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Some Quantum Neural Networks

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Abstract

We analyzed the classical aritificial neural networks (ANN) and quantum neural networks (QNN), in particular, Boltzmann machines, Hopfield machines, the rules of training quantum neural networks. Then we analyzed the case of implementing the XOR QNN. We proposed to use the Bernstein-Vazirani Algorithm and Grover’s Search Algorithm in QNN. We looked at the problem of least square solutions of the linear regression and proposed to use the quantum Gauss-Jordan Elimination Code to solve the LSP equation. This lets us to make the network works outperform the classical approaches.

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Acknowledgments

The author’s sincere thanks are deeply addressed to professors K. Nagata, T. Nakamura, H. Geurdes and the referees for a careful reading the manuscripts and for the valuable comments.

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  1. TIMAS, Thang Long University, Nghiem Xuan Yem Road, Hoang Mai district, Hanoi, Vietnam

    Do Ngoc Diep

  2. Institute of Mathematics, Vietnam National Academy of Science and Technology, 18 Hoang Quoc Viet road, Cau Giay district, 10307, Hanoi, Vietnam

    Do Ngoc Diep

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  1. Do Ngoc Diep
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Correspondence to Do Ngoc Diep.

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Diep, D.N. Some Quantum Neural Networks. Int J Theor Phys 59, 1179–1187 (2020). https://doi.org/10.1007/s10773-020-04397-1

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  • DOI: https://doi.org/10.1007/s10773-020-04397-1

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