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Issue 11, 2024
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On the 90th anniversary of the Lebedev Physics Institute of the Russian Academy of Sciences (LPI). Reviews of topical problems


Quantum memristors: a new approach to neuromorphic computing

†  a, b, ‡  a, b, c,  a, b, §  b, *  b, d
a Lomonosov Moscow State University, Vorobevy Gory, Moscow, 119991, Russian Federation
b Lebedev Physical Institute, Russian Academy of Sciences, Leninsky prosp. 53, Moscow, 119991, Russian Federation
c National Research Centre ‘Kurchatov Institute’, pl. akad. Kurchatova 1, Moscow, 123182, Russian Federation
d International Center for Quantum Optics and Quantum Technologies (the Russian Quantum Center), Skolkovo Innovation Center, Bolshoi Boulevard, Building 30, Block 1, 3rd floor, sectors G3, G7, Moscow, Moscow Region, 121205, Russian Federation

We present a review on quantum memristors, which define a new direction for neuromorphic applications. We discuss the general methodology and concept of constructing a quantum memristor, as well as the possibility of its implementation on photonic platforms, superconducting systems, and ultracold trapped ions. The latter platform is being actively developed at the Lebedev Physical Institute for conducting quantum computations and for building a high-performance quantum computer; it has also proven its worth in creating optical clocks.

Fulltext pdf (503 KB)
Fulltext is also available at DOI: 10.3367/UFNe.2024.06.039698
Keywords: memristors, quantum computing, neuromorphic systems
PACS: 03.67.−a, 42.50.Dv, 85.25.Cp (all)
DOI: 10.3367/UFNe.2024.06.039698
URL: https://ufn.ru/en/articles/2024/9/b/
001343554500003
2-s2.0-85208405312
Citation: Forsh P A, Stremoukhov S Yu, Frolova A S, Khabarova K Yu, Kolachevsky N N "Quantum memristors: a new approach to neuromorphic computing" Phys. Usp. 67 855–865 (2024)
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Received: 21st, May 2024, revised: 19th, June 2024, 22nd, June 2024

Îðèãèíàë: Ôîðø Ï À, Ñòðåìîóõîâ Ñ Þ, Ôðîëîâà À Ñ, Õàáàðîâà Ê Þ, Êîëà÷åâñêèé Í Í «Êâàíòîâûå ìåìðèñòîðû — íîâûé ïîäõîä ê íåéðîìîðôíûì âû÷èñëåíèÿì» ÓÔÍ 194 905–916 (2024); DOI: 10.3367/UFNr.2024.06.039698

References (55) ↓ Similar articles (2)

  1. Chua L IEEE Trans. Circuit Theory 18 507 (1971)
  2. Strukov D B et al Nature 453 80 (2008)
  3. Demin V A, Erokhin V V Int. J. Unconv. Comput. 12 433 (2016)
  4. Abraham I Sci. Rep. 8 10972 (2018)
  5. Borghetti J et al Nature 464 873 (2010)
  6. Linares-Barranco B, Serrano-Gotarredona T "Memristance can explain spike-time-dependent-plasticity in neural synapses" Nat. Prec. (2009)
  7. Alibart F et al Adv. Funct. Mater. 20 330 (2010)
  8. Ielmini D Semicond. Sci. Technol. 31 063002 (2016)
  9. Sun K, Chen J, Yan X Adv. Funct. Mater. 31 2006773 (2021)
  10. Tominov R et al Adv. Electron. Mater. 8 2200215 (2022)
  11. Tominov R V et al Nanoindustriya (15) 509 (2022)
  12. Rylkov V V et al J. Exp. Theor. Phys. 126 353 (2018); Rylkov V V et al Zh. Eksp. Teor. Fiz. 153 424 (2018)
  13. Emelyanov A V et al Microelectron. Eng. 215 110988 (2019)
  14. Yuan L et al Adv. Electron. Mater. 7 2100432 (2021)
  15. van de Burgt Y et al Nat. Electron. 1 386 (2018)
  16. Mu B et al J. Mater. Chem. C 8 12714 (2020)
  17. Park H-L, Lee T-W Org. Electron. 98 106301 (2021)
  18. Lapkin D A et al Appl. Phys. Lett. 112 043302 (2018)
  19. Minnekhanov A A et al Sci. Rep. 9 10800 (2019)
  20. Di Ventra M, Pershin Yu V, Chua L O Proc. IEEE 97 1371 (2009)
  21. Di Ventra M, Pershin Yu V, Chua L O Proc. IEEE 97 1717 (2009)
  22. Jo S H et al Nano Lett. 10 1297 (2010)
  23. Pershin Yu V, Di Ventra M Neural Networks 23 881 (2010)
  24. Pershin Yu V, Di Ventra M Phys. Rev. E 84 046703 (2011)
  25. Yu S et al IEEE Trans. Electron Devices 58 2729 (2011)
  26. Pershin Yu V, Di Ventra M Proc. IEEE 100 2071 (2012)
  27. Thomas A J. Phys. D 46 093001 (2013)
  28. Moon J et al Nat. Electron. 2 480 (2019)
  29. Yao P et al Nature 577 641 (2020)
  30. Chua L O, Kang S M Proc. IEEE 64 209 (1976)
  31. Caravelli F, Carbajal J P Technologies 6 (4) 118 (2018)
  32. Sanz M, Lamata L, Solano E APL Photon. 3 080801 (2018)
  33. Salmilehto J et al Sci. Rep. 7 42044 (2017)
  34. Pfeiffer P et al Sci. Rep. 6 29507 (2016)
  35. Qiu X et al Commun. Mater. 5 70 (2024)
  36. Aksenov M A et al Phys. Rev. A 107 052612 (2023)
  37. Vishnyakova G A et al Phys. Usp. 59 168 (2016); Vishnyakova G A et al Usp. Fiz. Nauk 186 176 (2016)
  38. Khabarova K Yu, Kalganova E S, Kolachevsky N N Phys. Usp. 61 203 (2018); Khabarova K Yu, Kalganova E S, Kolachevsky N N Usp. Fiz. Nauk 188 221 (2018)
  39. Khabarova K Yu, Zalivako I V, Kolachevsky N N Phys. Usp. 65 1217 (2022); Khabarova K Yu, Zalivako I V, Kolachevsky N N Usp. Fiz. Nauk 192 1305 (2022)
  40. Gonzalez-Raya T et al Materials 13 864 (2020)
  41. Kim M S et al Phys. Rev. A 65 032323 (2002)
  42. Spagnolo M et al Nat. Photon. 16 318 (2022)
  43. Norambuena A et al Phys. Rev. Appl. 17 024056 (2022)
  44. Stremoukhov S et al Entropy 25 1134 (2023)
  45. Stremoukhov S Yu et al JETP Lett. 119 352 (2024); Stremoukhov S Yu et al Pis’ma Zh. Eksp. Teor. Fiz. 119 343 (2024)
  46. Vool U et al Phys. Rev. Lett. 113 247001 (2014)
  47. Wiseman H M, Milburn G J Quantum Measurement And Control (Cambridge, UK: Cambridge Univ. Press, 2010)
  48. Jacobs K, Steck D A Contemp. Phys. 47 279 (2006)
  49. Kazmina A S et al Phys. Rev. A 109 032619 (2024)
  50. Jaeger H "The ’echo state’ approach to analysing and training recurrent neural networks — with an Erratum note" GMD Report No. 148 (Bonn: German National Research Institute for Computer Science, 2001)
  51. Maass W, Natschläger T, Markram H Neural Comput. 14 2531 (2002)
  52. Du C et al Nat. Commun. 8 2204 (2017)
  53. Jalalvand A, Van Wallendael G, Van de Walle R, in Proc. of the 7th Intern. Conf. on Computational Intelligence, Communication Systems and Networks, CICSYN 2015, Riga, Latvia, 03-05 June 2015 (Piscataway, NJ: IEEE, 2015) p. 146-151
  54. Penrose R The Emperor’s New Mind: Concerning Computers, Minds, And The Laws Of Physics (Oxford: Oxford Univ. Press, 1989)
  55. Penrose R Shadows Of The Mind: A Search For The Missing Science Of Consciousness (Oxford: Oxford Univ. Press, 1994)
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