CHARACTERISTICS OF QUANTUM CIRCUITS WITH FUNCTIONAL CONFIGURATIONS OF QUBITS

  • S.M. Gushanskiy Southern Federal University
  • V.S. Potapov Southern Federal University
Keywords: Modeling, quantum algorithm, qubit, model of a quantum computer, entanglement, superposition, quantum operator

Abstract

The paper is an exploration of a new approach to the systematic analysis and classification
of quantum circuits based on the functional configuration of qubits. The article examines in detail
the role of elementary gates in changing the elements of the state vector and highlights the importance
of functional configurations of qubits in the collective modification of quantum states.
The main aspects covered in the article include the characterization of quantum circuits with functional
configurations of qubits, analysis of the impact of elementary gates on the state of a quantum
vector, and determination of the number of possible types of functional configurations.
The results of the study could have important implications for optimizing quantum circuits and
improving our understanding of their general properties. A qubit functional configuration is a
mathematical structure that can collectively classify the properties and behavior of quantum circuits.
The development of quantum algorithms with efficient quantum circuits has been a central
part of quantum computing, which has seen enormous progress both theoretically and experimentally
over the past 30 years. The paper makes a contribution to the field of quantum computing by
providing a systematic approach to classify and analyze quantum circuits based on their functional
qubit configurations. Quantum algorithms are an innovative class of algorithms based on the
principles of quantum mechanics and using qubits instead of classical bits to process information.
Unlike classical algorithms, which operate on bits that take on the values 0 or 1, quantum algorithms
can use the principles of quantum superposition and quantum interaction, which allows
them to perform many calculations simultaneously. One of the key advantages of quantum algorithms
is their ability to solve certain problems much more efficiently than classical algorithms.
However, the design and implementation of quantum algorithms pose significant technical and
algorithmic challenges, such as managing quantum states, minimizing errors, and creating robust
quantum gates. Despite these challenges, quantum algorithms offer promising opportunities to
revolutionize computing and solve problems that have traditionally been too complex for classical
computers

References

1. Calderbank A.R., Shor P.W. Good quantum error-correcting codes exist, Phys. Rev. A, 1996,
Vol. 54, pp. 1098-1106;
2. Linke N.M., Gutierrez M,, Landsman K,A,, et al. Fault-tolerant quantum error detection, Science
Advances, 2017, 3 (10), pp. e1701074. Available from: https://doi.org/10.1126/
sciadv.1701074;
3. Vuillot C. Is error detection helpful on IBM 5q chips?, Quantum Information and Computation,
2018, Vol. 18, No. 11-12, pp. 0949-0964.
4. Harper R., Flammia S.T. Fault-tolerant logical gates in the IBM quantum experience, Phys.
Rev. Lett., 2019, 122, 080504. Available from: https://link.aps.org/doi/10.1103/
PhysRevLett.122.080504.
5. Wootton J.R., Loss D. Repetition code of 15 qubits, Physical Review A, 2018, 97 (5). Available
from: https://doi.org/10.1103/physreva.97.052313.
6. Aspuru-Guzik A., Dutoi A.D., Love P.J., et al. Simulated quantum computation of molecular
energies, Science, 2005, 309 (5741), pp. 1704-1707. Available from: https://science.
sciencemag.org/content/309/5741/1704.
7. Knill M., Laflamme R., and Zurek W. Threshold accuracy for quantum computation.
quantph/9610011, 15 Oct 1996.
8. Gushanskiy S.M., Potapov V.S. Metodika razrabotki i postroeniya kvantovykh algoritmov
[Methodology for the development and construction of quantum algorithms], Informatizatsiya
i svyaz' [Informatization and communication], 2017, No. 3, pp. 101-104.
9. Gushanskiy S.M., Polenov M.Yu., Potapov V.S. Realizatsiya komp'yuternogo modelirovaniya
sistemy s chastitsey v odnomernom i dvukhmernom prostranstve na kvantovom urovne [Implementation
of computer simulation of a system with a particle in one-dimensional and twodimensional
space at the quantum level], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya
SFedU. Engineering Sciences], 2017, No. 3, pp. 223-233.
10. Guzik V.F., Gushanskiy S.M., Potapov V.S. Kolichestvennye kharakteristiki stepeni
zaputannosti [Quantitative characteristics of the degree of entanglement], Izvestiya YuFU.
Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2016, No. 3, pp. 76-86.
11. Kleppner D., Kolenkow R. An Introduction to Mechanics (Second ed.). Cambridge: Cambridge
University Press, 2014, 49 p.
12. Potapov V.S., Gushanskiy S.M. Kvantovye tipy oshibok i metody ikh ustraneniya, zavisimost'
oshibki ot mery i chistoty zaputannosti [Quantum types of errors and methods for their elimination,
dependence of the error on the measure and purity of entanglement], Sb. trudov XIV
Vserossiyskoy nauchnoy konferentsii molodykh uchenykh, aspirantov i studentov ITSAiU-2016
[Collection of proceedings of the XIV All-Russian Scientific Conference of Young Scientists,
Postgraduates and Students of ITSAiU-2016]. Rostov-on-Don: Izd-vo YuFU, 2016, Vol. 3,
pp. 123-129.
13. Gushansky S., Pykhovskiy V., Kozlovskiy A., Potapov V. Development of a scheme of a hardware
accelerator of quantum computing for correction quantum types of errors, The 4-th Computational
Methods in Systems and Software 2020, Czech Republic, pp. 64-73.
14. 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, pp. 515.
15. Guzik V., Gushanskiy S., Polenov M., Potapov V. Complexity Estimation of Quantum Algorithms
Using Entanglement Properties, 16th International Multidisciplinary Scientific
GeoConference, Bulgaria, 2016, pp. 20-26.
16. Guzik V., Gushanskiy S., Polenov M., Potapov V. Models of a quantum computer, their characteristics
and analysis, 9th International Conference on Application of Information and Communication
Technologies (AICT). Institute of Electrical and Electronics Engineers, 2015, pp. 583-587.
17. Collier D. The Comparative Method / In: Finifter A.W. (ed.), Political Sciences: The State of
the Discipline II. American Science Association. Washington, DC, 1993, pp. 105-119:
18. Olukotun K. Chip Multiprocessor Architecture – Techniques to Improve Throughput and Latency.
Morgan and Claypool Publishers, San Rafael, 2007.
19. 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.
20. Williams C.P. Explorations in Quantum Computing, Texts in Computer Science. Chapter 2.
Quantum Gates. Springer, 2011, pp. 51-122.
21. Potapov V., Gushanskiy S., Guzik V., Polenov M. The Computational Structure of the Quantum
Computer Simulator and Its Performance Evaluation, In: Software Engineering Perspectives
and Application in Intelligent Systems. Advances in Intelligent Systems and Computing.
Springer, 2019, Vol. 763, pp. 198-207.
22. Bennett С.H., Shor P.W., Smolin J.A., Thapliyal A.V. Entanglement-assisted Capacity of a
Quantum Channel and the Reverse Shannon Theorem, IEEE Transactions on Information
Theory, 2002, 48, pp. 2637-2655.
23. Milner R.G. A Short History of Spin. In: Contribution to the XV International Workshop on
Polarized Sources, Targets, and Polarimetry. Charlottesville, Virginia, USA, September 9–13,
2013. arXiv:1311.5016 (2013).
24. Hallgren H.S. An improved quantum Fourier transform algorithm and applications, In: Proceedings
of the 41st Annual Symposium on Foundations of Computer Science, Redondo Beach,
CA, IEEE, 2000, pp. 515.
25. Boneh D., Zhandry M. Quantum-secure message authentication codes, In: Proceedings of
Eurocrypt, 2013, pp. 592-608.
26. Potapov V., Gushansky S., Guzik V., Polenov M. Architecture and Software Implementation of
a Quantum Computer Model, In: Advances in Intelligent Systems and Computing. Springer,
2016, Vol. 465, pp. 59-68.
Published
2024-01-05
Section
SECTION I. INFORMATION PROCESSING ALGORITHMS