DEVELOPMENT AND STUDY OF A CONTROL MODEL BASED ON NOISE-RESISTANT QUANTUM COMPUTING, SUPPRESSION AND CORRECTION OF ERRORS IN QUANTUM COMPUTING
Abstract
In recent years, quantum information systems have attracted increasing attention of researchers
in the field of computer science and physics. However, the introduction and practical
application of quantum computing is limited by the influence of noise and errors that occur in
quantum systems. To implement effective control and improve the reliability of quantum information
systems, it is necessary to develop methods that can suppress and correct errors in the
process of quantum computing. The purpose of this work is to develop and study a control model
based on noise-immune quantum computing, as well as methods for suppressing and correcting
errors in quantum computing. The paper proposes a combination of different approaches, including
the use of error correction codes, noise suppression algorithms, and methods for optimal control
of quantum information systems. In the course of the study, a control model was developed
that allows efficient processing of information in quantum systems, taking into account the presence
of noise and errors. Experiments were carried out using real quantum devices to evaluate the
effectiveness of the proposed model. The experimental results show that the developed method can
significantly improve the reliability and accuracy of quantum computing. The proposed control
model based on noise-immune quantum computing and methods for suppressing and correcting
errors represent a significant contribution to the development of quantum information systems.
Further development and optimization of the proposed approach can lead to the creation of more
reliable and efficient quantum systems capable of solving complex computational problems.
References
on the Theory of Computing, 1993, pp. 11-20.
2. Kaye F., Laflamm R. Vvedenie v kvantovye vychisleniya [Introduction to Quantum Computing].
Moscow; Izhevsk: RKhD, 2009, 360 p.
3. Phillips D.E., Eleischnauer A., Mair A., Walsworth P.L., Lukin M.D. Storage of light in Atomic
Vapor, Physical Review Letters, Januar 2001, Vol. 86, No. 05.
4. Guzik V., Gushanskiy S., Polenov M., Potapov V. Complexity Estimation of Quantum Algorithms
Using Entanglement Properties, 16th International Multidisciplinary Scientific Geo
Conference (SGEM). Bulgaria, 2016, pp. 20-26.
5. Eckert A., Jozsa R. Quantu Co putat on and Shor’s Factor n Al orh t , Rev. Mod. Phys.,
1996, 68 (3), pp. 733-753.
6. Altaisky M.V., Zolnikova N.N., Kaputkina N.E., Krylov V.A., Lozovik Yu.E., S. Dattani Nikesh.
Entanglement in a quantum neural network based on quantum dots. Available at:
http://arxiv.org/pdf/ 1512.01141v1.pdf (accessed 20 June 2023).
7. Barenco A., Bennett C.H., Cleve R. et al. Elementary gates for quantum computation, Phys.
Rev. A, 1995 – Nov., Vol. 52, No. 5, pp. 3457-3467.
8. Maurer P.C., Kucsko G., Latta C., Jiang L., Yao N.Y., Bennett S.D., M.D. Lukin. Room-
Temperature Quantum Bit Memory Exceeding One Second, Science, 2012, 336, 1283.
9. Boneh D. and Lipton R.J. Quantum cryptanalysis of hidden linear functions, In Don Coppersmith,
editor, CRYPTO '95, Lecture Notes in Computer Science. Springer – Verlag, 1995,
pp. 424-437.
10. Rieffel E., Polak W. An introduction to quantum computing nonphysicists // ACM Computing
Serveys. – 2000. – Vol. 32, No 3. – P. 300-335.
11. Kim Y.H., Kulik S.P., Shih Y. Quantum Teleportation with a Complete Bell State Measurement,
J. Mod. Opt., 2001, 49, Issue 1, pp. 221-236.
12. Du-an L.-M., Lukin M.D., Cirac J.I., Zoller P. Long-distance quantum communication with
atomic ensembles and linear optics, Nature, November 2001, Vol. 414.
13. Kak S. On Quantum Neural Computing, Inf. Sci., 1995, Vol. 83, pp. 143-160.
14. Christof Zalka. Grover’s quantu search n al or th s opt al, Phys. Rev. A60, 1999,
pp. 2746-2751.
15. Neumann P., et al. Quantum register based on coupled electron spins in a room-temperature
solid, Nature Physics, 2010, pp. 1-5. DOI: 10.1038/NPHYS1536.
16. Marshall A. Fourier transform ion cyclotron resonance mass spectrometry, Mass Spectrom
Rev., 17, pp. 1-35.
17. Werner R.F. Quantum states with Einstein – Podolsky – Rosen correlations admitting a hidden-
variable model, Phys. Rev. A, 1989, Vol. 40, pp. 4277.
18. Kitaev A., Shen' A., Vyalyy M. Klassicheskie i kvantovye vychisleniya [Classical and quantum
computing]. Moscow: MTSNMO, 1999, 192 p.
19. Guzik V.F., Gushanskiy S.M., Lyapuntsova E.V., Potapov V.S. Osnovy teorii postroeniya
kvantovykh komp'yuterov i modelirovanie kvantovykh algoritmov: monografiya [Fundamentals
of the theory of constructing quantum computers and modeling of quantum algorithms:
monograph]. Moscow: Fizmatlit, 2019, 285 p.
20. Richard G. Milner. A Short History of Spin, Contribution to the XVth International Workshop
on Polarized Sources, Targets, and Polarimetry. Charlottesville, Virginia, USA, September
9 - 13, 2013. arXiv:1311.5016.
21. Raedt K.D., Michielsen K., De Raedt H., Trieu B., Arnold G., Marcus Richter, Th Lip-pert,
Watanabe H., and Ito N. Massively parallel quantum computer simulator, Computer Physics
Communications, 176, pp. 121-136.
22. Boixo S., Isakov S.V., Smelyanskiy V.N., Babbush R., Ding N., Jiang Z., Martinis,J.M., and
Neven H. Characterizing quantum supremacy in near-term devices, arXiv pre-print
arXiv:1608.00263.
23. Stierhoff G.C., Davis A.G. A History of the IBM Systems Journal In: IEEE Annals of the History
of Computing, Vol. 20, Issue1, pp. 29-35.
24. Collier, David. The Comparative Method. In Ada W. Finifter, ed. Political Sciences: The State
of the Discipline II. Washington, DC: American Science Association, pp. 105-119.
25. Hales S. Hallgren An improved quantum Fourier transform algorithm and applications, Proceedings
of the 41st Annual Symposium on Foundations of Computer Science. November
12–14, 2000, P. 515.
26. Kleppner D., Kolenkow R. An Introduction to Mechanics. 2nd ed. Cambridge: Cambridge
University Press, 2014, 49 p.
