Near-optimal approximation algorithm for simultaneous Max-cut

Amey Bhangale, Subhash Khot, Swastik Kopparty, Sushant Sachdeva, Devanathan Thiruvenkatachari

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In the simultaneous Max-Cut problem, we are given k weighted graphs on the same set of n vertices, and the goal is to find a cut of the vertex set so that the minimum, over the k graphs, of the cut value is as large as possible. Previous work [BKS15] gave a polynomial time algorithm which achieved an approximation factor of 1-2- op1q for this problem (and an approximation factor of 1-2 + ϵk in the unweighted case, where "k Ñ 0 as k Ñ 8). In this work, we give a polynomial time approximation algorithm for simultaneous Max-Cut with an approximation factor of 0:8780 (for all constant k). The natural SDP formulation for simultaneous Max-Cut was shown to have an integrality gap of 1-2+ϵk in [BKS15]. In achieving the better approximation guarantee, we use a stronger Sum-of-Squares hierarchy SDP relaxation and a rounding algorithm based on Raghavendra-Tan [RT12], in addition to techniques from [BKS15].

Original languageEnglish (US)
Title of host publication29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018
EditorsArtur Czumaj
PublisherAssociation for Computing Machinery
Number of pages19
ISBN (Electronic)9781611975031
StatePublished - 2018
Event29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018 - New Orleans, United States
Duration: Jan 7 2018Jan 10 2018

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms


Other29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018
Country/TerritoryUnited States
CityNew Orleans

ASJC Scopus subject areas

  • Software
  • General Mathematics


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