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
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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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Items 201–209 of 209
Fast numerical solver of Ising optimization problems via pruning and domain selection
Li, L., Dong, D., & Pan, Y. (2025) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2025.107945
Hybrid real-imaginary time evolution for low-depth Hamiltonian simulation in quantum optimization
Li, F., & Li, X.-W. (2026) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2026.131539
Vipinchandran, D., & Jayashree, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6299588
Mapping of fermionic lattice models for Ising solvers
Nagpal, L., Kumar, A., & Hassan, S. R. (2026) · Scientific Reports · doi:10.1038/s41598-026-44886-7 · Cited by 1
Quantum algorithms for energy management optimization problems
Veshchezerova, M. (2022) · theses.fr (ABES) · doi:10.70675/f0d70a66z3066z4c81z8aa7zf9e72830f940 · Cited by 1
Supervised learning in binary dynamical physical systems through energy minimization
Laydevant, J. (2022) · theses.fr (ABES) · doi:10.70675/efd1c35czdc85z40bdzb5d3zd973c7dde220
Performance evaluation and control improvements for solving optimization problems on NISQ platforms
Gilbert, V. (2024) · theses.fr (ABES) · doi:10.70675/81f9c638z5867z40e4zaed8ze9824ff5a163
Quantum Computing for Operations Research : A special approach for Project Scheduling
Armas, L. F. P. (2024) · theses.fr (ABES) · doi:10.70675/cf991df2zcbd5z4574z9f45z6f05451dcf70
Quantum-enhanced spectral analysis for materials and networked systems
Ghosh, K., & Basu, B. (2026) · APL Quantum · doi:10.1063/5.0334173
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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