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3-Qubit Circular Quantum Convolution Computation Using the Fourier Transform with Illustrative Examples

by Artyom M. Grigoryan1,*, Sos S. Agaian2

1 Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, USA
2 Computer Science Department, The College of Staten Island, New York, USA

* Corresponding Author: Artyom M. Grigoryan. Email: email

Journal of Quantum Computing 2024, 6, 1-14. https://doi.org/10.32604/jqc.2023.026981

Abstract

In this work, we describe a method of calculation of the 1-D circular quantum convolution of signals represented by 3-qubit superpositions in the computational basis states. The examples of the ideal low pass and high pass filters are described and quantum schemes for the 3-qubit circular convolution are presented. In the proposed method, the 3-qubit Fourier transform is used and one addition qubit, to prepare the quantum superposition for the inverse quantum Fourier transform. It is considered that the discrete Fourier transform of one of the signals is known and calculated in advance and only the quantum Fourier transform of another signal is calculated. The frequency characteristics of many linear time-invariant systems and filters are well known. Therefore, the described method of convolution can be used for these systems in quantum computation.

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APA Style
Grigoryan, A.M., Agaian, S.S. (2024). 3-qubit circular quantum convolution computation using the fourier transform with illustrative examples. Journal of Quantum Computing, 6(1), 1-14. https://doi.org/10.32604/jqc.2023.026981
Vancouver Style
Grigoryan AM, Agaian SS. 3-qubit circular quantum convolution computation using the fourier transform with illustrative examples. J Quantum Comput . 2024;6(1):1-14 https://doi.org/10.32604/jqc.2023.026981
IEEE Style
A. M. Grigoryan and S. S. Agaian, “3-Qubit Circular Quantum Convolution Computation Using the Fourier Transform with Illustrative Examples,” J. Quantum Comput. , vol. 6, no. 1, pp. 1-14, 2024. https://doi.org/10.32604/jqc.2023.026981



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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