The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Quantum advantage with shallow circuits
Open accessAbstract
Quantum outperforms classical: Quantum computers are expected to be better at solving certain computational problems than classical computers. This expectation is based on (well-founded) conjectures in computational complexity theory, but rigorous comparisons between the capabilities of quantum and classical algorithms are difficult to perform. Bravyi et al. proved theoretically that whereas the number of “steps” needed by parallel quantum circuits to solve certain linear algebra problems was independent of the problem size, this number grew logarithmically with size for analogous classical circuits (see the Perspective by Montanaro). This so-called quantum advantage stems from the quantum correlations present in quantum circuits that cannot be reproduced in analogous classical circuits. Science , this issue p. 308 ; see also p. 289
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Cites
On the Einstein Podolsky Rosen paradox
Bell, J. S. (1964) · Physics Physique Fizika · doi:10.1103/physicsphysiquefizika.1.195 · Cited by 12,252
Raussendorf, R., & Briegel, H. J. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.5188 · Cited by 4,477
Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer
Shor, P. W. (1999) · SIAM Review · doi:10.1137/s0036144598347011 · Cited by 3,904
Rapid solution of problems by quantum computation
Deutsch, D., & Jozsa, R. (1992) · Proceedings of the Royal Society of London. Series A: Mathematical and Physical Sciences · doi:10.1098/rspa.1992.0167 · Cited by 2,700
Bell’s theorem without inequalities
Greenberger, D. M., Horne, M. A., Shimony, A., & Zeilinger, A. (1990) · American Journal of Physics · doi:10.1119/1.16243 · Cited by 2,404
Computational Complexity: A Modern Approach
Arora, S., & Barak, B. (2009) · Cited by 2,371
Measurement-based quantum computation on cluster states
Raussendorf, R., Browne, D. E., & Briegel, H. J. (2003) · Physical Review A · doi:10.1103/physreva.68.022312 · Cited by 1,655
Improved simulation of stabilizer circuits
Aaronson, S., & Gottesman, D. (2004) · Physical Review A · doi:10.1103/physreva.70.052328 · Cited by 1,515
Bernstein, E., & Vazirani, U. (1997) · SIAM Journal on Computing · doi:10.1137/s0097539796300921 · Cited by 1,503
Extreme quantum entanglement in a superposition of macroscopically distinct states
Mermin, N. D. (1990) · Physical Review Letters · doi:10.1103/physrevlett.65.1838 · Cited by 1,482 · cited 2×
“The proof exploits quantum nonlocality – a form of correlation present in the measurement statistics of entangled quantum states that cannot be reproduced by local hidden variable models [18, 19] even if a limited amount of communication is allowed [20].”
Background
Cited by
Quantum supremacy using a programmable superconducting processor
Arute, F., Arya, K., Babbush, R., Bacon, D., Bardin, J. C., Barends, R., Biswas, R., Boixo, S., Brandao, F. G. S. L., Buell, D. A., et al. (2019) · Nature · doi:10.1038/s41586-019-1666-5 · Cited by 7,720
Materials challenges and opportunities for quantum computing hardware
de Leon, N. P., Itoh, K. M., Kim, D., Mehta, K. K., Northup, T. E., Paik, H., Palmer, B. S., Samarth, N., Sangtawesin, S., & Steuerman, D. W. (2021) · Science · doi:10.1126/science.abb2823 · Cited by 710
A Survey on quantum computing technology
Gyongyosi, L., & Imre, S. (2019) · Computer Science Review · doi:10.1016/j.cosrev.2018.11.002 · Cited by 646
Quantum simulation and computing with Rydberg-interacting qubits
Morgado, M., & Whitlock, S. (2021) · AVS Quantum Science · doi:10.1116/5.0036562 · Cited by 370
Scalable Mitigation of Measurement Errors on Quantum Computers
Nation, P. D., Kang, H., Sundaresan, N., & Gambetta, J. M. (2021) · PRX Quantum · doi:10.1103/prxquantum.2.040326 · Cited by 269
Metadata
- Authors
- Bravyi, S., Gosset, D., & König, R.
- Venue
- Science
- Published
- 2018-10-19
- Volume
- 362
- Issue
- 6412
- Pages
- 308-311
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2604467189
- Cited by
- 406
- References
- 42
- FWCI
- 21.92
- Type
- journal article
- Language
- en
- Open access
- green
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