On the Parallel Complexity of Finding a Matroid Basis
Sanjeev Khanna, Aaron Putterman, Junkai Song

TL;DR
This paper advances the understanding of parallel algorithms for matroid basis problems by introducing a new algorithm that reduces the number of rounds needed, improving over previous bounds and settling the complexity for partition matroids.
Contribution
It presents the first algorithm to find a matroid basis in fewer than O(√n) rounds, using novel decomposition techniques, and determines the exact complexity for partition matroids.
Findings
New algorithm finds matroid basis in rac{n^{7/15}}{} rounds.
Achieves rac{n^{1/3}}{} rounds for partition matroids.
Surpasses the longstanding O(rac{rac{n}{}}) barrier.
Abstract
A fundamental question in parallel computation, posed by Karp, Upfal, and Wigderson (FOCS 1985, JCSS 1988), asks: \emph{given only independence-oracle access to a matroid on elements, how many rounds are required to find a basis using only polynomially many queries?} This question generalizes, among others, the complexity of finding bases of linear spaces, partition matroids, and spanning forests in graphs. In their work, they established an upper bound of rounds and a lower bound of rounds for this problem, and these bounds have remained unimproved since then. In this work, we make the first progress in narrowing this gap by designing a parallel algorithm that finds a basis of an arbitrary matroid in rounds (using polynomially many independence queries per round) with high probability, surpassing the long-standing…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Computational Geometry and Mesh Generation
