The pitfalls of planar spin-glass benchmarks: raising the bar for quantum annealers (again)
Open accessAbstract
In an effort to overcome the limitations of random spin-glass benchmarks for quantum annealers, focus has shifted to carefully crafted gadget-based problems whose logical structure typically has a planar topology. Recent experiments on these gadget problems using a commercially available quantum annealer have demonstrated an impressive performance over a selection of commonly used classical optimisation heuristics. Here, we show that efficient classical optimisation techniques, such as minimum-weight-perfect matching, can solve these gadget problems exactly and in polynomial time. We present approaches on how to mitigate this shortcoming of commonly used benchmark problems based on planar logical topologies.
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As of now we do not have a convincing theoretical argument or persuasive experimental evidence indicating that quantum annealers can really speed up the time to solution compared to the best classical hardware running the best algorithms for the same problems.
“as of now we don't have a convincing theoretical argument or persuasive experimental evidence indicating that quantum annealers can really speed up the time to solution compared to the best classical hardware running the best algorithms for the same problems [28, 29].”
From Quantum Computing in the NISQ era and beyond (2018) · cites this paper as [29]
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References 16 · Cited by 35
Research works printed but not linked: 3
- [10]10. Hamze F and de Freitas N 2004 Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence (Arlington, Virginia, United States: AUAI Press) UAI '04, p. 243, ISBN 0-9749039-0-6
- [11]11. Selby A 2014 Efficient subgraph-based sampling of Ising-type models with frustration arXiv:cond-mat/1409.3934
- [13]13. King J, Yarkoni S, Raymond J, Ozfidan I, King A D, Nevisi M M, Hilton J P and McGeoch C C 2017 Quantum annealing amid local ruggedness and global frustration arXiv:quant-phys/1701.04579
- Authors
- Mandrà, S., Katzgraber, H. G., & Thomas, C.
- Affiliations
- Ames Research Center (US)
- Santa Fe Institute (US)
- Google (United States) (US)
- Corresponding author
- Mandrà, Salvatore
- Venue
- Quantum Science and Technology
- Publisher
- IOP Publishing
- Published
- 2017-07-21
- Volume
- 2
- Issue
- 3
- Pages
- 038501
- ISSN
- 2058-9565 (ISSN-L)
- OpenAlex
- W2592578266
- Cited by
- 35
- References
- 16
- Citations by year
- 2025: 3 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 3 · 2020: 6 · 2019: 10 · 2018: 7 · 2017: 2
- FWCI
- 4.08
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Quantum Science and Technology (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Intelligence Advanced Research Projects Activity (FA8721- 05-C-0002)
- Division of Materials Research (1151387)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
- Keywords
- quantum annealers, planar graphs, minimum-weight perfect matching, combinatorial optimization
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