The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Quantum supremacy using a programmable superconducting processor
Open accessAbstract
The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor1. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here we report the use of a processor with programmable superconducting qubits2–7 to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 253 (about 1016). Measurements from repeated experiments sample the resulting probability distribution, which we verify using classical simulations. Our Sycamore processor takes about 200 seconds to sample one instance of a quantum circuit a million times—our benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy8–14 for this specific computational task, heralding a much-anticipated computing paradigm. Quantum supremacy is demonstrated using a programmable superconducting processor known as Sycamore, taking approximately 200 seconds to sample one instance of a quantum circuit a million times, which would take a state-of-the-art supercomputer around ten thousand years to compute.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In typical cases, if noise overwhelms the circuit, the measured distribution will be uniform18 and the measured XEB will be 0.”
From Logical quantum processor based on reconfigurable atom arrays (2024) · cites this paper as [18]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“As an illustration, a type of superconducting processor used for Google's quantum supremacy experiment had single-qubit and two-qubit gate errors of 0.1% and 0.3%, respectively [5].”
From Quantum Computing in the Next-Generation Computational Biology Landscape: From Protein Folding to Molecular Dynamics (2024) · cites this paper as [5]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Recent advances in control and readout of quantum bits have underscored the spectacular promise of QIP [82,83].”
From 2022 Roadmap on integrated quantum photonics (2022) · cites this paper as [82]
The cited source says what the claim attributes to it.
In the citing paper
“Quantum advantage was demonstrated against the best classical computers for the task of sampling the output of a pseudo-random quantum circuit.”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as Arute et al., 2019
The cited source says what the claim attributes to it.
In the citing paper
“Finally, using 3D [[8,3,2]] code blocks16,17, we realize computationally complex sampling circuits18 with up to 48 logical qubits entangled with hypercube connectivity19 with 228 logical two-qubit gates and 48 logical CCZ gates20.”
From Logical quantum processor based on reconfigurable atom arrays (2024) · cites this paper as [18]
The cited source says what the claim attributes to it.
In the citing paper
“We obtain an XEB of approximately 0.1 for 48 logical qubits and hundreds of nonlocal logical entangling gates, up to roughly an order of magnitude higher than previous physical qubit implementations of digital circuits of similar complexity18,48, showing the benefits of a logical encoding for this application.”
From Logical quantum processor based on reconfigurable atom arrays (2024) · cites this paper as [18]
The cited source says what the claim attributes to it.
In the citing paper
“The researchers have explained that their sycamore processor takes about 200s to compute. A similar job would take approximately 10,000years by a state-of-the-art classical supercomputer [5].”
From Quantum Computing in the Next-Generation Computational Biology Landscape: From Protein Folding to Molecular Dynamics (2024) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“In the year of 2019, researchers executed quantum supremacy successfully in a 53 qubit superconducting machine.”
From Quantum Computing in the Next-Generation Computational Biology Landscape: From Protein Folding to Molecular Dynamics (2024) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“RCS is a system-level benchmark assessing how effectively a quantum computer can generate computationally complex quantum states15.”
From A 98-qubit trapped-ion quantum computer with all-to-all connectivity (2026) · cites this paper as [15]
The cited source says what the claim attributes to it.
In the citing paper
“In either case, the quality of samples can be judged by statistical tests, with the linear cross-entropy test being a widely used standard15.”
From A 98-qubit trapped-ion quantum computer with all-to-all connectivity (2026) · cites this paper as [15]
The cited source says what the claim attributes to it.
In the citing paper
“Existing quantum devices contain on the order of 100 physical qubits.”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as Arute et al., 2019
The cited source says what the claim attributes to it.
In the citing paper
“The recent development of quantum computing, which uses entanglement, superposition, and other quantum fundamental concepts, can provide substantial processing advantages over traditional computing.”
From Quantum Computing: Vision and Challenges (2025) · cites this paper as [4]
In the citing paper
“Error correction requires thousands of physical qubits for each logical qubit [91], resulting in millions of qubits for calculating the FeMoco ground state energy [45, 46].”
From Drug design on quantum computers (2024) · cites this paper as [45]
In the citing paper
“However, in the near term, this tradeoff is a happy one as many NISQ architectures—most notably superconducting qubit devices—can easily and rapidly repeat executions of a quantum circuit.”
From Training deep quantum neural networks (2020) · cites this paper as [46]
In the citing paper
“For example, the recently reported experiment involving the “Sycamore” quantum computer executed one instance of a quantum circuit a million times in 200 s46.”
From Training deep quantum neural networks (2020) · cites this paper as [46]
In the citing paper
“For comparison, the recent work on quantum supremacy by Google reported fidelities of 0.1% for single-qubit gates and 0.3% for two-qubit gates in a superconducting processor [20].”
From The prospects of quantum computing in computational molecular biology (2021) · cites this paper as [20]
In the citing paper
“Given that the current record for a controllable, programmable quantum processor is 53 qubits [20], there is still a long way to go.”
From The prospects of quantum computing in computational molecular biology (2021) · cites this paper as [20]
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
Quantum Computing in the NISQ era and beyond
Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830
Algorithms for quantum computation: discrete logarithms and factoring
Shor, P. W. (2002) · Proceedings 35th Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1994.365700 · Cited by 8,713
Simulating physics with computers
Feynman, R. P. (1982) · International Journal of Theoretical Physics · doi:10.1007/bf02650179 · Cited by 7,691
A variational eigenvalue solver on a photonic quantum processor
Peruzzo, A., McClean, J., Shadbolt, P., Yung, M.-H., Zhou, X.-Q., Love, P. J., Aspuru-Guzik, A., & O’Brien, J. L. (2014) · Nature Communications · doi:10.1038/ncomms5213 · Cited by 4,552
Self-citationScheme for reducing decoherence in quantum computer memory
Shor, P. W. (1995) · Physical Review A · doi:10.1103/physreva.52.r2493 · Cited by 4,479
Quantum Mechanics Helps in Searching for a Needle in a Haystack
Grover, L. K. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.325 · Cited by 4,306
Strong coupling of a single photon to a superconducting qubit using circuit quantum electrodynamics
Wallraff, A., Schuster, D. I., Blais, A., Frunzio, L., Huang, R. S., Majer, J., Kumar, S., Girvin, S. M., & Schoelkopf, R. J. (2004) · Nature · doi:10.1038/nature02851 · Cited by 3,796
Charge-insensitive qubit design derived from the Cooper pair box
Koch, J., Yu, T. M., Gambetta, J., Houck, A. A., Schuster, D. I., Majer, J., Blais, A., Devoret, M. H., Girvin, S. M., & Schoelkopf, R. J. (2007) · Physical Review A · doi:10.1103/physreva.76.042319 · Cited by 3,351
Surface codes: Towards practical large-scale quantum computation
Fowler, A. G., Mariantoni, M., Martinis, J. M., & Cleland, A. N. (2012) · Physical Review A · doi:10.1103/physreva.86.032324 · Cited by 3,059
Self-citationBarren plateaus in quantum neural network training landscapes
McClean, J. R., Boixo, S., Smelyanskiy, V. N., Babbush, R., & Neven, H. (2018) · Nature Communications · doi:10.1038/s41467-018-07090-4 · Cited by 2,329
Self-citationSuperconducting Circuits for Quantum Information: An Outlook
Devoret, M., & Schoelkopf, R. J. (2013) · Science · doi:10.1126/science.1231930 · Cited by 2,197
Superconducting quantum circuits at the surface code threshold for fault tolerance
Barends, R., Kelly, J., Megrant, A., Veitia, A., Sank, D., Jeffrey, E., White, T. C., Mutus, J., Fowler, A. G., Campbell, B., et al. (2014) · Nature · doi:10.1038/nature13171 · Cited by 1,733
Self-citationQuantum convolutional neural networks
Cong, I., Choi, S., & Lukin, M. D. (2019) · Nature Physics · doi:10.1038/s41567-019-0648-8 · Cited by 1,517
Simulated Quantum Computation of Molecular Energies
Aspuru-Guzik, A., Dutoi, A. D., Love, P. J., & Head-Gordon, M. (2005) · Science · doi:10.1126/science.1113479 · Cited by 1,418
Josephson Persistent-Current Qubit
Mooij, J. E., Orlando, T. P., Levitov, L. S., Tian, L., van der Wal, C. H., & Lloyd, S. (1999) · Science · doi:10.1126/science.285.5430.1036 · Cited by 1,356
Atomic physics and quantum optics using superconducting circuits
You, J. Q., & Nori, F. (2011) · Nature · doi:10.1038/nature10122 · Cited by 1,311
Bernstein, E., & Vazirani, U. (1993) · Proceedings of the twenty-fifth annual ACM symposium on Theory of computing - STOC '93 · doi:10.1145/167088.167097 · Cited by 1,284
Characterizing quantum supremacy in near-term devices
Boixo, S., Isakov, S. V., Smelyanskiy, V. N., Babbush, R., Ding, N., Jiang, Z., Bremner, M. J., Martinis, J. M., & Neven, H. (2018) · Nature Physics · doi:10.1038/s41567-018-0124-x · Cited by 1,175
Self-citationTwo-bit gates are universal for quantum computation
DiVincenzo, D. P. (1995) · Physical Review A · doi:10.1103/physreva.51.1015 · Cited by 1,069
Randomized benchmarking of quantum gates
Knill, E., Leibfried, D., Reichle, R., Britton, J., Blakestad, R. B., Jost, J. D., Langer, C., Ozeri, R., Seidelin, S., & Wineland, D. J. (2008) · Physical Review A · doi:10.1103/physreva.77.012307 · Cited by 1,019
Extending the lifetime of a quantum bit with error correction in superconducting circuits
Ofek, N., Petrenko, A., Heeres, R., Reinhold, P., Leghtas, Z., Vlastakis, B., Liu, Y., Frunzio, L., Girvin, S. M., Jiang, L., et al. (2016) · Nature · doi:10.1038/nature18949 · Cited by 941
The computational complexity of linear optics
Aaronson, S., & Arkhipov, A. (2011) · Proceedings of the forty-third annual ACM symposium on Theory of computing · doi:10.1145/1993636.1993682 · Cited by 874
Resolving photon number states in a superconducting circuit
Schuster, D., Houck, A., Schreier, J. A., Wallraff, A. J., Gambetta, J., Blais, A., Frunzio, L., Majer, J., Johnson, B., Devoret, M., et al. (2007) · Nature · doi:10.1038/nature05461 · Cited by 869
Scalable and Robust Randomized Benchmarking of Quantum Processes
Magesan, E., Gambetta, J., & Emerson, J. (2011) · Physical Review Letters · doi:10.1103/physrevlett.106.180504 · Cited by 797
Quantum Chemistry Calculations on a Trapped-Ion Quantum Simulator
Hempel, C., Maier, C., Romero, J., McClean, J., Monz, T., Shen, H., Jurcevic, P., Lanyon, B. P., Love, P., Babbush, R., et al. (2018) · Physical Review X · doi:10.1103/physrevx.8.031022 · Cited by 629
Self-citationThe flux qubit revisited to enhance coherence and reproducibility
Yan, F., Gustavsson, S., Kamal, A., Birenbaum, J., Sears, A., Hover, D. J., Gudmundsen, T., Rosenberg, D., Samach, G., Weber, S. J., et al. (2016) · Nature Communications · doi:10.1038/ncomms12964 · Cited by 605
Qubit Architecture with High Coherence and Fast Tunable Coupling
Chen, Y., Neill, C., Roushan, P., Leung, N., Fang, M., Barends, R., Kelly, J., Campbell, B., Chen, Z., Chiaro, B., et al. (2014) · Physical Review Letters · doi:10.1103/physrevlett.113.220502 · Cited by 591
Self-citationApproaching Unit Visibility for Control of a Superconducting Qubit with Dispersive Readout
Wallraff, A. J., Schuster, D., Blais, A., Frunzio, L., Majer, J., Devoret, M., Girvin, S. M., & Schoelkopf, R. J. (2005) · Physical Review Letters · doi:10.1103/physrevlett.95.060501 · Cited by 586
Corcoles, A. D., Magesan, E., Srinivasan, S. J., Cross, A. W., Steffen, M., Gambetta, J., & Chow, J. M. (2015) · Nature Communications · doi:10.1038/ncomms7979 · Cited by 495
Fast Accurate State Measurement with Superconducting Qubits
Jeffrey, E. R., Sank, D., Mutus, J., White, T., Kelly, J., Barends, R., Chen, Y., Chen, Z., Chiaro, B., Dunsworth, A., et al. (2014) · Physical Review Letters · doi:10.1103/physrevlett.112.190504 · Cited by 481
Self-citationA blueprint for demonstrating quantum supremacy with superconducting qubits
Neill, C., Roushan, P., Kechedzhi, K., Boixo, S., Isakov, S. V., Smelyanskiy, V., Megrant, A., Chiaro, B., Dunsworth, A., Arya, K., et al. (2018) · Science · doi:10.1126/science.aao4309 · Cited by 468
Self-citationCharacterizing quantum gates via randomized benchmarking
Magesan, E., Gambetta, J. M., & Emerson, J. (2012) · Physical Review A · doi:10.1103/physreva.85.042311 · Cited by 464
Devoret, M. H., Martinis, J. M., & Clarke, J. (1985) · Physical Review Letters · doi:10.1103/physrevlett.55.1908 · Cited by 454
Self-citationTunable Coupling Scheme for Implementing High-Fidelity Two-Qubit Gates
Yan, F., Krantz, P., Sung, Y., Kjaergaard, M., Campbell, D. L., Orlando, T. P., Gustavsson, S., & Oliver, W. D. (2018) · Physical Review Applied · doi:10.1103/physrevapplied.10.054062 · Cited by 423
Quantum advantage with shallow circuits
Bravyi, S. B., Gosset, D., & König, R. (2018) · Science · doi:10.1126/science.aar3106 · Cited by 406
Complexity-Theoretic Foundations of Quantum Supremacy ExperimentsPreprint
Aaronson, S., & Chen, L. (2016) · arXiv (Cornell University) · doi:10.14288/1.0343134 · Cited by 400
Low-Depth Quantum Simulation of Materials
Babbush, R., Wiebe, N., McClean, J., McClain, J., Neven, H., & Chan, G. K.-L. (2018) · Physical Review X · doi:10.1103/physrevx.8.011044 · Cited by 335
Self-citationFluctuations of Energy-Relaxation Times in Superconducting Qubits
Klimov, P. V., Kelly, J., Chen, Z., Neeley, M., Megrant, A., Burkett, B., Barends, R., Arya, K., Chiaro, B., Chen, Y., et al. (2018) · Physical Review Letters · doi:10.1103/physrevlett.121.090502 · Cited by 328
Self-citationIntroduction to quantum electromagnetic circuits
Vool, U., & Devoret, M. (2017) · International Journal of Circuit Theory and Applications · doi:10.1002/cta.2359 · Cited by 315
Average-Case Complexity Versus Approximate Simulation of Commuting Quantum Computations
Bremner, M. J., Montanaro, A., & Shepherd, D. J. (2016) · Physical Review Letters · doi:10.1103/physrevlett.117.080501 · Cited by 299
On the complexity and verification of quantum random circuit sampling
Bouland, A., Fefferman, B., Nirkhe, C., & Vazirani, U. (2019) · Nature Physics · doi:10.1038/s41567-018-0318-2 · Cited by 287
Measuring and Suppressing Quantum State Leakage in a Superconducting Qubit
Chen, Z., Kelly, J., Quintana, C., Barends, R., Campbell, B., Chen, Y., Chiaro, B., Dunsworth, A., Fowler, A. G., Lucero, E. A., et al. (2016) · Physical Review Letters · doi:10.1103/physrevlett.116.020501 · Cited by 270
Self-citationCommercialize quantum technologies in five years
Mohseni, M., Read, P., Neven, H., Boixo, S., Denchev, V., Babbush, R., Fowler, A., Smelyanskiy, V., & Martinis, J. (2017) · Nature · doi:10.1038/543171a · Cited by 268
Self-citationNakamura, Y., Chen, C. D., & Tsai, J. S. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.2328 · Cited by 209
Quantum Simulations of Classical Annealing Processes
Somma, R. D., Boixo, S., Barnum, H., & Knill, E. (2008) · Physical Review Letters · doi:10.1103/physrevlett.101.130504 · Cited by 171
Self-citationEstablishing the quantum supremacy frontier with a 281 Pflop/s simulation
Villalonga, B., Lyakh, D. I., Boixo, S., Neven, H., Humble, T. S., Biswas, R., Rieffel, E. G., Ho, A., & Mandrà, S. (2020) · Quantum Science and Technology · doi:10.1088/2058-9565/ab7eeb · Cited by 163
Self-citationQuantum Supremacy Is Both Closer and Farther than It AppearsPreprint
Markov, I. L., Fatima, A., Isakov, S. V., & Boixo, S. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1807.10749 · Cited by 140
Self-citation64-qubit quantum circuit simulation
Chen, Z.-Y., Zhou, Q., Xue, C., Yang, X., Guo, G.-C., & Guo, G.-P. (2018) · Science Bulletin · doi:10.1016/j.scib.2018.06.007 · Cited by 136
Self-citationMassively parallel quantum computer simulator, eleven years later
Raedt, H. A. D., Jin, F., Willsch, D., Willsch, M., Yoshioka, N., Ito, N., Yuan, S., & Michielsen, K. F. L. (2018) · Computer Physics Communications · doi:10.1016/j.cpc.2018.11.005 · Cited by 125
Self-citationSimulation of low-depth quantum circuits as complex undirected graphical modelsPreprint
Boixo, S., Isakov, S. V., Smelyanskiy, V., & Neven, H. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1712.05384 · Cited by 105
Self-citationBreaking the 49-Qubit Barrier in the Simulation of Quantum Circuits
Pednault, E., Gunnels, J. A., Nannicini, G., Lior Horesh, C., Magerlein, T., Solomonik, E., & Wisnieff, R. (2018) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · Cited by 95
Classical Simulation of Intermediate-Size Quantum CircuitsPreprint
Chen, J., Zhang, F., Huang, C., Newman, M., & Shi, Y. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.01450 · Cited by 77
Pareto-Efficient Quantum Circuit Simulation Using Tensor Contraction Deferral
Pednault, E., Gunnels, J. A., Nannicini, G., Horesh, L., Magerlein, T., Solomonik, E., Draeger, E. W., Holland, E. T., & Wisnieff, R. (2017) · arXiv · doi:10.48550/arxiv.1710.05867 · Cited by 48
Quantum-Teleportation-Inspired Algorithm for Sampling Large Random Quantum Circuits
Chen, M.-C., Li, R., Gan, L., Zhu, X., Yang, G., Lu, C., & Pan, J.-W. (2020) · Physical Review Letters · doi:10.1103/physrevlett.124.080502 · Cited by 33
Efficient population transfer via non-ergodic extended states in quantum spin glassPreprint
Kechedzhi, K., Smelyanskiy, V., McClean, J. R., Denchev, V. S., Mohseni, M., Isakov, S. V., Boixo, S., Altshuler, B. L., & Neven, H. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1807.04792 · Cited by 23
Self-citationThe Theory of the Quantum World
Gross, D. J., Marc Henneaux, A., & Sevrin, A. (2013) · WORLD SCIENTIFIC eBooks · doi:10.1142/8674 · Cited by 11
Chiralities in topological vector spacesPreprint
Kerjean, M. (2019) · arXiv (Cornell University) · doi:10.4230/lipics
Research works printed but not linked: 3
- Farhi, E. & Neven, H. Classification with quantum neural networks on near term processors. Preprint at https://arxiv.org/abs/1802.06002 (2018). · arXiv
- Cross, A. W., Magesan, E., Bishop, L. S., Smolin, J. A. & Gambetta, J. M. Scalable randomised benchmarking of non-Clifford gates. npj Quant. Inform. 2, 16012 (2016).
- Villalonga, B. et al. A flexible high-performance simulator for the verification and benchmarking of quantum circuits implemented on real hardware. npj Quant. Inform. (in the press); preprint at https://arxiv.org/abs/1811.09599 (2018). · arXiv
Cited by
Sorted by citations
Variational quantum algorithms
Cerezo, M., Arrasmith, A., Babbush, R., Benjamin, S. C., Endo, S., Fujii, K., McClean, J. R., Mitarai, K., Yuan, X., Cincio, L., et al. (2021) · Nature Reviews Physics · doi:10.1038/s42254-021-00348-9 · Cited by 3,385
“This size actually allows one to achieve quantum supremacy, outperforming the best classical supercomputer, for certain contrived mathematical tasks [8, 9].”
BackgroundSelf-citationQuantum computational advantage using photons
Zhong, H.-S., Wang, H., Deng, Y.-H., Chen, M.-C., Peng, L.-C., Luo, Y.-H., Qin, J., Wu, D., Ding, X., Hu, Y., et al. (2020) · Science · doi:10.1126/science.abe8770 · Cited by 2,405
Circuit quantum electrodynamics
Blais, A., Grimsmo, A. L., Girvin, S. M., & Wallraff, A. J. (2021) · Reviews of Modern Physics · doi:10.1103/revmodphys.93.025005 · Cited by 2,217
Noisy intermediate-scale quantum algorithms
Bharti, K., Cervera-Lierta, A., Kyaw, T. H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J. S., Menke, T., et al. (2022) · Reviews of Modern Physics · doi:10.1103/revmodphys.94.015004 · Cited by 2,231
Quantum computational chemistry
McArdle, S., Endo, S., Aspuru-Guzik, A., Benjamin, S. C., & Yuan, X. (2020) · Reviews of Modern Physics · doi:10.1103/revmodphys.92.015003 · Cited by 1,621
Metadata
- Authors
- 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., Burkett, B., Chen, Y., Chen, Z., Chiaro, B., Collins, R., Courtney, W., Dunsworth, A., Farhi, E., Foxen, B., Fowler, A., Gidney, C., Giustina, M., Graff, R., Guerin, K., Habegger, S., Harrigan, M. P., Hartmann, M. J., Ho, A., Hoffmann, M., Huang, T., Humble, T. S., Isakov, S. V., Jeffrey, E., Jiang, Z., Kafri, D., Kechedzhi, K., Kelly, J., Klimov, P. V., Knysh, S., Korotkov, A., Kostritsa, F., Landhuis, D., Lindmark, M., Lucero, E., Lyakh, D., Mandrà, S., McClean, J. R., McEwen, M., Megrant, A., Mi, X., Michielsen, K., Mohseni, M., Mutus, J., Naaman, O., Neeley, M., Neill, C., Niu, M. Y., Ostby, E., Petukhov, A., Platt, J. C., Quintana, C., Rieffel, E. G., Roushan, P., Rubin, N. C., Sank, D., Satzinger, K. J., Smelyanskiy, V., Sung, K. J., Trevithick, M. D., Vainsencher, A., Villalonga, B., White, T., Yao, Z. J., Yeh, P., Zalcman, A., Neven, H., & Martinis, J. M.
- Affiliations
- Google (United States) (US)
- Ames Research Center (US)
- University of California, Santa Barbara (US)
- Oak Ridge National Laboratory (US)
- University of California, Riverside (US)
- Forschungszentrum Jülich (DE)
- Corresponding author
- Martinis, John M.
- ORCID
- Venue
- Nature
- Published
- 2019-10-23
- Volume
- 574
- Issue
- 7779
- Pages
- 505-510
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2982169647
- Cited by
- 7,720
- References
- 51
- Citations by year
- 2026: 701 · 2025: 1157 · 2024: 1143 · 2023: 1234 · 2022: 1230 · 2021: 1315 · 2020: 875 · 2019: 60
- FWCI
- 397.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, other-oa)
- arXiv (Cornell University) (publishedVersion)
- PubMed (publishedVersion)
- Comillas Repository (Comillas Pontifical University) (publishedVersion, cc-by-nc-nd)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Funders
- U.S. Department of Energy (AC05-00OR22725, DE--AC05--00OR22725, DE-AC05?, Contract DE-AC05-00OR22725, 00OR22725)
- National Aeronautics and Space Administration (DE-AC05-00OR22725)
- Office of Science (DEAC05- 00OR22725, AC05-00OR22725)
- Ames Research Center
- University of California, Santa Barbara
- Air Force Research Laboratory (F4HBKC4162G001, DE-AC05-00OR22725)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
- Keywords
- quantum advantage, superconducting qubits, classical simulation of quantum circuits, programmable quantum processors, quantum computing
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
