• Media type: E-Article
  • Title: Flow-augmentation II: Undirected Graphs
  • Contributor: Kim, Eun Jung; Kratsch, Stefan; Pilipczuk, Marcin; Wahlström, Magnus
  • imprint: Association for Computing Machinery (ACM), 2024
  • Published in: ACM Transactions on Algorithms
  • Language: English
  • DOI: 10.1145/3641105
  • ISSN: 1549-6325; 1549-6333
  • Keywords: Mathematics (miscellaneous)
  • Origination:
  • Footnote:
  • Description: <jats:p> We present an undirected version of the recently introduced <jats:italic>flow-augmentation</jats:italic> technique: Given an undirected multigraph <jats:italic>G</jats:italic> with distinguished vertices <jats:italic>s,t ∈ V(G)</jats:italic> and an integer <jats:italic>k</jats:italic> , one can in randomized <jats:italic>k</jats:italic> <jats:sup>𝒪(1)</jats:sup> ⋅ <jats:italic>(|V(G)| + |E(G)|)</jats:italic> time sample a set <jats:italic>A</jats:italic> ⊆ <jats:inline-formula content-type="math/tex"> <jats:tex-math notation="LaTeX" version="MathJax">\(\binom{V(G)}{2}\)</jats:tex-math> </jats:inline-formula> such that the following holds: for every inclusion-wise minimal <jats:italic>st</jats:italic> -cut <jats:italic>Z</jats:italic> in <jats:italic>G</jats:italic> of cardinality at most <jats:italic>k</jats:italic> , <jats:italic>Z</jats:italic> becomes a <jats:italic>minimum-cardinality</jats:italic> cut between <jats:italic>s</jats:italic> and <jats:italic>t</jats:italic> in <jats:italic>G+A</jats:italic> (i.e., in the multigraph <jats:italic>G</jats:italic> with all edges of <jats:italic>A</jats:italic> added) with probability 2 <jats:sup> -𝒪( <jats:italic>k</jats:italic> log <jats:italic>k</jats:italic> </jats:sup> ). </jats:p> <jats:p> Compared to the version for directed graphs [STOC 2022], the version presented here has improved success probability (2 <jats:sup> -𝒪( <jats:italic>k</jats:italic> log <jats:italic>k</jats:italic> </jats:sup> ) instead of 2 <jats:sup> -𝒪( <jats:italic> k <jats:sup>4</jats:sup> </jats:italic> log <jats:italic>k</jats:italic> ) </jats:sup> ), linear dependency on the graph size in the running time bound, and an arguably simpler proof. </jats:p> <jats:p> An immediate corollary is that the <jats:sc> Bi-objective <jats:italic>st</jats:italic> -Cut </jats:sc> problem can be solved in randomized FPT time 2 <jats:sup> 𝒪( <jats:italic>k</jats:italic> log <jats:italic>k</jats:italic> ) </jats:sup> <jats:italic>(|V(G)|+|E(G)|)</jats:italic> on undirected graphs. </jats:p>