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  1. Home > Articles & Issues >
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  3. Minimum Stable Cut a ...
Article

Minimum Stable Cut and Treewidth

Michael Lampis (1)
(1) Lamsade
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Open on arXiv
Submitted on
February 2, 2023
Accepted on
March 9, 2026
Published on
April 7, 2026
Last modified on
April 7, 2026
Volume 28
vol. 28:2
Discrete Algorithms
DOI
10.46298/dmtcs.10900
License
arXiv.org - Non-exclusive license to distribute
French National Research Agency (ANR)
ANR-18-CE40-0025
Algorithms with Small Separations acKnowledged: graphs and linear matroids
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334
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381
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Minimum Stable Cut and Treewidth

Michael Lampis (1)
(1) Lamsade
Abstract
A stable or locally-optimal cut of a graph is a cut whose weight cannot be increased by changing the side of a single vertex. In this paper we study Minimum Stable Cut, the problem of finding a stable cut of minimum weight. Since this problem is NP-hard, we study its complexity on graphs of low treewidth, low degree, or both. We begin by showing that the problem remains weakly NP-hard on severely restricted trees, so bounding treewidth alone cannot make it tractable. We match this hardness with a pseudo-polynomial DP algorithm solving the problem in time $(Δ\cdot W)^{O(tw)}n^{O(1)}$, where $tw$ is the treewidth, $Δ$ the maximum degree, and $W$ the maximum weight. On the other hand, bounding $Δ$ is also not enough, as the problem is NP-hard for unweighted graphs of bounded degree. We therefore parameterize Minimum Stable Cut by both $tw$ and $Δ$ and obtain an FPT algorithm running in time $2^{O(Δtw)}(n+\log W)^{O(1)}$. Our main result for the weighted problem is to provide a reduction showing that both aforementioned algorithms are essentially optimal, even if we replace treewidth by pathwidth: if there exists an algorithm running in $(nW)^{o(pw)}$ or $2^{o(Δpw)}(n+\log W)^{O(1)}$, then the ETH is false. Complementing this, we show that we can, however, obtain an FPT approximation scheme parameterized by treewidth, if we consider almost-stable solutions, that is, solutions where no single vertex can unilaterally increase the weight of its incident cut edges by more than a factor of $(1+\varepsilon)$. Motivated by these mostly negative results, we consider Unweighted Minimum Stable Cut. Here our results already imply a much faster exact algorithm running in time $Δ^{O(tw)}n^{O(1)}$. We show that this is also probably essentially optimal: an algorithm running in $n^{o(pw)}$ would contradict the ETH. Full version of ICALP 2021 paper
Keywords
  • Computational Complexity
  • Data Structures and Algorithms
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