The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Reinforcement Learning in Different Phases of Quantum Control
Open accessAbstract
New experiments show that reinforcement learning algorithms, a cutting-edge technique for machine learning, can quickly and accurately learn to prepare a desired quantum state despite no knowledge of quantum mechanics.
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Citations
Cites
Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357
Mastering the game of Go with deep neural networks and tree search
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016) · Nature · doi:10.1038/nature16961 · Cited by 15,612
Solving the quantum many-body problem with artificial neural networks
Carleo, G., & Troyer, M. (2017) · Science · doi:10.1126/science.aag2302 · Cited by 2,215
Khaneja, N., Reiss, T., Kehlet, C., Schulte-Herbrüggen, T., & Glaser, S. J. (2005) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2004.11.004 · Cited by 1,854
Machine learning phases of matter
Carrasquilla, J., & Melko, R. G. (2017) · Nature Physics · doi:10.1038/nphys4035 · Cited by 1,448
NMR techniques for quantum control and computation
Vandersypen, L. M. K., & Chuang, I. L. (2005) · Reviews of Modern Physics · doi:10.1103/revmodphys.76.1037 · Cited by 1,217
Quasiparticle engineering and entanglement propagation in a quantum many-body system
Jurcevic, P., Lanyon, B. P., Hauke, P., Hempel, C., Zoller, P., Blatt, R., & Roos, C. F. (2014) · Nature · doi:10.1038/nature13461 · Cited by 863
Quantum-Enhanced Machine Learning
Dunjko, V., Taylor, J. M., & Briegel, H. J. (2016) · Physical Review Letters · doi:10.1103/physrevlett.117.130501 · Cited by 460
Onset of a quantum phase transition with a trapped ion quantum simulator
Islam, R., Edwards, E. E., Kim, K., Korenblit, S., Noh, C., Carmichael, H., Lin, G.-D., Duan, L.-M., Joseph Wang, C.-C., Freericks, J. K., et al. (2011) · Nature Communications · doi:10.1038/ncomms1374 · Cited by 411
Driving at the quantum speed limit: optimal control of a two-level system
Hegerfeldt, G. C. (2013) · Physical Review Letters · doi:10.1103/physrevlett.111.260501 · Cited by 232
Cited by
Zhou, L., Wang, S.-T., Choi, S., Pichler, H., & Lukin, M. D. (2020) · Physical Review X · doi:10.1103/physrevx.10.021067 · Cited by 913
Polino, E., Valeri, M., Spagnolo, N., & Sciarrino, F. (2020) · AVS Quantum Science · doi:10.1116/5.0007577 · Cited by 414
Artificial intelligence and machine learning for quantum technologies
Krenn, M., Landgraf, J., Foesel, T., & Marquardt, F. (2023) · Physical Review A · doi:10.1103/physreva.107.010101 · Cited by 162
Model-Free Quantum Control with Reinforcement Learning
Sivak, V. V., Eickbusch, A., Liu, H., Royer, B., Tsioutsios, I., & Devoret, M. H. (2022) · Physical Review X · doi:10.1103/physrevx.12.011059 · Cited by 130
Capacity and Quantum Geometry of Parametrized Quantum Circuits
Haug, T., Bharti, K., & Kim, M. S. (2021) · PRX Quantum · doi:10.1103/prxquantum.2.040309 · Cited by 127
Metadata
- Authors
- Bukov, M., Day, A. G. R., Sels, D., Weinberg, P., Polkovnikov, A., & Mehta, P.
- Venue
- Physical Review X
- Publisher
- American Physical Society (APS)
- Published
- 2018-09-27
- Volume
- 8
- Issue
- 3
- ISSN
- 2160-3308 (ISSN-L)
- OpenAlex
- W2761015455
- Cited by
- 310
- References
- 13
- FWCI
- 15.84
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: Reinforcement Learning in Different Phases of Quantum Control. https://app.cochat.ai/papers/10.1103/physrevx.8.031086
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- Bukov, M., Day, A. G. R., Sels, D., Weinberg, P., Polkovnikov, A., & Mehta, P. (2018). Reinforcement Learning in Different Phases of Quantum Control. Physical Review X. https://doi.org/10.1103/physrevx.8.031086
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
