McClean, Jarrod R.

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

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 4,552

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

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 3,385

Barren plateaus in quantum neural network training landscapes

McClean, J. R., Boixo, S., Smelyanskiy, V. N., Babbush, R., & Neven, H. (2018) · Nature Communications

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 2,329

The theory of variational hybrid quantum-classical algorithms

McClean, J. R., Romero, J., Babbush, R., & Aspuru-Guzik, A. (2016) · New Journal of Physics

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 2,227

Suppressing quantum errors by scaling a surface code logical qubit

Google Quantum, A. I., Acharya, R., Aleiner, I., Allen, R., Andersen, T. I., Ansmann, M., Arute, F., Arya, K., Asfaw, A., Atalaya, J., et al. (2023) · Nature

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,103

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

Quantum Computing Algorithms and ArchitectureAdvanced Chemical Physics Studies

Cited by 1,059

Power of data in quantum machine learning

Huang, H.-Y., Broughton, M., Mohseni, M., Babbush, R., Boixo, S., Neven, H., & McClean, J. R. (2021) · Nature Communications

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 896

Quantum error correction below the surface code threshold

Collaborators, G. Q. A. A., Acharya, R., Abanin, D. A., Aghababaie-Beni, L., Aleiner, I., Andersen, T. I., Ansmann, M., Arute, F., Arya, K., Asfaw, A., et al. (2025) · Nature

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 778

Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz

Romero, J., Babbush, R., McClean, J. R., Hempel, C., Love, P. J., & Aspuru-Guzik, A. (2019) · Quantum Science and Technology

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 726

Quantum advantage in learning from experiments

Huang, H.-Y., Broughton, M., Cotler, J., Chen, S., Li, J., Mohseni, M., Neven, H., Babbush, R., Kueng, R., Preskill, J., et al. (2022) · Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 519

Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states

McClean, J. R., Kimchi-Schwartz, M. E., Carter, J., & de Jong, W. A. (2017) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 516

Computation of Molecular Spectra on a Quantum Processor with an Error-Resilient Algorithm

Colless, J. I., Ramasesh, V. V., Dahlen, D., Blok, M. S., Kimchi-Schwartz, M. E., McClean, J. R., Carter, J., de Jong, W. A., & Siddiqi, I. (2018) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 460

Quantum Simulation of Electronic Structure with Linear Depth and Connectivity

Kivlichan, I. D., McClean, J., Wiebe, N., Gidney, C., Aspuru-Guzik, A., Chan, G. K.-L., & Babbush, R. (2018) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 431

Exponential suppression of bit or phase errors with cyclic error correction

Google Quantum, A. I., Chen, Z., Satzinger, K. J., Atalaya, J., Korotkov, A. N., Dunsworth, A., Sank, D., Quintana, C., McEwen, M., Barends, R., et al. (2021) · Nature

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 393

Encoding Electronic Spectra in Quantum Circuits with Linear T Complexity

Babbush, R., Gidney, C., Berry, D. W., Wiebe, N., McClean, J., Paler, A., Fowler, A., & Neven, H. (2018) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 383

Boson sampling for molecular vibronic spectra

Huh, J., Guerreschi, G. G., Peropadre, B., McClean, J. R., & Aspuru-Guzik, A. (2015) · Nature Photonics

Quantum Computing Algorithms and ArchitectureSpectroscopy and Quantum Chemical Studies

Cited by 341

Layerwise learning for quantum neural networks

Skolik, A., McClean, J. R., Mohseni, M., van der Smagt, P., & Leib, M. (2021) · Quantum Machine Intelligence

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 324

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

Broughton, M., Verdon, G., McCourt, T., Martinez, A. J., Yoo, J. H., Isakov, S. V., Massey, P., Halavati, R., Niu, M. Y., Zlokapa, A., et al. (2020) · arXiv

Quantum Computing Algorithms and ArchitectureParallel Computing and Optimization Techniques

Cited by 308

Even More Efficient Quantum Computations of Chemistry Through Tensor Hypercontraction

Lee, J., Berry, D. W., Gidney, C., Huggins, W. J., McClean, J. R., Wiebe, N., & Babbush, R. (2021) · PRX Quantum

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 304

Information scrambling in quantum circuits

Mi, X., Roushan, P., Quintana, C., Mandrà, S., Marshall, J., Neill, C., Arute, F., Arya, K., Atalaya, J., Babbush, R., et al. (2021) · Science

Quantum many-body systemsQuantum Computing Algorithms and Architecture

Cited by 283

Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers

Huggins, W. J., McClean, J. R., Rubin, N. C., Jiang, Z., Wiebe, N., Whaley, K. B., & Babbush, R. (2021) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 256

Qubitization of Arbitrary Basis Quantum Chemistry Leveraging Sparsity and Low Rank Factorization

Berry, D. W., Gidney, C., Motta, M., McClean, J. R., & Babbush, R. (2019) · Quantum

Quantum Computing Algorithms and ArchitectureAdvanced Chemical Physics Studies

Cited by 222

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

Quantum Computing Algorithms and ArchitectureCold Atom Physics and Bose-Einstein Condensates

Cited by 221

Witnessing eigenstates for quantum simulation of Hamiltonian spectra

Santagati, R., Wang, J., Gentile, A. A., Paesani, S., Wiebe, N., McClean, J. R., Morley-Short, S., Shadbolt, P. J., Bonneau, D., Silverstone, J. W., et al. (2018) · Science Advances

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 211