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Vertex Connectivity in Poly-logarithmic Max-Flows

  • Jason Li
  • , Danupon Nanongkai
  • , Debmalya Panigrahi
  • , Thatchaphol Saranurak
  • , Sorrachai Yingchareonthawornchai
  • Carnegie Mellon University
  • KTH Royal Institute of Technology
  • University of Copenhagen
  • Max Planck Institute for Informatics
  • Duke University
  • University of Michigan, Ann Arbor
  • Swiss Federal Institute of Technology Zurich

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
3 Downloads (Pure)

Abstract

The vertex connectivity of an m-edge n-vertex undirected graph is the smallest number of vertices whose removal disconnects the graph or leaves only a singleton vertex. In 1974, Aho Hopcroft and Ullman asked if vertex connectivity can be computed in linear time. Despite the substantial effort in the past five decades, the best-known running time is Õ(mn) by Henzinger-Rao-Gabow (FOCS 1996). Indeed, no algorithm with an o(mn) running time is known even if we assume a linear-time max-flow algorithm. In this article, we give an affirmative answer to this long-standing open problem (up to a sub-polynomial factor). We present a randomized reduction from the vertex connectivity problem to the max-flow problem which incurs only a poly-logarithmic overhead in runtime. Using this reduction, we can solve vertex connectivity in almost linear time by using the celebrated almost-linear-time max-flow algorithms by Chen-Kyng-Liu-Peng-Probst Gutenberg-Sachdeva (FOCS 2022) and Brand-Chen-Kyng-Liu-Peng-Probst Gutenberg-Sachdeva-Sidford (FOCS 2023). Using our new techniques, we also obtain an algorithm for directed vertex connectivity with a running time of n2+o(1) time which improves the best-known bound of Õ(mn) by Henzinger-Rao-Gabow (FOCS 1996).

Original languageEnglish
Article number28
Pages (from-to)1-34
Number of pages34
JournalJournal of the ACM
Volume72
Issue number4
DOIs
Publication statusPublished - 25 Jul 2025
MoE publication typeA1 Journal article-refereed

Funding

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 715672 and No. 759557. Nanongkai was also partially supported by the Swedish Research Council (Reg. No. 2019-05622). Panigrahi has been supported in part by NSF Awards CCF 1750140 and CCF 1955703. Saranurak is supported by NSF Grant CCF 2238138.

Keywords

  • Algorithmic graph theory
  • vertex connectivity

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