Cloud Quantum Computing of an Atomic Nucleus
Open accessAbstract
We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.
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
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?
An exact solution of the time-independent non-relativistic Schrödinger equation for molecular systems quickly becomes intractable due to exponential growth of the wave function size with particle number.
“However, an exact solution quickly becomes intractable due to the exponential growth of the size of the wave function with the particle number 69 .”
From Quantum Chemistry in the Age of Quantum Computing (2019) · cites this paper as [69]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249 · see citing works
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2012) · doi:10.1017/cbo9780511976667 · Cited by 8,436 · see citing works
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 · cited 4× · see citing works
“—We use the VQE [11] quantum-classical hybrid algorithm to minimize the”
MethodInfluentialCoupled-cluster theory in quantum chemistry
Bartlett, R. J., & Musiał, M. (2007) · Reviews of Modern Physics · doi:10.1103/revmodphys.79.291 · Cited by 3,343 · see citing works
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Kandala, A., Mezzacapo, A., Temme, K., Takita, M., Brink, M., Chow, J. M., & Gambetta, J. M. (2017) · Nature · doi:10.1038/nature23879 · Cited by 2,982 · see citing works
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2011) · Cited by 2,724 · see citing works
The theory of variational hybrid quantum-classical algorithms
McClean, J. R., Romero, J., Babbush, R., & Aspuru-Guzik, A. (2016) · New Journal of Physics · doi:10.1088/1367-2630/18/2/023023 · Cited by 2,227 · see citing works
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 · see citing works
The shell model as a unified view of nuclear structure
Caurier, E., Martínez-Pinedo, G., Nowacki, F., et al. (2005) · Reviews of Modern Physics · doi:10.1103/revmodphys.77.427 · Cited by 1,301 · see citing works
Computational Complexity and Fundamental Limitations to Fermionic Quantum Monte Carlo Simulations
Troyer, M., & Wiese, U. ‐. (2005) · Physical Review Letters · doi:10.1103/physrevlett.94.170201 · Cited by 1,251 · see citing works
Volume dependence of the energy spectrum in massive quantum field theories
Lüscher, M. (1986) · Communications in Mathematical Physics · doi:10.1007/bf01211589 · Cited by 1,160 · see citing works
Scalable Quantum Simulation of Molecular Energies
O’Malley, P. J. J., Babbush, R., Kivlichan, I. D., Romero, J., McClean, J. R., Barends, R., Kelly, J., Roushan, P., Tranter, A., Ding, N., et al. (2016) · Physical Review X · doi:10.1103/physrevx.6.031007 · Cited by 1,059 · see citing works
Quantum Monte Carlo methods for nuclear physics
Carlson, J., Gandolfi, S., Pederiva, F., Pieper, S. C., Schiavilla, R., Schmidt, K. E., & Wiringa, R. B. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.1067 · Cited by 804 · see citing works
Towards quantum chemistry on a quantum computer
Lanyon, B. P., Whitfield, J. D., Gillett, G. G., Goggin, M. E., Almeida, M. P., Kassal, I., Biamonte, J. D., Mohseni, M., Powell, B. J., Barbieri, M., et al. (2010) · Nature Chemistry · doi:10.1038/nchem.483 · Cited by 796 · see citing works
BARRETT, B. R., Navrátil, P., & Vary, J. P. (2012) · Progress in Particle and Nuclear Physics · doi:10.1016/j.ppnp.2012.10.003 · Cited by 779 · see citing works
E FFECTIVE F IELD T HEORY FOR F EW -N UCLEON S YSTEMS
Bedaque, P. F., & van Kolck, U. (2002) · Annual Review of Nuclear and Particle Science · doi:10.1146/annurev.nucl.52.050102.090637 · Cited by 760 · see citing works
A new expansion for nucleon-nucleon interactions
Kaplan, D. B., Savage, M. J., & Wise, M. B. (1998) · Physics Letters B · doi:10.1016/s0370-2693(98)00210-x · Cited by 748 · see citing works
Efficient Variational Quantum Simulator Incorporating Active Error Minimization
Li, Y., & Benjamin, S. C. (2017) · Physical Review X · doi:10.1103/physrevx.7.021050 · Cited by 686 · see citing works
Coupled-cluster computations of atomic nuclei
Hagen, G., Papenbrock, T., Hjorth-Jensen, M., & Dean, D. J. (2014) · Reports on Progress in Physics · doi:10.1088/0034-4885/77/9/096302 · Cited by 590 · see citing works
Self-citationThe limits of the nuclear landscape
Erler, J., Birge, N., Kortelainen, M., et al. (2012) · Nature · doi:10.1038/nature11188 · Cited by 567 · see citing works
Shell model Monte Carlo methods
Koonin, S. E., Dean, D. J., & Langanke, K. (1997) · Physics Reports · doi:10.1016/s0370-1573(96)00017-8 · Cited by 459 · see citing works
Self-citationA New Expansion for Nucleon-Nucleon Interactions
Kaplan, D. B., Savage, M. J., & Wise, M. B. (1998) · CERN Document Server (European Organization for Nuclear Research) · Cited by 380 · see citing works
Recent developments in no-core shell-model calculations
Navrátil, P., Quaglioni, S., Stetcu, I., et al. (2009) · Journal of Physics G Nuclear and Particle Physics · doi:10.1088/0954-3899/36/8/083101 · Cited by 375 · see citing works
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 · see citing works
A Practical Quantum Instruction Set ArchitecturePreprint
Smith, R. S., Curtis, M. J., & Zeng, W. J. (2016) · arXiv (Cornell University) · doi:10.4230/lipics.fsttcs.2021.51 · Cited by 315 · see citing works
Open Quantum Assembly Language
Cross, A. W., Bishop, L. S., Smolin, J. A., & Gambetta, J. M. (2017) · arXiv · doi:10.48550/arxiv.1707.03429 · Cited by 310 · see citing works
Quantum implementation of the unitary coupled cluster for simulating molecular electronic structure
Shen, Y., Zhang, X., Zhang, S., Zhang, J.-N., Yung, M., & Kim, K. (2017) · Physical Review A · doi:10.1103/physreva.95.020501 · Cited by 288 · see citing works
Effective field theory of nuclear forces
van Kolck, U. (1999) · Progress in Particle and Nuclear Physics · doi:10.1016/s0146-6410(99)00097-6 · Cited by 285 · see citing works
Lattice simulations for few- and many-body systems
Lee, D. (2008) · Progress in Particle and Nuclear Physics · doi:10.1016/j.ppnp.2008.12.001 · Cited by 283 · see citing works
Unsupervised Machine Learning on a Hybrid Quantum Computer
Otterbach, J. S., Manenti, R., Alidoust, N., Bestwick, A., Block, M., Bloom, B., Caldwell, S., Didier, N., Fried, E. S., Hong, S., et al. (2017) · arXiv · doi:10.48550/arxiv.1712.05771 · Cited by 263 · see citing works
Universal properties of infrared oscillator basis extrapolations
More, S., Ekström, A., Furnstahl, R. J., et al. (2013) · Physical Review C · doi:10.1103/physrevc.87.044326 · Cited by 101 · see citing works
Systematic expansion for infrared oscillator basis extrapolations
Furnstahl, R. J., More, S., & Papenbrock, T. (2014) · Physical Review C · doi:10.1103/physrevc.89.044301 · Cited by 68 · see citing works
Self-citationPion-less effective field theory for atomic nuclei and lattice nuclei
Bansal, A., Binder, S., Ekström, A., Hagen, G., Jansen, G. R., & Papenbrock, T. (2018) · Physical Review C · doi:10.1103/physrevc.98.054301 · Cited by 67 · see citing works
Self-citationUltraviolet extrapolations in finite oscillator bases
König, S., Bogner, S. K., Furnstahl, R. J., More, S., & Papenbrock, T. (2014) · Physical Review C · doi:10.1103/physrevc.90.064007 · Cited by 47 · see citing works
Self-citationEffective field theory in the harmonic oscillator basis
Binder, S., Ekström, A., Hagen, G., Papenbrock, T., & Wendt, K. (2016) · Physical Review C · doi:10.1103/physrevc.93.044332 · Cited by 35 · see citing works
Self-citationLow Depth Quantum Simulation of Electronic StructurePreprint
Babbush, R., Wiebe, N., McClean, J. R., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.00023 · Cited by 8 · see citing works
Extreme-Scale Programming Model for Quantum Acceleration within High Performance ComputingPreprint
McCaskey, A., Dumitrescu, E., Liakh, D., Chen, M., Feng, W.-C., & Humble, T. S. (2017) · arXiv (Cornell University) · Cited by 6 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 3
- [15]J. R. McClean, J. Romero, R. Babbush, and A. AspuruGuzik, 'The theory of variational hybrid quantumclassical algorithms,' New J. Phys. 18 , 023023 (2016), arXiv:1509.04279 [quant-ph]. · arXiv
- [19]J. R. McClean, I. D. Kivlichan, D. S. Steiger, K. J. Sung, Y. Cao, C. Dai, E. Schuyler Fried, C. Gidney, T. H¨ aner, V. Havl´ ıˇ cek, C. Huang, Z. Jiang, M. Neeley, J. Romero, N. Rubin, N. P. D. Sawaya, K. Setia, S. Sim, W. Sun, F. Zhang, and R. Babbush, 'OpenFermion: The Electronic Structure Package for Quantum Computers,' ArXiv e-prints (2017), arXiv:1710.07629 [quant-ph]. · arXiv
- [23]P. F. Bedaque and U. van Kolck, 'Effective field theory for few-nucleon systems,' Annual Review of Nuclear and Particle Science 52 , 339-396 (2002).
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 · see citing works
Barren 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 · see citing works
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 1,726 · see citing works
Quantum Chemistry in the Age of Quantum Computing
Cao, Y., Romero, J., Olson, J. P., Degroote, M., Johnson, P. D., Kieferová, M., Kivlichan, I. D., Menke, T., Peropadre, B., Sawaya, N. P. D., et al. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00803 · Cited by 1,560 · see citing works
Evidence for the utility of quantum computing before fault tolerance
Kim, Y., Eddins, A., Anand, S., Wei, K. X., van den Berg, E., Rosenblatt, S., Nayfeh, H., Wu, Y., Zaletel, M., Temme, K., et al. (2023) · Nature · doi:10.1038/s41586-023-06096-3 · Cited by 1,050 · see citing works
The Variational Quantum Eigensolver: A review of methods and best practices
Tilly, J., Chen, H., Cao, S., Picozzi, D., Setia, K., Li, Y., Grant, E., Wossnig, L., Rungger, I., Booth, G. H., et al. (2022) · Physics Reports · doi:10.1016/j.physrep.2022.08.003 · Cited by 1,031 · see citing works
Programmable Quantum Simulations of Spin Systems with Trapped Ions
Monroe, C., Campbell, W. C., Duan, L. M., Gong, Z. X., Gorshkov, A. V., Hess, P., Islam, R., Kim, K., Linke, N., Pagano, G., et al. (2019) · arXiv · doi:10.48550/arxiv.1912.07845 · Cited by 806
Self-verifying variational quantum simulation of lattice models
Kokail, C., Maier, C., van Bijnen, R., Brydges, T., Joshi, M. K., Jurcevic, P., Muschik, C. A., Silvi, P., Blatt, R., Roos, C. F., et al. (2019) · Nature · doi:10.1038/s41586-019-1177-4 · Cited by 594 · see citing works
Hybrid Quantum-Classical Algorithms and Quantum Error Mitigation
Endo, S., Cai, Z., Benjamin, S. C., & Yuan, X. (2021) · Journal of the Physical Society of Japan · doi:10.7566/jpsj.90.032001 · Cited by 566 · see citing works
Variational quantum algorithms for nonlinear problems
Lubasch, M., Joo, J., Moinier, P., Kiffner, M., & Jaksch, D. (2020) · Physical Review A · doi:10.1103/physreva.101.010301 · Cited by 332 · see citing works
QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation
Li, A., Stein, S., Krishnamoorthy, S., & Ang, J. (2023) · ACM Transactions on Quantum Computing · doi:10.1145/3550488 · Cited by 183 · see citing works
Sawaya, N. P. D., Menke, T., Kyaw, T. H., Johri, S., Aspuru-Guzik, A., & Guerreschi, G. G. (2020) · npj Quantum Information · doi:10.1038/s41534-020-0278-0 · Cited by 163 · see citing works
Measurement reduction in variational quantum algorithms
Zhao, A., Tranter, A., Kirby, W. M., Ung, S. F., Miyake, A., & Love, P. J. (2020) · Physical Review A · doi:10.1103/physreva.101.062322 · Cited by 121 · see citing works
$O(N^3)$ Measurement Cost for Variational Quantum Eigensolver on Molecular Hamiltonians
Gokhale, P., Angiuli, O., Ding, Y., Gui, K., Tomesh, T., Suchara, M., Martonosi, M., & Chong, F. T. (2020) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2020.3035814 · Cited by 104 · see citing works
Mitigating Realistic Noise in Practical Noisy Intermediate-Scale Quantum Devices
Sun, J., Yuan, X., Tsunoda, T., Vedral, V., Benjamin, S. C., & Endo, S. (2021) · Physical Review Applied · doi:10.1103/physrevapplied.15.034026 · Cited by 105 · see citing works
Biology and medicine in the landscape of quantum advantages
Cordier, B. A., Sawaya, N. P. D., Guerreschi, G. G., & McWeeney, S. K. (2022) · Journal of The Royal Society Interface · doi:10.1098/rsif.2022.0541 · Cited by 87 · see citing works
Machine learning phase transitions with a quantum processor
Uvarov, A. V., Kardashin, A. S., & Biamonte, J. D. (2020) · Physical Review A · doi:10.1103/physreva.102.012415 · Cited by 69 · see citing works
Variational quantum eigensolver for frustrated quantum systems
Uvarov, A., Biamonte, J. D., & Yudin, D. (2020) · Physical Review B · doi:10.1103/physrevb.102.075104 · Cited by 61 · see citing works
Polymer physics by quantum computing
Micheletti, C., Hauke, P., & Faccioli, P. (2021) · Physical Review Letters · doi:10.1103/physrevlett.127.080501 · Cited by 48 · see citing works
Computationally efficient zero-noise extrapolation for quantum-gate-error mitigation
Pascuzzi, V. R., He, A., Bauer, C. W., de Jong, W. A., & Nachman, B. (2022) · Physical Review A · doi:10.1103/physreva.105.042406 · Cited by 39 · see citing works
Error mitigation with Clifford quantum-circuit data
Czarnik, P., Arrasmith, A., Coles, P. J., & Cincio, L. (2021) · Quantum · doi:10.22331/q-2021-11-26-592 · Cited by 27 · see citing works
- Authors
- Dumitrescu, E. F., McCaskey, A. J., Hagen, G., Jansen, G. R., Morris, T. D., Papenbrock, T., Pooser, R. C., Dean, D. J., & Lougovski, P.
- Affiliations
- Oak Ridge National Laboratory (US)
- ORCID
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2018-05-23
- Volume
- 120
- Issue
- 21
- Pages
- 210501-210501
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2784059933
- Cited by
- 393
- References
- 37
- Citations by year
- 2026: 22 · 2025: 29 · 2024: 40 · 2023: 64 · 2022: 51 · 2021: 83 · 2020: 53 · 2019: 36 · 2018: 14 · 2017: 1
- FWCI
- 26.18
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Physical Review Letters (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- arXiv (Cornell University)
- Funders
- U.S. Department of Energy (DE-FG02-96ER40963, DE-SC0018223, DE-AC05-00OR22725)
- Office of Science
- Oak Ridge National Laboratory (ERKBP57, ERKBP72)
- Advanced Scientific Computing Research (ERKJ332, ERKJ335)
- UT-Battelle, LLC
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › Nuclear physics research studies
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Keywords
- deuteron binding energy, pionless effective field theory, unitary coupled cluster ansatz, variational quantum eigensolver, cloud quantum computing, nuclear structure, quantum hardware mapping
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
