The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Quantum versus classical annealing of Ising spin glasses
Open accessAbstract
Benchmarking quantum simulation: Finding a solution to a problem often amounts to an optimization problem and thus can be recast in terms of the lowest-energy state of a system. To find such ground states, mathematical methods based on annealing were developed. To reach the ground state more quickly than with the earlier classical methods, a quantum-mechanical approach was proposed; however, the evidence for quantum speed-up is contradictory. Heim et al.show that the results depend on how the problem is described and how the optimization routine is implemented. This development should be valuable for benchmarking quantum machines. Science, this issue p.215
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The complexity of theorem-proving procedures
Cook, S. A. (1971) · Proceedings of the third annual ACM symposium on Theory of computing - STOC '71 · doi:10.1145/800157.805047 · Cited by 6,385
Non-adiabatic crossing of energy levels
Zener, C. (1932) · Proceedings of the Royal Society of London Series A Containing Papers of a Mathematical and Physical Character · doi:10.1098/rspa.1932.0165 · Cited by 4,572
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
On the product of semi-groups of operators
Trotter, H. F. (1959) · Proceedings of the American Mathematical Society · doi:10.1090/s0002-9939-1959-0108732-6 · Cited by 2,282
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
Suzuki, M. (1976) · Communications in Mathematical Physics · doi:10.1007/bf01609348 · Cited by 895
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
Self-citationColloquium : Quantum annealing and analog quantum computation
Das, A., & Chakrabarti, B. K. (2008) · Reviews of Modern Physics · doi:10.1103/revmodphys.80.1061 · Cited by 700
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
Self-citation
Cited by
Microwave photonics with superconducting quantum circuits
Gu, X., Kockum, A. F., Miranowicz, A., Liu, Y.-X., & Nori, F. (2017) · Physics Reports · doi:10.1016/j.physrep.2017.10.002 · Cited by 1,307
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
Quantum generalisation of feedforward neural networks
Wan, K. H., Dahlsten, O., Kristjánsson, H., Gardner, R., & Kim, M. S. (2017) · npj Quantum Information · doi:10.1038/s41534-017-0032-4 · Cited by 276
Quantum critical dynamics in a 5,000-qubit programmable spin glass
King, A. D., Raymond, J., Lanting, T., Harris, R., Zucca, A., Altomare, F., Berkley, A. J., Boothby, K., Ejtemaee, S., Enderud, C., et al. (2023) · Nature · doi:10.1038/s41586-023-05867-2 · Cited by 242
Optimizing Variational Quantum Algorithms Using Pontryagin’s Minimum Principle
Yang, Z.-C., Rahmani, A., Shabani, A., Neven, H., & Chamon, C. (2017) · Physical Review X · doi:10.1103/physrevx.7.021027 · Cited by 210
Metadata
- Authors
- Heim, B., Rønnow, T. F., Isakov, S. V., & Troyer, M.
- Venue
- Science
- Published
- 2015-04-10
- Volume
- 348
- Issue
- 6231
- Pages
- 215-217
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2083773133
- Cited by
- 193
- References
- 9
- FWCI
- 19.71
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
