Optimal Bounds for the k-cut Problem

Anupam Gupta, David G. Harris, Euiwoong Lee, Jason Li

Research output: Contribution to journalArticlepeer-review


In the k-cut problem, we want to find the lowest-weight set of edges whose deletion breaks a given (multi)graph into k connected components. Algorithms of Karger and Stein can solve this in roughly O(n2k) time. However, lower bounds from conjectures about the k-clique problem imply that ω (n(1-o(1))k) time is likely needed. Recent results of Gupta, Lee, and Li have given new algorithms for general k-cut in n1.98k + O(1) time, as well as specialized algorithms with better performance for certain classes of graphs (e.g., for small integer edge weights).In this work, we resolve the problem for general graphs. We show that the Contraction Algorithm of Karger outputs any fixed k-cut of weight α λ k with probability ωk(n-α k), where λ k denotes the minimum k-cut weight. This also gives an extremal bound of Ok(nk) on the number of minimum k-cuts and an algorithm to compute λ k with roughly nk polylog(n) runtime. Both are tight up to lower-order factors, with the algorithmic lower bound assuming hardness of max-weight k-clique.The first main ingredient in our result is an extremal bound on the number of cuts of weight less than 2 λk/k, using the Sunflower lemma. The second ingredient is a fine-grained analysis of how the graph shrinks - and how the average degree evolves - in the Karger process.

Original languageEnglish (US)
Article number2
JournalJournal of the ACM
Issue number1
StatePublished - Feb 2022


  • contraction algorithm
  • k-cut

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Hardware and Architecture
  • Artificial Intelligence


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