A Quantum Phase Neuron

A quantum phase neuron (QPN), including its structural design and the derivation of input-output relationships, is proposed for the first time. The research focuses on the design process of quantum phase neurons when the probability amplitude is a real number. The paper provides the corresponding encoding functions based on different input types, which offers the flexibility for handling complex input data patterns. At the same time, the proposed single-layer QPN is used to solve the XNOR logic operation problem, and the superiority of the proposed QPN in performance is shown. The research presented in this paper demonstrates the potential and application prospects of QPN in constructing high-efficient quantum neural networks.

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Published
2025-02-06
DOI
https://doi.org/10.1109/icicip64458.2025.10898106
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

A Quantum Phase Neuron

Shuang Cong
Neural Networks and Applications
article

A Quantum Phase Neuron

Shuang Cong
article en

Abstract

A quantum phase neuron (QPN), including its structural design and the derivation of input-output relationships, is proposed for the first time. The research focuses on the design process of quantum phase neurons when the probability amplitude is a real number. The paper provides the corresponding encoding functions based on different input types, which offers the flexibility for handling complex input data patterns. At the same time, the proposed single-layer QPN is used to solve the XNOR logic operation problem, and the superiority of the proposed QPN in performance is shown. The research presented in this paper demonstrates the potential and application prospects of QPN in constructing high-efficient quantum neural networks.

University of Science and Technology of China (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 98%
Neural Networks and Applications
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