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 language | English |
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Title of host publication | Technical Papers Program |
Editors | Candace Culhane, Greg T. Byrd, Hausi Muller, Yuri Alexeev, Yuri Alexeev, Sarah Sheldon |
Publisher | IEEE |
Pages | 681-691 |
Number of pages | 11 |
ISBN (Electronic) | 9798331541378 |
DOIs | |
Publication status | Published - 2025 |
Event | 5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024 - Montreal, Canada Duration: 15 Sept 2024 → 20 Sept 2024 |
Publication series
Name | Proceedings - IEEE Quantum Week 2024, QCE 2024 |
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Volume | 1 |
Conference
Conference | 5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024 |
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Country/Territory | Canada |
City | Montreal |
Period | 15/09/24 → 20/09/24 |
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-careOtherwise 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