms for constructing near-optimal spanners with improved runtime in both pointer-machine and WORD RAM models, advancing the state-of-the-art in spanner construction.
Findings
Algorithms achieve near-optimal sparsity and lightness.
Runtime improvements over previous methods.
Deterministic algorithms in different computational models.
Abstract
Let be a weighted undirected graph on vertices and edges, let be any integer, and let be any parameter. We present the following results on fast constructions of spanners with near-optimal sparsity and lightness, which culminate a long line of work in this area. (By near-optimal we mean optimal under Erd\H{o}s' girth conjecture and disregarding the -dependencies.) - There are (deterministic) algorithms for constructing -spanners for with a near-optimal sparsity of . The first algorithm can be implemented in the pointer-machine model within time , where is the two-parameter inverse-Ackermann function and is the time needed to sort integers. The second algorithm can be…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Drug Transport and Resistance Mechanisms
