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Malajahan mesin kuantum

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Petang pendekatan sane matiosan anggen ngapukang disiplin ilmu komputasi kuantum miwah pembelajaran mesin. [1] [2] Aksara kapertama nyihnayang napike sistem sane kaselehin punika klasik utawi kuantum, nanging aksara kaping kalih nelatarang napike piranti pemrosesan informasi klasik utawi kuantum sane kaanggen.

Malajah mesin kuantum punika integrasi algoritma kuantum ring program pembelajaran mesin. [3] [4] [5] [6] [7] [8] [9] [10]

Kawigunan istilah sane pinih sering manut ring algoritma pembelajaran mesin anggen analisis data klasik sane kalaksanayang ring komputer kuantum, inggih punika pembelajaran mesin sane katincapang kuantum. [11] [12] [13] Rikalaning algoritma pembelajaran mesin kawigunayang anggen ngitung akeh pisan data, pembelajaran mesin kuantum ngawigunayang qubit miwah operasi kuantum utawi sistem kuantum khusus anggen nincapang kecepatan komputasi miwah penyimpanan data sane kamargiang olih algoritma ring program. [14] Puniki rumasuk metode hibrida sane nyarengin pemrosesan klasik miwah kuantum, inggian subrutin sane sukil manut komputasi ka outsource ring perangkat kuantum. [15] [16] [17] Rutinitas puniki prasida madue sifat sane sayan kompleks taler kamargiang sayan gelis ring komputer kuantum. [18] Selanturnyane, algoritma kuantum prasida kawigunayang anggen nyelehin kahanan kuantum gumanti data klasik. [19] [20]

Ring dura komputasi kuantum, istilah "pembelajaran mesin kuantum" taler mapaiketan sareng metode pembelajaran mesin klasik sane kaanggen ring data sane kapolihang saking eksperimen kuantum (inggih punika pembelajaran mesin sistem kuantum ), sekadi malajah transisi fase sistem kuantum [21] [22] utawi ngaryanin eksperimen kuantum anyar. [23] [24] [25]

Pembelajaran mesin kuantum taler nglimbak ring pahan penelitian sane nyelehin kepatehan metodologis miwah struktural inggian sistem fisik miwah sistem pembelajaran, utamanyane jaringan saraf. Sekadi, makudang teknik matematika miwah numerik saking fisika kuantum prasida kamargiang ring pembelajaran mendalam klasik miwah tungkalikannyané. [26] [27] [28]

Selanturnyane, para peneliti nyelehin pikayunan sane pinih abstrak indik teori pembelajaran sane mapaiketan sareng informasi kuantum, wenten sane kabawos pinaka "teori pembelajaran kuantum". [29] [30]

Cingak taler

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Lis pustaka

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  1. ↑ Aïmeur, Esma; Brassard, Gilles; Gambs, Sébastien (2006-06-07). "Machine Learning in a Quantum World". Advances in Artificial Intelligence. Lecture Notes in Computer Science (ring Inggris). 4013. pp. 431–442. doi:10.1007/11766247_37. ISBN 978-3-540-34628-9.
  2. ↑ Dunjko, Vedran; Taylor, Jacob M.; Briegel, Hans J. (2016-09-20). "Quantum-Enhanced Machine Learning". Physical Review Letters. 117 (13): 130501. arXiv:1610.08251. Bibcode:2016PhRvL.117m0501D. doi:10.1103/PhysRevLett.117.130501. PMID 27715099.
  3. ↑ Ventura, Dan (2000). "Quantum Associative Memory". Information Sciences. 124 (1–4): 273–296. arXiv:quant-ph/9807053. doi:10.1016/S0020-0255(99)00101-2.
  4. ↑ Trugenberger, Carlo A. (2001). "Probabilistic Quantum Memories". Physical Review Letters. 87 (6): 067901. arXiv:quant-ph/0012100. Bibcode:2001PhRvL..87f7901T. doi:10.1103/PhysRevLett.87.067901. PMID 11497863.
  5. ↑ Trugenberger, Carlo A. (2002). "Quantum Pattern Recognition". Quantum Information Processing. 1 (6): 471–493. arXiv:quant-ph/0210176. Bibcode:2002QuIP....1..471T. doi:10.1023/A:1024022632303.
  6. ↑ Trugenberger, C. A. (2002-12-19). "Phase Transitions in Quantum Pattern Recognition". Physical Review Letters. 89 (27): 277903. arXiv:quant-ph/0204115. Bibcode:2002PhRvL..89A7903T. doi:10.1103/physrevlett.89.277903. ISSN 0031-9007. PMID 12513243.
  7. ↑ Biamonte, Jacob; Wittek, Peter; Nicola, Pancotti; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth (2017). "Quantum machine learning". Nature. 549 (7671): 195–202. arXiv:1611.09347. Bibcode:2017Natur.549..195B. doi:10.1038/nature23474. PMID 28905917.
  8. ↑ Schuld, Maria; Petruccione, Francesco (2018). Supervised Learning with Quantum Computers. Quantum Science and Technology. Bibcode:2018slqc.book.....S. doi:10.1007/978-3-319-96424-9. ISBN 978-3-319-96423-2.
  9. ↑ Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco (2014). "An introduction to quantum machine learning". Contemporary Physics. 56 (2): 172–185. arXiv:1409.3097. Bibcode:2015ConPh..56..172S. CiteSeerX 10.1.1.740.5622. doi:10.1080/00107514.2014.964942.
  10. ↑ Wittek, Peter (2014). Quantum Machine Learning: What Quantum Computing Means to Data Mining. Academic Press. ISBN 978-0-12-800953-6.
  11. ↑ Wiebe, Nathan; Kapoor, Ashish; Svore, Krysta (2014). "Quantum Algorithms for Nearest-Neighbor Methods for Supervised and Unsupervised Learning". Quantum Information & Computation. 15 (3): 0318–0358. arXiv:1401.2142.
  12. ↑ A bot will complete this citation soon. Click here to jump the queue arXiv:[1].
  13. ↑ Yoo, Seokwon; Bang, Jeongho; Lee, Changhyoup; Lee, Jinhyoung (2014). "A quantum speedup in machine learning: Finding a N-bit Boolean function for a classification". New Journal of Physics. 16 (10): 103014. arXiv:1303.6055. Bibcode:2014NJPh...16j3014Y. doi:10.1088/1367-2630/16/10/103014.
  14. ↑ Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco (2014-10-15). "An introduction to quantum machine learning". Contemporary Physics (ring Inggris). 56 (2): 172–185. arXiv:1409.3097. Bibcode:2015ConPh..56..172S. CiteSeerX 10.1.1.740.5622. doi:10.1080/00107514.2014.964942. ISSN 0010-7514.
  15. ↑ Benedetti, Marcello; Realpe-Gómez, John; Biswas, Rupak; Perdomo-Ortiz, Alejandro (2017-11-30). "Quantum-Assisted Learning of Hardware-Embedded Probabilistic Graphical Models". Physical Review X. 7 (4): 041052. arXiv:1609.02542. Bibcode:2017PhRvX...7d1052B. doi:10.1103/PhysRevX.7.041052. ISSN 2160-3308.
  16. ↑ A bot will complete this citation soon. Click here to jump the queue arXiv:[2].
  17. ↑ Schuld, Maria; Bocharov, Alex; Svore, Krysta; Wiebe, Nathan (2020). "Circuit-centric quantum classifiers". Physical Review A. 101 (3): 032308. arXiv:1804.00633. Bibcode:2020PhRvA.101c2308S. doi:10.1103/PhysRevA.101.032308.
  18. ↑ Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco (2014). "An introduction to quantum machine learning". Contemporary Physics. 56 (2): 172–185. arXiv:1409.3097. Bibcode:2015ConPh..56..172S. CiteSeerX 10.1.1.740.5622. doi:10.1080/00107514.2014.964942.
  19. ↑ Yu, Shang; Albarran-Arriagada, F.; Retamal, J. C.; Wang, Yi-Tao; Liu, Wei; Ke, Zhi-Jin; Meng, Yu; Li, Zhi-Peng; Tang, Jian-Shun (2018-08-28). "Reconstruction of a Photonic Qubit State with Quantum Reinforcement Learning". Advanced Quantum Technologies. 2 (7–8): 1800074. arXiv:1808.09241. doi:10.1002/qute.201800074.
  20. ↑ Ghosh, Sanjib; Opala, A.; Matuszewski, M.; Paterek, T.; Liew, Timothy C. H. (2019). "Quantum reservoir processing". npj Quantum Information. 5: 35. arXiv:1811.10335. Bibcode:2019npjQI...5...35G. doi:10.1038/s41534-019-0149-8.
  21. ↑ A bot will complete this citation soon. Click here to jump the queue arXiv:[3].
  22. ↑ 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.
  23. ↑ 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.
  24. ↑ 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.
  25. ↑ 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. ISSN 0034-4885. PMID 29504942. |hdl-access= requires |hdl= (help)
  26. ↑ Huggins, William; Patel, Piyush; Whaley, K. Birgitta; Stoudenmire, E. Miles (2018-03-30). "Towards Quantum Machine Learning with Tensor Networks". Quantum Science and Technology. 4 (2): 024001. arXiv:1803.11537. doi:10.1088/2058-9565/aaea94.
  27. ↑ Carleo, Giuseppe; Nomura, Yusuke; Imada, Masatoshi (2018-02-26). "Constructing exact representations of quantum many-body systems with deep neural networks". Nature Communications. 9 (1): 5322. arXiv:1802.09558. Bibcode:2018NatCo...9.5322C. doi:10.1038/s41467-018-07520-3. PMC 6294148. PMID 30552316.
  28. ↑ A bot will complete this citation soon. Click here to jump the queue arXiv:[4].
  29. ↑ A bot will complete this citation soon. Click here to jump the queue arXiv:[5].
  30. ↑ Sergioli, Giuseppe; Giuntini, Roberto; Freytes, Hector (2019-05-09). "A new Quantum approach to binary classification". PLOS ONE. 14 (5): e0216224. Bibcode:2019PLoSO..1416224S. doi:10.1371/journal.pone.0216224. PMC 6508868. PMID 31071129.
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