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  4. A comprehensive benchmark of an Ising machine on the Max-Cut problem
 
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A comprehensive benchmark of an Ising machine on the Max-Cut problem

Citation Link: https://doi.org/10.15480/882.15973
Publikationstyp
Preprint
Date Issued
2025-07-29
Sprache
English
Author(s)
Shaglel, Salwa 
Quantum-Inspired and Quantum Optimization E-25  
Kirsch, Markus
Winkler, Marten
Quantum Inspired and Quantum Optimization E-25  
Münch, Christian
Walter, Stefan
Schinkel, Fritz
Kliesch, Martin  
Quantum Inspired and Quantum Optimization E-25  
TORE-DOI
10.15480/882.15973
TORE-URI
https://hdl.handle.net/11420/57923
Citation
arXiv: 2507.22117 (2025)
Publisher DOI
10.48550/arXiv.2507.22117
ArXiv ID
2507.22117
Peer Reviewed
false
QUBO formulations of combinatorial optimization problems allow for solving them using various quantum heuristics. While large-scale quantum computations are currently still out of reach, we can already numerically test such QUBO formulations on a perhaps surprisingly large scale. In this work, we benchmark Fujitsu’s Digital Annealer (DA) on the Max-Cut problem, which captures the main complexity of the QUBO problem. We make a comprehensive benchmark against leading other heuristic algorithms on graphs with up to 53,000 variables by focusing on the wall-clock time. Moreover, we compare the DA performance against published performance results of the D-Wave hybrid quantum-classical annealer and the recently proposed QIS3 heuristic. Based on performance statistics for over 2,000 graphs from the MQLib, we find that the DA yields competitive results. We hope that this benchmark demonstrates the extent to which large QUBO instances can be heuristically solved today, yielding consistent results across different solvers.
Subjects
Quantum Physics
Emerging Technologies
DDC Class
539: Matter; Molecular Physics; Atomic and Nuclear physics; Radiation; Quantum Physics
006: Special computer methods
Lizenz
https://creativecommons.org/licenses/by/4.0/
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