Machine learning in physics (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Machine learning in physics" in English language version.

refsWebsite

Global rank English rank

36doi.org

2^nd place

31harvard.edu

18^th place

17^th place

30arxiv.org

69^th place

59^th place

28semanticscholar.org

11^th place

8^th place

21nih.gov

4^th place

14worldcat.org

5^th place

4handle.net

102^nd place

76^th place

1caltech.edu

887^th place

714^th place

1qmlt.readthedocs.io

low place

1medium.com

551^st place

406^th place

1osti.gov

2,036^th place

1,254^th place

1newscientist.com

774^th place

716^th place

1advancedsciencenews.com

low place

advancedsciencenews.com

Feldman, Andrey (11 August 2022). "Artificial physicist to unravel the laws of nature". Advanced Science News. Retrieved 21 August 2022.

arxiv.org

Torlai, Giacomo; Mazzola, Guglielmo; Carrasquilla, Juan; Troyer, Matthias; Melko, Roger; Carleo, Giuseppe (May 2018). "Neural-network quantum state tomography". Nature Physics. 14 (5): 447–450. arXiv:1703.05334. Bibcode:2018NatPh..14..447T. doi:10.1038/s41567-018-0048-5. ISSN 1745-2481. S2CID 125415859.
Cory, D. G.; Wiebe, Nathan; Ferrie, Christopher; Granade, Christopher E. (2012-07-06). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. S2CID 9928389.
Cao, Chenfeng; Hou, Shi-Yao; Cao, Ningping; Zeng, Bei (2020-02-10). "Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates". Journal of Physics: Condensed Matter. 33 (6): 064002. arXiv:2007.05962. doi:10.1088/1361-648x/abc4cf. ISSN 0953-8984. PMID 33105109. S2CID 220496757.
Broecker, Peter; Assaad, Fakher F.; Trebst, Simon (2017-07-03). "Quantum phase recognition via unsupervised machine learning". arXiv:1707.00663 [cond-mat.str-el].
Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter (2018). "Identifying Quantum Phase Transitions with Adversarial Neural Networks". Physical Review B. 97 (13): 134109. arXiv:1710.08382. Bibcode:2018PhRvB..97m4109H. doi:10.1103/PhysRevB.97.134109. ISSN 2469-9950. S2CID 125593239.
Krenn, Mario (2016-01-01). "Automated Search for new Quantum Experiments". Physical Review Letters. 116 (9): 090405. arXiv:1509.02749. Bibcode:2016PhRvL.116i0405K. doi:10.1103/PhysRevLett.116.090405. PMID 26991161. S2CID 20182586.
Knott, Paul (2016-03-22). "A search algorithm for quantum state engineering and metrology". New Journal of Physics. 18 (7): 073033. arXiv:1511.05327. Bibcode:2016NJPh...18g3033K. doi:10.1088/1367-2630/18/7/073033. S2CID 2721958.
Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Melnikov, Alexey A.; Nautrup, Hendrik Poulsen; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J. (1221). "Active learning machine learns to create new quantum experiments". Proceedings of the National Academy of Sciences. 115 (6): 1221–1226. arXiv:1706.00868. doi:10.1073/pnas.1714936115. ISSN 0027-8424. PMC 5819408. PMID 29348200.
Carleo, Giuseppe; Troyer, Matthias (2017-02-09). "Solving the quantum many-body problem with artificial neural networks". Science. 355 (6325): 602–606. arXiv:1606.02318. Bibcode:2017Sci...355..602C. doi:10.1126/science.aag2302. PMID 28183973. S2CID 206651104.
Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Raúl; Bagan, Emilio (2012). "Quantum learning without quantum memory". Scientific Reports. 2: 708. arXiv:1106.2742. Bibcode:2012NatSR...2..708S. doi:10.1038/srep00708. PMC 3464493. PMID 23050092.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David (2014). "Quantum Hamiltonian learning using imperfect quantum resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/physreva.89.042314. hdl:10453/118943. S2CID 55126023.
Bisio, Alessandro; Chiribella, Giulio; D'Ariano, Giacomo Mauro; Facchini, Stefano; Perinotti, Paolo (2010). "Optimal quantum learning of a unitary transformation". Physical Review A. 81 (3): 032324. arXiv:0903.0543. Bibcode:2010PhRvA..81c2324B. doi:10.1103/PhysRevA.81.032324. S2CID 119289138.
Jeongho; Junghee Ryu, Bang; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung (2014). "A strategy for quantum algorithm design assisted by machine learning". New Journal of Physics. 16 (1): 073017. arXiv:1304.2169. Bibcode:2014NJPh...16a3017K. doi:10.1088/1367-2630/16/1/013017. S2CID 54494244.
Granade, Christopher E.; Ferrie, Christopher; Wiebe, Nathan; Cory, D. G. (2012-10-03). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. ISSN 1367-2630. S2CID 9928389.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, D. G. (2014). "Hamiltonian Learning and Certification Using Quantum Resources". Physical Review Letters. 112 (19): 190501. arXiv:1309.0876. Bibcode:2014PhRvL.112s0501W. doi:10.1103/PhysRevLett.112.190501. ISSN 0031-9007. PMID 24877920. S2CID 39126228.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David G. (2014-04-17). "Quantum Hamiltonian Learning Using Imperfect Quantum Resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/PhysRevA.89.042314. hdl:10453/118943. ISSN 1050-2947. S2CID 55126023.
Sasaki, Madahide; Carlini, Alberto; Jozsa, Richard (2001). "Quantum Template Matching". Physical Review A. 64 (2): 022317. arXiv:quant-ph/0102020. Bibcode:2001PhRvA..64b2317S. doi:10.1103/PhysRevA.64.022317. S2CID 43413485.
Sasaki, Masahide (2002). "Quantum learning and universal quantum matching machine". Physical Review A. 66 (2): 022303. arXiv:quant-ph/0202173. Bibcode:2002PhRvA..66b2303S. doi:10.1103/PhysRevA.66.022303. S2CID 119383508.
Sentís, Gael; Guţă, Mădălin; Adesso, Gerardo (2015-07-09). "Quantum learning of coherent states". EPJ Quantum Technology. 2 (1): 17. arXiv:1410.8700. Bibcode:2015EPJQT...2...17S. doi:10.1140/epjqt/s40507-015-0030-4. ISSN 2196-0763. S2CID 6980007.
Lee, Sang Min; Lee, Jinhyoung; Bang, Jeongho (2018-11-02). "Learning unknown pure quantum states". Physical Review A. 98 (5): 052302. arXiv:1805.06580. Bibcode:2018PhRvA..98e2302L. doi:10.1103/PhysRevA.98.052302. S2CID 119095806.
Zahedinejad, Ehsan; Ghosh, Joydip; Sanders, Barry C. (2016-11-16). "Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach". Physical Review Applied. 6 (5): 054005. arXiv:1511.08862. Bibcode:2016PhRvP...6e4005Z. doi:10.1103/PhysRevApplied.6.054005. ISSN 2331-7019. S2CID 7299645.
Ness, Gal; Vainbaum, Anastasiya; Shkedrov, Constantine; Florshaim, Yanay; Sagi, Yoav (2020-07-06). "Single-exposure absorption imaging of ultracold atoms using deep learning". Physical Review Applied. 14 (1): 014011. arXiv:2003.01643. Bibcode:2020PhRvP..14a4011N. doi:10.1103/PhysRevApplied.14.014011. S2CID 211817864.
Bartok, Albert P.; Payne, Mike C.; Risi, Kondor; Csanyi, Gabor (2010). "Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons" (PDF). Physical Review Letters. 104 (13): 136403. arXiv:0910.1019. Bibcode:2010PhRvL.104m6403B. doi:10.1103/PhysRevLett.104.136403. PMID 20481899. S2CID 15918457.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O. Anatole (2012-01-31). "Fast and Accurate Modeling of Molecular Atomization Energies With Machine Learning". Physical Review Letters. 355 (6325): 602. arXiv:1109.2618. Bibcode:2012PhRvL.108e8301R. doi:10.1103/PhysRevLett.108.058301. PMID 22400967. S2CID 321566.
Xia, Rongxin; Kais, Sabre (2018-10-10). "Quantum machine learning for electronic structure calculations". Nature Communications. 9 (1): 4195. arXiv:1803.10296. Bibcode:2018NatCo...9.4195X. doi:10.1038/s41467-018-06598-z. PMC 6180079. PMID 30305624.
van Nieuwenburg, Evert; Liu, Ye-Hua; Huber, Sebastian (2017). "Learning phase transitions by confusion". Nature Physics. 13 (5): 435. arXiv:1610.02048. Bibcode:2017NatPh..13..435V. doi:10.1038/nphys4037. S2CID 119285403.
Hentschel, Alexander (2010-01-01). "Machine Learning for Precise Quantum Measurement". Physical Review Letters. 104 (6): 063603. arXiv:0910.0762. Bibcode:2010PhRvL.104f3603H. doi:10.1103/PhysRevLett.104.063603. PMID 20366821. S2CID 14689659.
Quek, Yihui; Fort, Stanislav; Ng, Hui Khoon (2018-12-17). "Adaptive Quantum State Tomography with Neural Networks". arXiv:1812.06693 [quant-ph].
Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott (2017). "Deep Learning Beyond Lefschetz Thimbles". Physical Review D. 96 (9): 094505. arXiv:1709.01971. Bibcode:2017PhRvD..96i4505A. doi:10.1103/PhysRevD.96.094505. S2CID 119074823.

caltech.edu

authors.library.caltech.edu

Bartok, Albert P.; Payne, Mike C.; Risi, Kondor; Csanyi, Gabor (2010). "Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons" (PDF). Physical Review Letters. 104 (13): 136403. arXiv:0910.1019. Bibcode:2010PhRvL.104m6403B. doi:10.1103/PhysRevLett.104.136403. PMID 20481899. S2CID 15918457.

doi.org

Torlai, Giacomo; Mazzola, Guglielmo; Carrasquilla, Juan; Troyer, Matthias; Melko, Roger; Carleo, Giuseppe (May 2018). "Neural-network quantum state tomography". Nature Physics. 14 (5): 447–450. arXiv:1703.05334. Bibcode:2018NatPh..14..447T. doi:10.1038/s41567-018-0048-5. ISSN 1745-2481. S2CID 125415859.
Cory, D. G.; Wiebe, Nathan; Ferrie, Christopher; Granade, Christopher E. (2012-07-06). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. S2CID 9928389.
Cao, Chenfeng; Hou, Shi-Yao; Cao, Ningping; Zeng, Bei (2020-02-10). "Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates". Journal of Physics: Condensed Matter. 33 (6): 064002. arXiv:2007.05962. doi:10.1088/1361-648x/abc4cf. ISSN 0953-8984. PMID 33105109. S2CID 220496757.
Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter (2018). "Identifying Quantum Phase Transitions with Adversarial Neural Networks". Physical Review B. 97 (13): 134109. arXiv:1710.08382. Bibcode:2018PhRvB..97m4109H. doi:10.1103/PhysRevB.97.134109. ISSN 2469-9950. S2CID 125593239.
Krenn, Mario (2016-01-01). "Automated Search for new Quantum Experiments". Physical Review Letters. 116 (9): 090405. arXiv:1509.02749. Bibcode:2016PhRvL.116i0405K. doi:10.1103/PhysRevLett.116.090405. PMID 26991161. S2CID 20182586.
Knott, Paul (2016-03-22). "A search algorithm for quantum state engineering and metrology". New Journal of Physics. 18 (7): 073033. arXiv:1511.05327. Bibcode:2016NJPh...18g3033K. doi:10.1088/1367-2630/18/7/073033. S2CID 2721958.
Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Melnikov, Alexey A.; Nautrup, Hendrik Poulsen; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J. (1221). "Active learning machine learns to create new quantum experiments". Proceedings of the National Academy of Sciences. 115 (6): 1221–1226. arXiv:1706.00868. doi:10.1073/pnas.1714936115. ISSN 0027-8424. PMC 5819408. PMID 29348200.
Behler, Jörg; Parrinello, Michele (2007-04-02). "Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces". Physical Review Letters. 98 (14): 146401. Bibcode:2007PhRvL..98n6401B. doi:10.1103/PhysRevLett.98.146401. PMID 17501293.
Carleo, Giuseppe; Troyer, Matthias (2017-02-09). "Solving the quantum many-body problem with artificial neural networks". Science. 355 (6325): 602–606. arXiv:1606.02318. Bibcode:2017Sci...355..602C. doi:10.1126/science.aag2302. PMID 28183973. S2CID 206651104.
Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Raúl; Bagan, Emilio (2012). "Quantum learning without quantum memory". Scientific Reports. 2: 708. arXiv:1106.2742. Bibcode:2012NatSR...2..708S. doi:10.1038/srep00708. PMC 3464493. PMID 23050092.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David (2014). "Quantum Hamiltonian learning using imperfect quantum resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/physreva.89.042314. hdl:10453/118943. S2CID 55126023.
Bisio, Alessandro; Chiribella, Giulio; D'Ariano, Giacomo Mauro; Facchini, Stefano; Perinotti, Paolo (2010). "Optimal quantum learning of a unitary transformation". Physical Review A. 81 (3): 032324. arXiv:0903.0543. Bibcode:2010PhRvA..81c2324B. doi:10.1103/PhysRevA.81.032324. S2CID 119289138.
Jeongho; Junghee Ryu, Bang; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung (2014). "A strategy for quantum algorithm design assisted by machine learning". New Journal of Physics. 16 (1): 073017. arXiv:1304.2169. Bibcode:2014NJPh...16a3017K. doi:10.1088/1367-2630/16/1/013017. S2CID 54494244.
Granade, Christopher E.; Ferrie, Christopher; Wiebe, Nathan; Cory, D. G. (2012-10-03). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. ISSN 1367-2630. S2CID 9928389.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, D. G. (2014). "Hamiltonian Learning and Certification Using Quantum Resources". Physical Review Letters. 112 (19): 190501. arXiv:1309.0876. Bibcode:2014PhRvL.112s0501W. doi:10.1103/PhysRevLett.112.190501. ISSN 0031-9007. PMID 24877920. S2CID 39126228.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David G. (2014-04-17). "Quantum Hamiltonian Learning Using Imperfect Quantum Resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/PhysRevA.89.042314. hdl:10453/118943. ISSN 1050-2947. S2CID 55126023.
Sasaki, Madahide; Carlini, Alberto; Jozsa, Richard (2001). "Quantum Template Matching". Physical Review A. 64 (2): 022317. arXiv:quant-ph/0102020. Bibcode:2001PhRvA..64b2317S. doi:10.1103/PhysRevA.64.022317. S2CID 43413485.
Sasaki, Masahide (2002). "Quantum learning and universal quantum matching machine". Physical Review A. 66 (2): 022303. arXiv:quant-ph/0202173. Bibcode:2002PhRvA..66b2303S. doi:10.1103/PhysRevA.66.022303. S2CID 119383508.
Sentís, Gael; Guţă, Mădălin; Adesso, Gerardo (2015-07-09). "Quantum learning of coherent states". EPJ Quantum Technology. 2 (1): 17. arXiv:1410.8700. Bibcode:2015EPJQT...2...17S. doi:10.1140/epjqt/s40507-015-0030-4. ISSN 2196-0763. S2CID 6980007.
Lee, Sang Min; Lee, Jinhyoung; Bang, Jeongho (2018-11-02). "Learning unknown pure quantum states". Physical Review A. 98 (5): 052302. arXiv:1805.06580. Bibcode:2018PhRvA..98e2302L. doi:10.1103/PhysRevA.98.052302. S2CID 119095806.
Zahedinejad, Ehsan; Ghosh, Joydip; Sanders, Barry C. (2016-11-16). "Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach". Physical Review Applied. 6 (5): 054005. arXiv:1511.08862. Bibcode:2016PhRvP...6e4005Z. doi:10.1103/PhysRevApplied.6.054005. ISSN 2331-7019. S2CID 7299645.
Banchi, Leonardo; Pancotti, Nicola; Bose, Sougato (2016-07-19). "Quantum gate learning in qubit networks: Toffoli gate without time-dependent control". npj Quantum Information. 2 (1): 16019. Bibcode:2016npjQI...216019B. doi:10.1038/npjqi.2016.19. hdl:11858/00-001M-0000-002C-AA64-F.
Ness, Gal; Vainbaum, Anastasiya; Shkedrov, Constantine; Florshaim, Yanay; Sagi, Yoav (2020-07-06). "Single-exposure absorption imaging of ultracold atoms using deep learning". Physical Review Applied. 14 (1): 014011. arXiv:2003.01643. Bibcode:2020PhRvP..14a4011N. doi:10.1103/PhysRevApplied.14.014011. S2CID 211817864.
von Lilienfeld, O. Anatole (2018-04-09). "Quantum Machine Learning in Chemical Compound Space". Angewandte Chemie International Edition. 57 (16): 4164–4169. doi:10.1002/anie.201709686. PMID 29216413.
Bartok, Albert P.; Payne, Mike C.; Risi, Kondor; Csanyi, Gabor (2010). "Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons" (PDF). Physical Review Letters. 104 (13): 136403. arXiv:0910.1019. Bibcode:2010PhRvL.104m6403B. doi:10.1103/PhysRevLett.104.136403. PMID 20481899. S2CID 15918457.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O. Anatole (2012-01-31). "Fast and Accurate Modeling of Molecular Atomization Energies With Machine Learning". Physical Review Letters. 355 (6325): 602. arXiv:1109.2618. Bibcode:2012PhRvL.108e8301R. doi:10.1103/PhysRevLett.108.058301. PMID 22400967. S2CID 321566.
Xia, Rongxin; Kais, Sabre (2018-10-10). "Quantum machine learning for electronic structure calculations". Nature Communications. 9 (1): 4195. arXiv:1803.10296. Bibcode:2018NatCo...9.4195X. doi:10.1038/s41467-018-06598-z. PMC 6180079. PMID 30305624.
van Nieuwenburg, Evert; Liu, Ye-Hua; Huber, Sebastian (2017). "Learning phase transitions by confusion". Nature Physics. 13 (5): 435. arXiv:1610.02048. Bibcode:2017NatPh..13..435V. doi:10.1038/nphys4037. S2CID 119285403.
Hentschel, Alexander (2010-01-01). "Machine Learning for Precise Quantum Measurement". Physical Review Letters. 104 (6): 063603. arXiv:0910.0762. Bibcode:2010PhRvL.104f3603H. doi:10.1103/PhysRevLett.104.063603. PMID 20366821. S2CID 14689659.
Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott (2017). "Deep Learning Beyond Lefschetz Thimbles". Physical Review D. 96 (9): 094505. arXiv:1709.01971. Bibcode:2017PhRvD..96i4505A. doi:10.1103/PhysRevD.96.094505. S2CID 119074823.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Piloto, Luis S.; Weinstein, Ari; Battaglia, Peter; Botvinick, Matthew (11 July 2022). "Intuitive physics learning in a deep-learning model inspired by developmental psychology". Nature Human Behaviour. 6 (9): 1257–1267. doi:10.1038/s41562-022-01394-8. ISSN 2397-3374. PMC 9489531. PMID 35817932.
Chen, Boyuan; Huang, Kuang; Raghupathi, Sunand; Chandratreya, Ishaan; Du, Qiang; Lipson, Hod (July 2022). "Automated discovery of fundamental variables hidden in experimental data". Nature Computational Science. 2 (7): 433–442. doi:10.1038/s43588-022-00281-6. ISSN 2662-8457. PMID 38177869. S2CID 251087119.

handle.net

hdl.handle.net

Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David (2014). "Quantum Hamiltonian learning using imperfect quantum resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/physreva.89.042314. hdl:10453/118943. S2CID 55126023.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David G. (2014-04-17). "Quantum Hamiltonian Learning Using Imperfect Quantum Resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/PhysRevA.89.042314. hdl:10453/118943. ISSN 1050-2947. S2CID 55126023.
Banchi, Leonardo; Pancotti, Nicola; Bose, Sougato (2016-07-19). "Quantum gate learning in qubit networks: Toffoli gate without time-dependent control". npj Quantum Information. 2 (1): 16019. Bibcode:2016npjQI...216019B. doi:10.1038/npjqi.2016.19. hdl:11858/00-001M-0000-002C-AA64-F.

harvard.edu

ui.adsabs.harvard.edu

Torlai, Giacomo; Mazzola, Guglielmo; Carrasquilla, Juan; Troyer, Matthias; Melko, Roger; Carleo, Giuseppe (May 2018). "Neural-network quantum state tomography". Nature Physics. 14 (5): 447–450. arXiv:1703.05334. Bibcode:2018NatPh..14..447T. doi:10.1038/s41567-018-0048-5. ISSN 1745-2481. S2CID 125415859.
Cory, D. G.; Wiebe, Nathan; Ferrie, Christopher; Granade, Christopher E. (2012-07-06). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. S2CID 9928389.
Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter (2018). "Identifying Quantum Phase Transitions with Adversarial Neural Networks". Physical Review B. 97 (13): 134109. arXiv:1710.08382. Bibcode:2018PhRvB..97m4109H. doi:10.1103/PhysRevB.97.134109. ISSN 2469-9950. S2CID 125593239.
Krenn, Mario (2016-01-01). "Automated Search for new Quantum Experiments". Physical Review Letters. 116 (9): 090405. arXiv:1509.02749. Bibcode:2016PhRvL.116i0405K. doi:10.1103/PhysRevLett.116.090405. PMID 26991161. S2CID 20182586.
Knott, Paul (2016-03-22). "A search algorithm for quantum state engineering and metrology". New Journal of Physics. 18 (7): 073033. arXiv:1511.05327. Bibcode:2016NJPh...18g3033K. doi:10.1088/1367-2630/18/7/073033. S2CID 2721958.
Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Behler, Jörg; Parrinello, Michele (2007-04-02). "Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces". Physical Review Letters. 98 (14): 146401. Bibcode:2007PhRvL..98n6401B. doi:10.1103/PhysRevLett.98.146401. PMID 17501293.
Carleo, Giuseppe; Troyer, Matthias (2017-02-09). "Solving the quantum many-body problem with artificial neural networks". Science. 355 (6325): 602–606. arXiv:1606.02318. Bibcode:2017Sci...355..602C. doi:10.1126/science.aag2302. PMID 28183973. S2CID 206651104.
Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Raúl; Bagan, Emilio (2012). "Quantum learning without quantum memory". Scientific Reports. 2: 708. arXiv:1106.2742. Bibcode:2012NatSR...2..708S. doi:10.1038/srep00708. PMC 3464493. PMID 23050092.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David (2014). "Quantum Hamiltonian learning using imperfect quantum resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/physreva.89.042314. hdl:10453/118943. S2CID 55126023.
Bisio, Alessandro; Chiribella, Giulio; D'Ariano, Giacomo Mauro; Facchini, Stefano; Perinotti, Paolo (2010). "Optimal quantum learning of a unitary transformation". Physical Review A. 81 (3): 032324. arXiv:0903.0543. Bibcode:2010PhRvA..81c2324B. doi:10.1103/PhysRevA.81.032324. S2CID 119289138.
Jeongho; Junghee Ryu, Bang; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung (2014). "A strategy for quantum algorithm design assisted by machine learning". New Journal of Physics. 16 (1): 073017. arXiv:1304.2169. Bibcode:2014NJPh...16a3017K. doi:10.1088/1367-2630/16/1/013017. S2CID 54494244.
Granade, Christopher E.; Ferrie, Christopher; Wiebe, Nathan; Cory, D. G. (2012-10-03). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. ISSN 1367-2630. S2CID 9928389.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, D. G. (2014). "Hamiltonian Learning and Certification Using Quantum Resources". Physical Review Letters. 112 (19): 190501. arXiv:1309.0876. Bibcode:2014PhRvL.112s0501W. doi:10.1103/PhysRevLett.112.190501. ISSN 0031-9007. PMID 24877920. S2CID 39126228.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David G. (2014-04-17). "Quantum Hamiltonian Learning Using Imperfect Quantum Resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/PhysRevA.89.042314. hdl:10453/118943. ISSN 1050-2947. S2CID 55126023.
Sasaki, Madahide; Carlini, Alberto; Jozsa, Richard (2001). "Quantum Template Matching". Physical Review A. 64 (2): 022317. arXiv:quant-ph/0102020. Bibcode:2001PhRvA..64b2317S. doi:10.1103/PhysRevA.64.022317. S2CID 43413485.
Sasaki, Masahide (2002). "Quantum learning and universal quantum matching machine". Physical Review A. 66 (2): 022303. arXiv:quant-ph/0202173. Bibcode:2002PhRvA..66b2303S. doi:10.1103/PhysRevA.66.022303. S2CID 119383508.
Sentís, Gael; Guţă, Mădălin; Adesso, Gerardo (2015-07-09). "Quantum learning of coherent states". EPJ Quantum Technology. 2 (1): 17. arXiv:1410.8700. Bibcode:2015EPJQT...2...17S. doi:10.1140/epjqt/s40507-015-0030-4. ISSN 2196-0763. S2CID 6980007.
Lee, Sang Min; Lee, Jinhyoung; Bang, Jeongho (2018-11-02). "Learning unknown pure quantum states". Physical Review A. 98 (5): 052302. arXiv:1805.06580. Bibcode:2018PhRvA..98e2302L. doi:10.1103/PhysRevA.98.052302. S2CID 119095806.
Zahedinejad, Ehsan; Ghosh, Joydip; Sanders, Barry C. (2016-11-16). "Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach". Physical Review Applied. 6 (5): 054005. arXiv:1511.08862. Bibcode:2016PhRvP...6e4005Z. doi:10.1103/PhysRevApplied.6.054005. ISSN 2331-7019. S2CID 7299645.
Banchi, Leonardo; Pancotti, Nicola; Bose, Sougato (2016-07-19). "Quantum gate learning in qubit networks: Toffoli gate without time-dependent control". npj Quantum Information. 2 (1): 16019. Bibcode:2016npjQI...216019B. doi:10.1038/npjqi.2016.19. hdl:11858/00-001M-0000-002C-AA64-F.
Ness, Gal; Vainbaum, Anastasiya; Shkedrov, Constantine; Florshaim, Yanay; Sagi, Yoav (2020-07-06). "Single-exposure absorption imaging of ultracold atoms using deep learning". Physical Review Applied. 14 (1): 014011. arXiv:2003.01643. Bibcode:2020PhRvP..14a4011N. doi:10.1103/PhysRevApplied.14.014011. S2CID 211817864.
Bartok, Albert P.; Payne, Mike C.; Risi, Kondor; Csanyi, Gabor (2010). "Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons" (PDF). Physical Review Letters. 104 (13): 136403. arXiv:0910.1019. Bibcode:2010PhRvL.104m6403B. doi:10.1103/PhysRevLett.104.136403. PMID 20481899. S2CID 15918457.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O. Anatole (2012-01-31). "Fast and Accurate Modeling of Molecular Atomization Energies With Machine Learning". Physical Review Letters. 355 (6325): 602. arXiv:1109.2618. Bibcode:2012PhRvL.108e8301R. doi:10.1103/PhysRevLett.108.058301. PMID 22400967. S2CID 321566.
Xia, Rongxin; Kais, Sabre (2018-10-10). "Quantum machine learning for electronic structure calculations". Nature Communications. 9 (1): 4195. arXiv:1803.10296. Bibcode:2018NatCo...9.4195X. doi:10.1038/s41467-018-06598-z. PMC 6180079. PMID 30305624.
van Nieuwenburg, Evert; Liu, Ye-Hua; Huber, Sebastian (2017). "Learning phase transitions by confusion". Nature Physics. 13 (5): 435. arXiv:1610.02048. Bibcode:2017NatPh..13..435V. doi:10.1038/nphys4037. S2CID 119285403.
Hentschel, Alexander (2010-01-01). "Machine Learning for Precise Quantum Measurement". Physical Review Letters. 104 (6): 063603. arXiv:0910.0762. Bibcode:2010PhRvL.104f3603H. doi:10.1103/PhysRevLett.104.063603. PMID 20366821. S2CID 14689659.
Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott (2017). "Deep Learning Beyond Lefschetz Thimbles". Physical Review D. 96 (9): 094505. arXiv:1709.01971. Bibcode:2017PhRvD..96i4505A. doi:10.1103/PhysRevD.96.094505. S2CID 119074823.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.

medium.com

Schuld, Maria (2018-06-12). "Quantum Machine Learning 1.0". XanaduAI. Retrieved 2018-12-07.

newscientist.com

"DeepMind AI learns physics by watching videos that don't make sense". New Scientist. Retrieved 21 August 2022.

nih.gov

pubmed.ncbi.nlm.nih.gov

Cao, Chenfeng; Hou, Shi-Yao; Cao, Ningping; Zeng, Bei (2020-02-10). "Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates". Journal of Physics: Condensed Matter. 33 (6): 064002. arXiv:2007.05962. doi:10.1088/1361-648x/abc4cf. ISSN 0953-8984. PMID 33105109. S2CID 220496757.
Krenn, Mario (2016-01-01). "Automated Search for new Quantum Experiments". Physical Review Letters. 116 (9): 090405. arXiv:1509.02749. Bibcode:2016PhRvL.116i0405K. doi:10.1103/PhysRevLett.116.090405. PMID 26991161. S2CID 20182586.
Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Melnikov, Alexey A.; Nautrup, Hendrik Poulsen; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J. (1221). "Active learning machine learns to create new quantum experiments". Proceedings of the National Academy of Sciences. 115 (6): 1221–1226. arXiv:1706.00868. doi:10.1073/pnas.1714936115. ISSN 0027-8424. PMC 5819408. PMID 29348200.
Behler, Jörg; Parrinello, Michele (2007-04-02). "Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces". Physical Review Letters. 98 (14): 146401. Bibcode:2007PhRvL..98n6401B. doi:10.1103/PhysRevLett.98.146401. PMID 17501293.
Carleo, Giuseppe; Troyer, Matthias (2017-02-09). "Solving the quantum many-body problem with artificial neural networks". Science. 355 (6325): 602–606. arXiv:1606.02318. Bibcode:2017Sci...355..602C. doi:10.1126/science.aag2302. PMID 28183973. S2CID 206651104.
Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Raúl; Bagan, Emilio (2012). "Quantum learning without quantum memory". Scientific Reports. 2: 708. arXiv:1106.2742. Bibcode:2012NatSR...2..708S. doi:10.1038/srep00708. PMC 3464493. PMID 23050092.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, D. G. (2014). "Hamiltonian Learning and Certification Using Quantum Resources". Physical Review Letters. 112 (19): 190501. arXiv:1309.0876. Bibcode:2014PhRvL.112s0501W. doi:10.1103/PhysRevLett.112.190501. ISSN 0031-9007. PMID 24877920. S2CID 39126228.
von Lilienfeld, O. Anatole (2018-04-09). "Quantum Machine Learning in Chemical Compound Space". Angewandte Chemie International Edition. 57 (16): 4164–4169. doi:10.1002/anie.201709686. PMID 29216413.
Bartok, Albert P.; Payne, Mike C.; Risi, Kondor; Csanyi, Gabor (2010). "Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons" (PDF). Physical Review Letters. 104 (13): 136403. arXiv:0910.1019. Bibcode:2010PhRvL.104m6403B. doi:10.1103/PhysRevLett.104.136403. PMID 20481899. S2CID 15918457.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O. Anatole (2012-01-31). "Fast and Accurate Modeling of Molecular Atomization Energies With Machine Learning". Physical Review Letters. 355 (6325): 602. arXiv:1109.2618. Bibcode:2012PhRvL.108e8301R. doi:10.1103/PhysRevLett.108.058301. PMID 22400967. S2CID 321566.
Xia, Rongxin; Kais, Sabre (2018-10-10). "Quantum machine learning for electronic structure calculations". Nature Communications. 9 (1): 4195. arXiv:1803.10296. Bibcode:2018NatCo...9.4195X. doi:10.1038/s41467-018-06598-z. PMC 6180079. PMID 30305624.
Hentschel, Alexander (2010-01-01). "Machine Learning for Precise Quantum Measurement". Physical Review Letters. 104 (6): 063603. arXiv:0910.0762. Bibcode:2010PhRvL.104f3603H. doi:10.1103/PhysRevLett.104.063603. PMID 20366821. S2CID 14689659.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Piloto, Luis S.; Weinstein, Ari; Battaglia, Peter; Botvinick, Matthew (11 July 2022). "Intuitive physics learning in a deep-learning model inspired by developmental psychology". Nature Human Behaviour. 6 (9): 1257–1267. doi:10.1038/s41562-022-01394-8. ISSN 2397-3374. PMC 9489531. PMID 35817932.
Chen, Boyuan; Huang, Kuang; Raghupathi, Sunand; Chandratreya, Ishaan; Du, Qiang; Lipson, Hod (July 2022). "Automated discovery of fundamental variables hidden in experimental data". Nature Computational Science. 2 (7): 433–442. doi:10.1038/s43588-022-00281-6. ISSN 2662-8457. PMID 38177869. S2CID 251087119.

ncbi.nlm.nih.gov

Melnikov, Alexey A.; Nautrup, Hendrik Poulsen; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J. (1221). "Active learning machine learns to create new quantum experiments". Proceedings of the National Academy of Sciences. 115 (6): 1221–1226. arXiv:1706.00868. doi:10.1073/pnas.1714936115. ISSN 0027-8424. PMC 5819408. PMID 29348200.
Sentís, Gael; Calsamiglia, John; Muñoz-Tapia, Raúl; Bagan, Emilio (2012). "Quantum learning without quantum memory". Scientific Reports. 2: 708. arXiv:1106.2742. Bibcode:2012NatSR...2..708S. doi:10.1038/srep00708. PMC 3464493. PMID 23050092.
Xia, Rongxin; Kais, Sabre (2018-10-10). "Quantum machine learning for electronic structure calculations". Nature Communications. 9 (1): 4195. arXiv:1803.10296. Bibcode:2018NatCo...9.4195X. doi:10.1038/s41467-018-06598-z. PMC 6180079. PMID 30305624.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Piloto, Luis S.; Weinstein, Ari; Battaglia, Peter; Botvinick, Matthew (11 July 2022). "Intuitive physics learning in a deep-learning model inspired by developmental psychology". Nature Human Behaviour. 6 (9): 1257–1267. doi:10.1038/s41562-022-01394-8. ISSN 2397-3374. PMC 9489531. PMID 35817932.

osti.gov

Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.

qmlt.readthedocs.io

"Variational Circuits — Quantum Machine Learning Toolbox 0.7.1 documentation". qmlt.readthedocs.io. Retrieved 2018-12-06.

semanticscholar.org

api.semanticscholar.org

Torlai, Giacomo; Mazzola, Guglielmo; Carrasquilla, Juan; Troyer, Matthias; Melko, Roger; Carleo, Giuseppe (May 2018). "Neural-network quantum state tomography". Nature Physics. 14 (5): 447–450. arXiv:1703.05334. Bibcode:2018NatPh..14..447T. doi:10.1038/s41567-018-0048-5. ISSN 1745-2481. S2CID 125415859.
Cory, D. G.; Wiebe, Nathan; Ferrie, Christopher; Granade, Christopher E. (2012-07-06). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. S2CID 9928389.
Cao, Chenfeng; Hou, Shi-Yao; Cao, Ningping; Zeng, Bei (2020-02-10). "Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates". Journal of Physics: Condensed Matter. 33 (6): 064002. arXiv:2007.05962. doi:10.1088/1361-648x/abc4cf. ISSN 0953-8984. PMID 33105109. S2CID 220496757.
Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter (2018). "Identifying Quantum Phase Transitions with Adversarial Neural Networks". Physical Review B. 97 (13): 134109. arXiv:1710.08382. Bibcode:2018PhRvB..97m4109H. doi:10.1103/PhysRevB.97.134109. ISSN 2469-9950. S2CID 125593239.
Krenn, Mario (2016-01-01). "Automated Search for new Quantum Experiments". Physical Review Letters. 116 (9): 090405. arXiv:1509.02749. Bibcode:2016PhRvL.116i0405K. doi:10.1103/PhysRevLett.116.090405. PMID 26991161. S2CID 20182586.
Knott, Paul (2016-03-22). "A search algorithm for quantum state engineering and metrology". New Journal of Physics. 18 (7): 073033. arXiv:1511.05327. Bibcode:2016NJPh...18g3033K. doi:10.1088/1367-2630/18/7/073033. S2CID 2721958.
Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Carleo, Giuseppe; Troyer, Matthias (2017-02-09). "Solving the quantum many-body problem with artificial neural networks". Science. 355 (6325): 602–606. arXiv:1606.02318. Bibcode:2017Sci...355..602C. doi:10.1126/science.aag2302. PMID 28183973. S2CID 206651104.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David (2014). "Quantum Hamiltonian learning using imperfect quantum resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/physreva.89.042314. hdl:10453/118943. S2CID 55126023.
Bisio, Alessandro; Chiribella, Giulio; D'Ariano, Giacomo Mauro; Facchini, Stefano; Perinotti, Paolo (2010). "Optimal quantum learning of a unitary transformation". Physical Review A. 81 (3): 032324. arXiv:0903.0543. Bibcode:2010PhRvA..81c2324B. doi:10.1103/PhysRevA.81.032324. S2CID 119289138.
Jeongho; Junghee Ryu, Bang; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung (2014). "A strategy for quantum algorithm design assisted by machine learning". New Journal of Physics. 16 (1): 073017. arXiv:1304.2169. Bibcode:2014NJPh...16a3017K. doi:10.1088/1367-2630/16/1/013017. S2CID 54494244.
Granade, Christopher E.; Ferrie, Christopher; Wiebe, Nathan; Cory, D. G. (2012-10-03). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. ISSN 1367-2630. S2CID 9928389.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, D. G. (2014). "Hamiltonian Learning and Certification Using Quantum Resources". Physical Review Letters. 112 (19): 190501. arXiv:1309.0876. Bibcode:2014PhRvL.112s0501W. doi:10.1103/PhysRevLett.112.190501. ISSN 0031-9007. PMID 24877920. S2CID 39126228.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David G. (2014-04-17). "Quantum Hamiltonian Learning Using Imperfect Quantum Resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/PhysRevA.89.042314. hdl:10453/118943. ISSN 1050-2947. S2CID 55126023.
Sasaki, Madahide; Carlini, Alberto; Jozsa, Richard (2001). "Quantum Template Matching". Physical Review A. 64 (2): 022317. arXiv:quant-ph/0102020. Bibcode:2001PhRvA..64b2317S. doi:10.1103/PhysRevA.64.022317. S2CID 43413485.
Sasaki, Masahide (2002). "Quantum learning and universal quantum matching machine". Physical Review A. 66 (2): 022303. arXiv:quant-ph/0202173. Bibcode:2002PhRvA..66b2303S. doi:10.1103/PhysRevA.66.022303. S2CID 119383508.
Sentís, Gael; Guţă, Mădălin; Adesso, Gerardo (2015-07-09). "Quantum learning of coherent states". EPJ Quantum Technology. 2 (1): 17. arXiv:1410.8700. Bibcode:2015EPJQT...2...17S. doi:10.1140/epjqt/s40507-015-0030-4. ISSN 2196-0763. S2CID 6980007.
Lee, Sang Min; Lee, Jinhyoung; Bang, Jeongho (2018-11-02). "Learning unknown pure quantum states". Physical Review A. 98 (5): 052302. arXiv:1805.06580. Bibcode:2018PhRvA..98e2302L. doi:10.1103/PhysRevA.98.052302. S2CID 119095806.
Zahedinejad, Ehsan; Ghosh, Joydip; Sanders, Barry C. (2016-11-16). "Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach". Physical Review Applied. 6 (5): 054005. arXiv:1511.08862. Bibcode:2016PhRvP...6e4005Z. doi:10.1103/PhysRevApplied.6.054005. ISSN 2331-7019. S2CID 7299645.
Ness, Gal; Vainbaum, Anastasiya; Shkedrov, Constantine; Florshaim, Yanay; Sagi, Yoav (2020-07-06). "Single-exposure absorption imaging of ultracold atoms using deep learning". Physical Review Applied. 14 (1): 014011. arXiv:2003.01643. Bibcode:2020PhRvP..14a4011N. doi:10.1103/PhysRevApplied.14.014011. S2CID 211817864.
Bartok, Albert P.; Payne, Mike C.; Risi, Kondor; Csanyi, Gabor (2010). "Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons" (PDF). Physical Review Letters. 104 (13): 136403. arXiv:0910.1019. Bibcode:2010PhRvL.104m6403B. doi:10.1103/PhysRevLett.104.136403. PMID 20481899. S2CID 15918457.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O. Anatole (2012-01-31). "Fast and Accurate Modeling of Molecular Atomization Energies With Machine Learning". Physical Review Letters. 355 (6325): 602. arXiv:1109.2618. Bibcode:2012PhRvL.108e8301R. doi:10.1103/PhysRevLett.108.058301. PMID 22400967. S2CID 321566.
van Nieuwenburg, Evert; Liu, Ye-Hua; Huber, Sebastian (2017). "Learning phase transitions by confusion". Nature Physics. 13 (5): 435. arXiv:1610.02048. Bibcode:2017NatPh..13..435V. doi:10.1038/nphys4037. S2CID 119285403.
Hentschel, Alexander (2010-01-01). "Machine Learning for Precise Quantum Measurement". Physical Review Letters. 104 (6): 063603. arXiv:0910.0762. Bibcode:2010PhRvL.104f3603H. doi:10.1103/PhysRevLett.104.063603. PMID 20366821. S2CID 14689659.
Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott (2017). "Deep Learning Beyond Lefschetz Thimbles". Physical Review D. 96 (9): 094505. arXiv:1709.01971. Bibcode:2017PhRvD..96i4505A. doi:10.1103/PhysRevD.96.094505. S2CID 119074823.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Chen, Boyuan; Huang, Kuang; Raghupathi, Sunand; Chandratreya, Ishaan; Du, Qiang; Lipson, Hod (July 2022). "Automated discovery of fundamental variables hidden in experimental data". Nature Computational Science. 2 (7): 433–442. doi:10.1038/s43588-022-00281-6. ISSN 2662-8457. PMID 38177869. S2CID 251087119.

worldcat.org

search.worldcat.org

Torlai, Giacomo; Mazzola, Guglielmo; Carrasquilla, Juan; Troyer, Matthias; Melko, Roger; Carleo, Giuseppe (May 2018). "Neural-network quantum state tomography". Nature Physics. 14 (5): 447–450. arXiv:1703.05334. Bibcode:2018NatPh..14..447T. doi:10.1038/s41567-018-0048-5. ISSN 1745-2481. S2CID 125415859.
Cao, Chenfeng; Hou, Shi-Yao; Cao, Ningping; Zeng, Bei (2020-02-10). "Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates". Journal of Physics: Condensed Matter. 33 (6): 064002. arXiv:2007.05962. doi:10.1088/1361-648x/abc4cf. ISSN 0953-8984. PMID 33105109. S2CID 220496757.
Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter (2018). "Identifying Quantum Phase Transitions with Adversarial Neural Networks". Physical Review B. 97 (13): 134109. arXiv:1710.08382. Bibcode:2018PhRvB..97m4109H. doi:10.1103/PhysRevB.97.134109. ISSN 2469-9950. S2CID 125593239.
Dunjko, Vedran; Briegel, Hans J (2018-06-19). "Machine learning & artificial intelligence in the quantum domain: a review of recent progress". Reports on Progress in Physics. 81 (7): 074001. arXiv:1709.02779. Bibcode:2018RPPh...81g4001D. doi:10.1088/1361-6633/aab406. hdl:1887/71084. ISSN 0034-4885. PMID 29504942. S2CID 3681629.
Melnikov, Alexey A.; Nautrup, Hendrik Poulsen; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J. (1221). "Active learning machine learns to create new quantum experiments". Proceedings of the National Academy of Sciences. 115 (6): 1221–1226. arXiv:1706.00868. doi:10.1073/pnas.1714936115. ISSN 0027-8424. PMC 5819408. PMID 29348200.
Granade, Christopher E.; Ferrie, Christopher; Wiebe, Nathan; Cory, D. G. (2012-10-03). "Robust Online Hamiltonian Learning". New Journal of Physics. 14 (10): 103013. arXiv:1207.1655. Bibcode:2012NJPh...14j3013G. doi:10.1088/1367-2630/14/10/103013. ISSN 1367-2630. S2CID 9928389.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, D. G. (2014). "Hamiltonian Learning and Certification Using Quantum Resources". Physical Review Letters. 112 (19): 190501. arXiv:1309.0876. Bibcode:2014PhRvL.112s0501W. doi:10.1103/PhysRevLett.112.190501. ISSN 0031-9007. PMID 24877920. S2CID 39126228.
Wiebe, Nathan; Granade, Christopher; Ferrie, Christopher; Cory, David G. (2014-04-17). "Quantum Hamiltonian Learning Using Imperfect Quantum Resources". Physical Review A. 89 (4): 042314. arXiv:1311.5269. Bibcode:2014PhRvA..89d2314W. doi:10.1103/PhysRevA.89.042314. hdl:10453/118943. ISSN 1050-2947. S2CID 55126023.
Sentís, Gael; Guţă, Mădălin; Adesso, Gerardo (2015-07-09). "Quantum learning of coherent states". EPJ Quantum Technology. 2 (1): 17. arXiv:1410.8700. Bibcode:2015EPJQT...2...17S. doi:10.1140/epjqt/s40507-015-0030-4. ISSN 2196-0763. S2CID 6980007.
Zahedinejad, Ehsan; Ghosh, Joydip; Sanders, Barry C. (2016-11-16). "Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach". Physical Review Applied. 6 (5): 054005. arXiv:1511.08862. Bibcode:2016PhRvP...6e4005Z. doi:10.1103/PhysRevApplied.6.054005. ISSN 2331-7019. S2CID 7299645.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Piloto, Luis S.; Weinstein, Ari; Battaglia, Peter; Botvinick, Matthew (11 July 2022). "Intuitive physics learning in a deep-learning model inspired by developmental psychology". Nature Human Behaviour. 6 (9): 1257–1267. doi:10.1038/s41562-022-01394-8. ISSN 2397-3374. PMC 9489531. PMID 35817932.
Chen, Boyuan; Huang, Kuang; Raghupathi, Sunand; Chandratreya, Ishaan; Du, Qiang; Lipson, Hod (July 2022). "Automated discovery of fundamental variables hidden in experimental data". Nature Computational Science. 2 (7): 433–442. doi:10.1038/s43588-022-00281-6. ISSN 2662-8457. PMID 38177869. S2CID 251087119.