Noisy Quantum Channel Characterization Using Quantum Neural Networks

被引：2

作者：

Song, Junyang ^{[1
]}

Lu, Bo ^{[1
]}

Liu, Lu ^{[1
]}

Wang, Chuan ^{[1
,2
]}

机构：

[1] Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China

[2] Beijing Normal Univ, Appl Opt Beijing Area Major Lab, Beijing 100875, Peoples R China

来源：

ELECTRONICS | 2023年 / 12卷 / 11期

基金：

中国国家自然科学基金;

关键词：

quantum neural networks; noisy quantum channel; cost function; COMMUNICATION; INFORMATION;

D O I：

10.3390/electronics12112430

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Channel noise is considered to be the main obstacle in long-distance quantum communication and distributed quantum networks. Here, employing a quantum neural network, we present an efficient method to study the model and detect the noise of quantum channels. Based on various types of noisy quantum channel models, we construct the architecture of the quantum neural network and the model training process. Finally, we perform experiments to verify the training effectiveness of the scheme, and the results show that the cost function of the quantum neural network could approach above 90% of the channel model.

引用

页数：14

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