The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.
The theory of variational hybrid quantum-classical algorithms
Open accessAbstract
Many quantum algorithms have daunting resource requirements when compared to what is available today. To address this discrepancy, a quantum-classical hybrid optimization scheme known as 'the quantum variational eigensolver' was developed (Peruzzo et al 2014 Nat. Commun. 5 4213 ) with the philosophy that even minimal quantum resources could be made useful when used in conjunction with classical routines. In this work we extend the general theory of this algorithm and suggest algorithmic improvements for practical implementations. Specifically, we develop a variational adiabatic ansatz and explore unitary coupled cluster where we establish a connection from second order unitary coupled cluster to universal gate sets through a relaxation of exponential operator splitting. We introduce the concept of quantum variational error suppression that allows some errors to be suppressed naturally in this algorithm on a pre-threshold quantum device. Additionally, we analyze truncation and correlated sampling in Hamiltonian averaging as ways to reduce the cost of this procedure. Finally, we show how the use of modern derivative free optimization techniques can offer dramatic computational savings of up to three orders of magnitude over previously used optimization techniques.
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
“To this end, it has been shown that by considering general commutations (and increasing the number of gates of the circuit quadratically with n ) the scaling of the number of measurements can be reduced to n 3 [213, 214, 216-219].”
From Variational quantum algorithms (2021) · cites this paper as [218]
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
“Motivated by adiabatic state preparation, the Variational Hamiltonian Ansatz (VHA) was developed to reduce the number of parameters and accelerate the convergence (McClean et al. , 2016; Wecker et al. , 2015).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as McClean et al., 2016
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
“The electronic structure problem is one of the most prominent tasks within VQAs (see for example the reviews (Cao et al. , 2019; McArdle et al. , 2020)) and was the pioneering task for VQE (McClean et al. , 2016; Peruzzo et al. , 2014).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as McClean et al. , 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“An important class of algorithms for NISQ hardware are socalled hybrid quantum-classical algorithms that partition the computational workload between a classical and a quantum computer.[124,125]”
From Quantum Computing for Molecular Biology** (2023) · cites this paper as [124]
The cited source says what the claim attributes to it.
In the citing paper
“Pauli strings that commute qubit-wise, i.e. the Pauli operators on each qubit commute, can be measured at the same time (Kandala et al. , 2017; McClean et al. , 2016).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as McClean et al., 2016
The cited source says what the claim attributes to it.
In the citing paper
“To this end, VQE (McClean et al. , 2016; Peruzzo et al. , 2014) has been proposed, to find the ground state of a Hamiltonian H in a manner that is suited for NISQ devices (Wecker et al. , 2015).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as McClean et al. , 2016
In the citing paper
“In contrast, the Boson Sampling model of computation does not have this property 63 .”
From Quantum Chemistry in the Age of Quantum Computing (2019) · cites this paper as [63]
In the citing paper
“Many algorithms for near-term quantum computers are based on variational circuits [1-6]”
From Estimating the gradient and higher-order derivatives on quantum hardware (2021) · cites this paper as [4]
In the citing paper
“This definition differs from [13, 14] and loosely coincides with the complexity of classically simulating the model circuits.”
From Validating quantum computers using randomized model circuits (2019) · cites this paper as [14]
In the citing paper
“Hybrid quantum-classical algorithms, such as the variational quantum eigensolver 2,3 (VQE) and the quantum approximate optimization algorithm 4,5 (QAOA), provide ways to use NISQ computers for practical applications.”
From A generative modeling approach for benchmarking and training shallow quantum circuits (2019) · cites this paper as [3]
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 Computation and Quantum Information
Nielsen, M. A., Chuang, I., & Grover, L. K. (2002) · American Journal of Physics · doi:10.1119/1.1463744 · Cited by 21,895
Braun, W. J., & Murdoch, D. J. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108993456.011 · Cited by 14,099
(1999) · Cited by 12,854
Nocedal, J. M., & Wright, S. J. (2006) · Springer series in operations research/Springer series in operations research and financial engineering · doi:10.1007/978-0-387-40065-5 · Cited by 10,206
A fifth-order perturbation comparison of electron correlation theories
Raghavachari, K., Trucks, G. W., Pople, J. A., & Head‐Gordon, M. (1989) · Chemical Physics Letters · doi:10.1016/s0009-2614(89)87395-6 · Cited by 8,511
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2012) · doi:10.1017/cbo9780511976667 · Cited by 8,436
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-citationThe Mathematical Theory of Optimal Processes
Bellman, R., Pontryagin, L. S., Boltyanskii, V. G., Gamkrelidze, R. V., Mishchenko, E. F., Trirogoff, Κ. N., & Neustadt, L. W. (1965) · Econometrica · doi:10.2307/1911909 · Cited by 4,212
Coupled-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
Čı́žek, J. (1966) · The Journal of Chemical Physics · doi:10.1063/1.1727484 · Cited by 3,062
�ber das Paulische �quivalenzverbot
Jordan, P., & Wigner, E. (1928) · Zeitschrift f�r Physik · doi:10.1007/bf01331938 · Cited by 2,597
Molecular Electronic‐Structure Theory
Helgaker, T., Jørgensen, P., & Olsen, J. (2000) · doi:10.1002/9781119019572 · Cited by 2,594
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
A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
Farhi, E., Goldstone, J., Gutmann, S., Lapan, J., Lundgren, A., & Preda, D. (2001) · Science · doi:10.1126/science.1057726 · Cited by 2,056
Kalos, M. H., & Whitlock, P. A. (1986) · Wiley eBooks · doi:10.1002/9783527617395 · Cited by 1,632
Molecular electronic-structure theory
Ratner, M. A. (2000) · Cited by 1,565
Born, M., & Fock, V. (1928) · Zeitschrift f�r Physik · doi:10.1007/bf01343193 · Cited by 1,494
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
Self-citationMany-Body Methods in Chemistry and Physics
Shavitt, I., & Bartlett, R. J. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511596834 · Cited by 1,282
Derivative-free optimization: a review of algorithms and comparison of software implementations
Rios, L. M., & Sahinidis, N. V. (2013) · Journal of Global Optimization · doi:10.1007/s10898-012-9951-y · Cited by 1,276
Short-range correlations in nuclear wave functions
Coester, F., & Kümmel, H. G. (1960) · Nuclear Physics · doi:10.1016/0029-5582(60)90140-1 · Cited by 1,261
Aspuru-Guzik, A., & Walther, P. (2012) · Nature Physics · doi:10.1038/nphys2253 · Cited by 952
Self-citationAbout the Pauli exclusion principle
Jordán, P., & Wigner, E. P. (1928) · Cited by 951
Quantum Algorithm Providing Exponential Speed Increase for Finding Eigenvalues and Eigenvectors
Abrams, D. S., & Lloyd, S. (1999) · Physical Review Letters · doi:10.1103/physrevlett.83.5162 · Cited by 817
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
Self-citationSimulation of Many-Body Fermi Systems on a Universal Quantum Computer
Abrams, D. S., & Lloyd, S. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.2586 · Cited by 745
MONTE CARLO METHODS IN AB INITIO QUANTUM CHEMISTRY
Hammond, B. L., & Lester, W. A. J. (1994) · World Scientific lecture and course notes in chemistry · doi:10.1142/9789814317245 · Cited by 697
The Complexity of the Local Hamiltonian Problem
Kempe, J., Kitaev, A., & Regev, O. (2006) · SIAM Journal on Computing · doi:10.1137/s0097539704445226 · Cited by 648
Quantum search by local adiabatic evolution
Roland, J., & Cerf, N. J. (2002) · Physical Review A · doi:10.1103/physreva.65.042308 · Cited by 629
The Bravyi-Kitaev transformation for quantum computation of electronic structure
Seeley, J. T., Richard, M. J., & Love, P. J. (2012) · The Journal of Chemical Physics · doi:10.1063/1.4768229 · Cited by 585
Solving Schrödinger’s equation around a desired energy: Application to silicon quantum dots
Wang, L., & Zunger, A. (1994) · The Journal of Chemical Physics · doi:10.1063/1.466486 · Cited by 560
Quantum Computation as Geometry
Nielsen, M. A., Dowling, M. R., Gu, M., & Doherty, A. C. (2006) · Science · doi:10.1126/science.1121541 · Cited by 539
Quantum Computation by Adiabatic Evolution
Farhi, E., Goldstone, J., Gutmann, S., & Sipser, M. (2000) · arXiv · doi:10.48550/arxiv.quant-ph/0001106 · Cited by 536
Simulation of electronic structure Hamiltonians using quantum computers
Whitfield, J. D., Biamonte, J., & Aspuru-Guzik, A. (2011) · Molecular Physics · doi:10.1080/00268976.2011.552441 · Cited by 472
Self-citationAdiabatic Quantum Computation Is Equivalent to Standard Quantum Computation
Aharonov, D., van Dam, W., Kempe, J., Landau, Z., Lloyd, S., & Regev, O. (2008) · SIAM Review · doi:10.1137/080734479 · Cited by 395
Mazziotti, D. A. (1998) · Physical Review A · doi:10.1103/physreva.57.4219 · Cited by 391
Eigenvalue computation in the 20th century
Golub, G. H., & van der Vorst, H. A. (2000) · Journal of Computational and Applied Mathematics · doi:10.1016/s0377-0427(00)00413-1 · Cited by 388
Polynomial-time quantum algorithm for the simulation of chemical dynamics
Kassal, I., Jordan, S. P., Love, P. J., Mohseni, M., & Aspuru-Guzik, A. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808245105 · Cited by 385
Self-citationSimulating physical phenomena by quantum networks
Somma, R. D., Ortíz, G., Gubernatis, J. E., Knill, E. H., & Laflamme, R. (2002) · Physical Review A · doi:10.1103/physreva.65.042323 · Cited by 372
Simulating Chemistry Using Quantum Computers
Kassal, I., Whitfield, J. D., Perdomo-Ortiz, A., Yung, M.-H., & Aspuru-Guzik, A. (2011) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-032210-103512 · Cited by 352
Self-citationMaximum-likelihood estimation of the density matrix
Banaszek, K., D’Ariano, G. M., Paris, M. G. A., & Sacchi, M. F. (1999) · Physical Review A · doi:10.1103/physreva.61.010304 · Cited by 342
Boson sampling for molecular vibronic spectra
Huh, J., Guerreschi, G. G., Peropadre, B., McClean, J. R., & Aspuru-Guzik, A. (2015) · Nature Photonics · doi:10.1038/nphoton.2015.153 · Cited by 341
Self-citationGate-count estimates for performing quantum chemistry on small quantum computers
Wecker, D., Bauer, B., Clark, B. K., Hastings, M. B., & Troyer, M. (2014) · Physical Review A · doi:10.1103/physreva.90.022305 · Cited by 296
Most Quantum States Are Too Entangled To Be Useful As Computational Resources
Gross, D., Flammia, S. T., & Eisert, J. (2009) · Physical Review Letters · doi:10.1103/physrevlett.102.190501 · Cited by 279
A new Monte Carlo technique: antithetic variates
Hammersley, J. M., & Morton, K. W. (1956) · Mathematical Proceedings of the Cambridge Philosophical Society · doi:10.1017/s0305004100031455 · Cited by 279
Quantum Simulation of Time-Dependent Hamiltonians and the Convenient Illusion of Hilbert Space
Poulin, D., Qarry, A., Somma, R., & Verstraete, F. (2011) · Physical Review Letters · doi:10.1103/physrevlett.106.170501 · Cited by 265
New perspectives on unitary coupled‐cluster theory
Taube, A. G., & Bartlett, R. J. (2006) · International Journal of Quantum Chemistry · doi:10.1002/qua.21198 · Cited by 254
A multi-reference coupled-cluster method for molecular applications
Laidig, W. D., & Bartlett, R. J. (1984) · Chemical Physics Letters · doi:10.1016/0009-2614(84)85617-1 · Cited by 250
Recent Progress in Coupled Cluster Methods
Čárský, P., Paldus, J., & Pittner, J. (2010) · Challenges and advances in computational chemistry and physics · doi:10.1007/978-90-481-2885-3 · Cited by 246
From transistor to trapped-ion computers for quantum chemistry
Yung, M.-H., Casanova, J., Mezzacapo, A., McClean, J., Lamata, L., Aspuru-Guzik, A., & Solano, E. (2014) · Scientific Reports · doi:10.1038/srep03589 · Cited by 221
Self-citationSimulation of Electronic Structure Hamiltonians Using Quantum Computers
Whitfield, J. D., Biamonte, J., & Aspuru‐Guzik, A. (2011) · Digital Access to Scholarship at Harvard (DASH) (Harvard University) · Cited by 218
Self-citationWeinstein, D. H. (1934) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.20.9.529 · Cited by 212
Improving quantum algorithms for quantum chemistry
Hastings, M., Wecker, D., Bauer, B., & Troyer, M. (2014) · Quantum information & computation · doi:10.26421/qic15.1-2-1 · Cited by 208
Mazziotti, D. A. (2006) · Physical Review Letters · doi:10.1103/physrevlett.97.143002 · Cited by 205
Chemical basis of Trotter-Suzuki errors in quantum chemistry simulation
Babbush, R., McClean, J., Wecker, D., Aspuru-Guzik, A., & Wiebe, N. (2015) · Physical Review A · doi:10.1103/physreva.91.022311 · Cited by 199
Self-citationQuantum Information and Computation for Chemistry
Lidar, D. A. (2014) · Advances in chemical physics · doi:10.1002/9781118742631 · Cited by 198
Adiabatic Quantum Simulation of Quantum Chemistry
Babbush, R., Love, P. J., & Aspuru-Guzik, A. (2014) · Scientific Reports · doi:10.1038/srep06603 · Cited by 191
Self-citationGeneral Decomposition Theory of Ordered Exponentials.
Suzuki, M. (1993) · Proceedings of the Japan Academy Series B · doi:10.2183/pjab.69.161 · Cited by 181
Experimental Implementation of an Adiabatic Quantum Optimization Algorithm
Steffen, M., van Dam, W., Hogg, T., Breyta, G., & Chuang, I. L. (2003) · Physical Review Letters · doi:10.1103/physrevlett.90.067903 · Cited by 180
An augmented coupled cluster method and its application to the first-row homonuclear diatomics
Raghavachari, K. (1985) · The Journal of Chemical Physics · doi:10.1063/1.448718 · Cited by 171
Quantum Simulation of Helium Hydride Cation in a Solid-State Spin Register
Wang, Y., Dolde, F., Biamonte, J., Babbush, R., Bergholm, V., Yang, S., Jakobi, I., Neumann, P., Aspuru‐Guzik, A., Whitfield, J. D., et al. (2015) · ACS Nano · doi:10.1021/acsnano.5b01651 · Cited by 155
Self-citationMultireference coupled-cluster theory: The easy way
Musiał, M., Perera, A., & Bartlett, R. J. (2011) · The Journal of Chemical Physics · doi:10.1063/1.3567115 · Cited by 146
The B ravyi– K itaev transformation: Properties and applications
Tranter, A., Sofia, S. E., Seeley, J. T., Kaicher, M., McClean, J. R., Babbush, R., Coveney, P. V., Mintert, F., Wilhelm, F. K., & Love, P. J. (2015) · International Journal of Quantum Chemistry · doi:10.1002/qua.24969 · Cited by 133
Self-citationExploiting Locality in Quantum Computation for Quantum Chemistry
McClean, J. R., Babbush, R., Love, P. J., & Aspuru-Guzik, A. (2014) · The Journal of Physical Chemistry Letters · doi:10.1021/jz501649m · Cited by 125
Self-citationCooling by Heating: Refrigeration Powered by Photons
Cleuren, B., Rutten, B., & den Broeck, C. V. (2012) · Physical Review Letters · doi:10.1103/physrevlett.108.120603 · Cited by 125
Schmalfuß, D., Darradi, R., Richter, J., et al. (2006) · Physical Review Letters · doi:10.1103/physrevlett.97.157201 · Cited by 124
Polynomially scaling spin dynamics simulation algorithm based on adaptive state-space restriction
Kuprov, I., Wagner-Rundell, N., & Hore, P. J. (2007) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2007.09.014 · Cited by 118
Efficient quantum circuits for diagonal unitaries without ancillas
Welch, J., Greenbaum, D., Mostame, S., & Aspuru-Guzik, A. (2014) · New Journal of Physics · doi:10.1088/1367-2630/16/3/033040 · Cited by 114
Self-citationQuantum algorithm for obtaining the energy spectrum of molecular systems
Wang, H., Kais, S., Aspuru-Guzik, A., & Hoffmann, M. R. (2008) · Physical Chemistry Chemical Physics · doi:10.1039/b804804e · Cited by 109
Self-citationGötze, O., FARNELL, D. J. J., Bishop, R. F., Li, P. H. Y., & Richter, J. (2011) · Physical Review B · doi:10.1103/physrevb.84.224428 · Cited by 102
Adiabatic state preparation study of methylene
Veis, L., & Pittner, J. (2014) · The Journal of Chemical Physics · doi:10.1063/1.4880755 · Cited by 90
Prospective study on microscopic potential with Gogny interaction
Blanchon, G., Dupuis, M., & Arellano, H. F. (2015) · The European Physical Journal A · doi:10.1140/epja/i2015-15165-1 · Cited by 89
Quantum algorithm for obtaining the energy spectrum of molecular systems
Wang, H., Kais, S., Aspuru‐Guzik, A., & Hoffmann, M. R. (2008) · Digital Access to Scholarship at Harvard (DASH) (Harvard University) · Cited by 75
Self-citationFARNELL, D. J. J., Götze, O., Richter, J., Bishop, R. F., & Li, P. H. Y. (2014) · Physical Review B · doi:10.1103/physrevb.89.184407 · Cited by 73
Simulation of Chemical Isomerization Reaction Dynamics on a NMR Quantum Simulator
Lu, D., Xu, N., Xu, R., Chen, H., Gong, J., Peng, X., & Du, J. (2011) · Physical Review Letters · doi:10.1103/physrevlett.107.020501 · Cited by 73
Neven, H., Rose, G., & Macready, W. G. (2008) · arXiv (Cornell University) · doi:10.48550/arxiv.0804.4457 · Cited by 67
Different Strategies for Optimization Using the Quantum Adiabatic AlgorithmPreprint
Crosson, E., Farhi, E., Lin, C. Y.-Y., Lin, H.-H., & Shor, P. W. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1401.7320 · Cited by 66
Quantum Adiabatic Evolution Algorithms with Different PathsPreprint
Farhi, E., Goldstone, J., & Gutmann, S. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.quant-ph/0208135 · Cited by 65
Necessary condition for the quantum adiabatic approximation
Boixo, S., & Somma, R. D. (2010) · Physical Review A · doi:10.1103/physreva.81.032308 · Cited by 60
Algorithmic Complexity and Entanglement of Quantum States
Mora, C. E., & Briegel, H. J. (2005) · Physical Review Letters · doi:10.1103/physrevlett.95.200503 · Cited by 59
On the Modified Ritz Variation Method
MacDonald, J. K. L. (1934) · Physical Review · doi:10.1103/physrev.46.828 · Cited by 57
Preparing Projected Entangled Pair States on a Quantum Computer
Schwarz, M., Temme, K., & Verstraete, F. (2012) · Physical Review Letters · doi:10.1103/physrevlett.108.110502 · Cited by 55
Robustness of the adiabatic quantum search
Åberg, J., Kult, D., & Sjöqvist, E. (2005) · Physical Review A · doi:10.1103/physreva.71.060312 · Cited by 46
Quantum Algorithms for Quantum Chemistry based on the sparsity of the CI-matrixPreprint
Toloui, B., & Love, P. J. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1312.2579 · Cited by 40
Cooling through optimal control of quantum evolution
Rahmani, A., Kitagawa, T., Demler, E., & Chamon, C. (2013) · Physical Review A · doi:10.1103/physreva.87.043607 · Cited by 36
Efficient quantum circuits for diagonal unitaries without ancillas
Welch, J., Greenbaum, D., Mostame, S., & Aspuru‐Guzik, A. (2014) · Digital Access to Scholarship at Harvard (DASH) (Harvard University) · Cited by 35
Self-citationMonte Carlo Methods in Ab Initio Quantum Chemistry
Fiedler, K. (1995) · Zeitschrift für Physikalische Chemie · doi:10.1524/zpch.1995.192.part_2.221 · Cited by 34 · cited 1×
“For an operator O and a general mixed state ρ , this is given by A variational principle on the variance exists as well, and has been used extensively for optimization in the context of quantum Monte Carlo [36].”
MethodFoley, J. J., & Mazziotti, D. A. (2012) · Physical Review A · doi:10.1103/physreva.86.012512 · Cited by 26
Communication: Spin-free quantum computational simulations and symmetry adapted states
Whitfield, J. D. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4812566 · Cited by 23
Magic state distillation and gate compilation in quantum algorithms for quantum chemistry
Trout, C. J., & Brown, K. R. (2015) · International Journal of Quantum Chemistry · doi:10.1002/qua.24856 · Cited by 17
Energy-Moment Methods in Quantum Mechanics
Delos, J. B., & Blinder, S. M. (1967) · The Journal of Chemical Physics · doi:10.1063/1.1712298 · Cited by 17
State complexity and quantum computation
Cai, Y., Le, H. N., & Scarani, V. (2015) · Annalen der Physik · doi:10.1002/andp.201400199 · Cited by 16
Unified views of quantum simulation algorithms for chemistryPreprint
Whitfield, J. D. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.03771 · Cited by 13
Probing nonlinear adiabatic paths with a universal integrator
Hofmann, M., & Schaller, G. (2014) · Physical Review A · doi:10.1103/physreva.89.032308 · Cited by 8
The Trotter Step Size Required for Accurate Quantum Simulation of Quantum ChemistryPreprint
Poulin, D., Hastings, M. B., Wecker, D., et al. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1406.4920 · Cited by 5
Numerical Methods for Large Eigenvalue Problems (Youcef Saad)
Cullum, J. K. (1994) · SIAM Review · doi:10.1137/1036077 · Cited by 2
Babbush, R., Berry, D. W., Kivlichan, I. D., et al. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.01020 · Cited by 1
Self-citation
Research works printed but not linked: 4
- Bravyi S, 2000, Ann. Phys., 298, 18
- Urban M, 1985, Chem. Phys., 83, 4041
- 10.1002/9783527626212 · DOI
- Holmström K, 2015, User’s Guide for TOMLAB
Cited by
Sorted by citations
Quantum Computing in the NISQ era and beyond
Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830
“y states of many-particle quantum systems (large molecules, for example). When applied to quantum problems this hybrid quantum-classical procedure goes by the name Variation Quantum Eigensolver (VQE) [23]. Will NISQ technology running QAOA or VQE be able to outperform classical algorithms that find approximate solution…”
MethodVariational 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
“Indeed, this was the first method introduced [192].”
MethodSelf-citationHardware-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
Machine learning and the physical sciences
Carleo, G., Cirac, J. I., Cranmer, K. S., Daudet, L., Schuld, M., Tishby, N., Vogt-Maranto, L., & Zdeborová, L. (2019) · Reviews of Modern Physics · doi:10.1103/revmodphys.91.045002 · Cited by 2,640
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
Self-citation
Metadata
- Authors
- McClean, J. R., Romero, J., Babbush, R., & Aspuru-Guzik, A.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- Harvard University (US)
- Google (United States) (US)
- Corresponding author
- McClean, Jarrod R
- Venue
- New Journal of Physics
- Publisher
- IOP Publishing
- Published
- 2016-02-04
- Volume
- 18
- Issue
- 2
- Pages
- 023023
- ISSN
- 1367-2630 (ISSN-L)
- OpenAlex
- W2257937122
- Semantic Scholar
- c78988d6c8b3d0a0385164b372f202cdeb4a5849
- Cited by
- 2,227
- References
- 93
- Citations by year
- 2026: 219 · 2025: 353 · 2024: 306 · 2023: 321 · 2022: 310 · 2021: 337 · 2020: 203 · 2019: 99 · 2018: 50 · 2017: 18 · 2016: 9
- FWCI
- 48.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- New Journal of Physics (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Army Research Office (W911NF-15-1-0256)
- Air Force Office of Scientific Research (FA9550-12-1-0046)
- Office of Naval Research Global (N00014-16-1-2008)
- Defense Security Science Engineering Fellowship (N00014-16-1-2008)
- Lawrence Berkeley National Laboratory (Luis W. Alvarez Fellowship in Compu)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Keywords
- hybrid quantum-classical algorithms, unitary coupled cluster, universal gate set, truncation, correlated sampling, derivative-free optimization
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
