Solving Max-3SAT Using QUBO Approximation

Sebastian Zielinski, Jonas Nublein, Michael Kolle, Thomas Gabor, Claudia Linnhoff-Popien, Sebastian Feld

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

As contemporary quantum computers do not possess error correction, any calculation performed by these devices can be considered an involuntary approximation. To solve a problem on a quantum annealer, it has to be expressed as an instance of Quadratic Unconstrained Binary Optimization (QUBO). In this work, we thus study whether systematically approximating QUBO representations of the MAX-3SAT problem can improve the solution quality when solved on contemporary quantum hardware, compared to using exact, non-approximated QUBO representations. For a MAX-3SAT instance consisting of a 3SAT formula with n variables and m clauses, we propose a method of systematically creating approximate QUBO representations of dimension (n× n), which is significantly smaller than the QUBO matrices of any exact, non-approximated MAX-3SAT QUBO transformation. In an empirical evaluation, we demonstrate that using our QUBO approximations for solving MAX-3SAT problems on D-Wave's quantum annealer Advantage_System6.4 can yield better results than using state-of-the-art exact QUBO transformations. Furthermore, we demonstrate that using naive QUBO approximation methods, based on removing values from exact (n+m)×(n+m)-dimensional QUBO representations of MAX-3SAT instances, is ineffective.

Original languageEnglish
Title of host publicationTechnical Papers Program
EditorsCandace Culhane, Greg T. Byrd, Hausi Muller, Yuri Alexeev, Yuri Alexeev, Sarah Sheldon
PublisherIEEE
Pages681-691
Number of pages11
ISBN (Electronic)9798331541378
DOIs
Publication statusPublished - 2025
Event5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024 - Montreal, Canada
Duration: 15 Sept 202420 Sept 2024

Publication series

NameProceedings - IEEE Quantum Week 2024, QCE 2024
Volume1

Conference

Conference5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024
Country/TerritoryCanada
CityMontreal
Period15/09/2420/09/24

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Approximation
  • Combinatorial Optimization
  • Max-3SAT
  • Quadratic Unconstrained Binary Optimization

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