The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Quantum Optimization of Fully Connected Spin Glasses
Open accessAbstract
Quantum computing promises to be more efficient and significantly faster than today's classical computing. Researchers compare the performance of a quantum annealer with that of classical algorithms for the first time on hard spin-glass problems.
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“Since the number of random couplings scales as M 2 it is necessary to rescale the coupling strength to ensure extensive energy (correct scaling behavior) 71 ; we rescale couplers as J ij → Jij √ M/4 for every i in A and j in B.”
From Beyond-classical computation in quantum simulation (2025) · cites this paper as [71]
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Citations
Cites
Solvable Model of a Spin-Glass
Sherrington, D., & Kirkpatrick, S. (1975) · Physical Review Letters · doi:10.1103/physrevlett.35.1792 · Cited by 3,577
Collective Monte Carlo Updating for Spin Systems
Ulli Wolff, A. (1989) · Physical Review Letters · doi:10.1103/physrevlett.62.361 · Cited by 2,564
Ising formulations of many NP problems
Lucas, A. (2014) · Frontiers in Physics · doi:10.3389/fphy.2014.00005 · Cited by 2,512
Quantum annealing in the transverse Ising model
Kadowaki, T., & Nishimori, H. (1998) · Physical Review E · doi:10.1103/physreve.58.5355 · Cited by 2,339
Exchange Monte Carlo Method and Application to Spin Glass Simulations
Hukushima, K., & Nemoto, K. (1995) · Journal of the Physical Society of Japan · doi:10.1143/jpsj.65.1604 · Cited by 2,223
Quantum annealing with manufactured spins
Johnson, M. W., Amin, M. H. S., Gildert, S., Lanting, T., Hamze, F., Dickson, N., Harris, R., Berkley, A. J., Johansson, J., Bunyk, P., et al. (2011) · Nature · doi:10.1038/nature10012 · Cited by 1,891
Exchange Monte Carlo method and application to spin glass simulationsPreprint
Hukushima, K., & Nemoto, K. (1996) · Cited by 1,645
Evidence for quantum annealing with more than one hundred qubits
Boixo, S., Rønnow, T. F., Isakov, S. V., Wang, Z., Wecker, D., Lidar, D. A., Martinis, J. M., & Troyer, M. (2014) · Nature Physics · doi:10.1038/nphys2900 · Cited by 810
Theory of Quantum Annealing of an Ising Spin Glass
Santoro, G. E., Martoňák, R., Tosatti, E., & Car, R. (2002) · Science · doi:10.1126/science.1068774 · Cited by 734
Defining and detecting quantum speedup
Rønnow, T. F., Wang, Z., Job, J., Boixo, S., Isakov, S. V., Wecker, D., Martinis, J. M., Lidar, D. A., & Troyer, M. (2014) · Science · doi:10.1126/science.1252319 · Cited by 601 · cited 5×
“For these reasons groups around the world have started to experimentally benchmark the machine [9–11], nurturing a lively discussion on whether the device is making functional use of quantum mechanics for computation [12] and how to properly measure speedups between different computational/experimental algorithms [13,…”
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Perspectives of quantum annealing: methods and implementations
Hauke, P., Katzgraber, H. G., Lechner, W., Nishimori, H., & Oliver, W. D. (2020) · Reports on Progress in Physics · doi:10.1088/1361-6633/ab85b8 · Cited by 507
Traffic Flow Optimization Using a Quantum Annealer
Neukart, F., Compostella, G., Seidel, C., Dollen, D. V., Yarkoni, S., & Parney, B. (2017) · Frontiers in ICT · doi:10.3389/fict.2017.00029 · Cited by 470
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer
Aramon, M., Rosenberg, G., Valiante, E., Miyazawa, T., Tamura, H., & Katzgraber, H. G. (2019) · Frontiers in Physics · doi:10.3389/fphy.2019.00048 · Cited by 442
What is the Computational Value of Finite-Range Tunneling?
Denchev, V. S., Boixo, S., Isakov, S. V., Ding, N., Babbush, R., Smelyanskiy, V., Martinis, J., & Neven, H. (2016) · Physical Review X · doi:10.1103/physrevx.6.031015 · Cited by 399
Self-citationQuantum annealing for industry applications: introduction and review
Yarkoni, S., Raponi, E., Bäck, T., & Schmitt, S. (2022) · Reports on Progress in Physics · doi:10.1088/1361-6633/ac8c54 · Cited by 341
Metadata
- Authors
- Venturelli, D., Mandrà, S., Knysh, S., O’Gorman, B., Biswas, R., & Smelyanskiy, V.
- Affiliations
- Ames Research Center (US)
- Google (United States) (US)
- Venue
- Physical Review X
- Publisher
- American Physical Society (APS)
- Published
- 2015-09-18
- Volume
- 5
- Issue
- 3
- ISSN
- 2160-3308 (ISSN-L)
- OpenAlex
- W1553502100
- Cited by
- 209
- References
- 35
- Citations by year
- 2026: 6 · 2025: 19 · 2024: 19 · 2023: 15 · 2022: 14 · 2021: 19 · 2020: 19 · 2019: 23 · 2018: 15 · 2017: 18 · 2016: 21 · 2015: 19
- FWCI
- 23.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Physical Review X (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- National Aeronautics and Space Administration (NNX14AF62G, NNX12AK33A)
- Office of the Director of National Intelligence
- Intelligence Advanced Research Projects Activity
- AFRL Information Directorate (F4HBKC4162G001)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Keywords
- quantum annealing, spin glass, combinatorial optimization, quantum annealers, hard optimization problems
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