Faster Algorithms for Global Minimum Vertex-Cut in Directed Graphs
Julia Chuzhoy, Ron Mosenzon, Ohad Trabelsi

TL;DR
This paper introduces faster randomized algorithms for the directed global minimum vertex-cut problem, breaking the long-standing $ ilde{O}(mn)$ time barrier and significantly improving computational efficiency.
Contribution
It presents the first algorithm to surpass the $ ilde{O}(mn)$ time for directed vertex cuts, achieving $O(mn^{0.976} ext{polylog} W)$ time, and offers a new efficient solution for the unweighted case.
Findings
Breaks the $ ilde{O}(mn)$ time barrier for directed vertex cuts.
Provides a randomized algorithm with $O(mn^{0.976} ext{polylog} W)$ running time.
Offers an efficient unweighted case algorithm with $O( ext{min}igrace m^{1+o(1)} ext{·}k, n^{2+o(1)}igrace)$ complexity.
Abstract
We study the directed global minimum vertex-cut problem: given a directed vertex-weighted graph , compute a vertex-cut in of minimum value, which is defined to be the total weight of all vertices in . The problem, together with its edge-based variant, is one of the most basic in graph theory and algorithms, and has been studied extensively. The fastest currently known algorithm for directed global minimum vertex-cut (Henzinger, Rao and Gabow, FOCS 1996 and J. Algorithms 2000) has running time , where and denote the number of edges and vertices in the input graph, respectively. A long line of work over the past decades led to faster algorithms for other main versions of the problem, including the undirected edge-based setting (Karger, STOC 1996 and J. ACM 2000), directed edge-based setting (Cen et al., FOCS 2021), and undirected vertex-based…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Stochastic Gradient Optimization Techniques
