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The signal recovery of continuous variable quantum communication system

机译:连续可变量子通信系统的信号恢复

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摘要

In this paper, a novel continuous variable quantum teleportation (CVQTS) scheme based on quantum neural network (QNN) is proposed to implement the high-efficient and communication security. To achieve the teleportation in two-dimensional Hilbert space, the continuous variable quantum states are split into N modes by an array of N - 1 beam splitters (N-splitter) in the continuous variable quantum teleportation channel (CVQTC). The QNN is applied to trace and restore the distortion signals. It used QNN training indirectly to obtain the weight parameters. In order to ensure the communication security, only a small number of information is extracted as training expectation. The results demonstrate that our scheme is capable of enhancing the fidelity close to 1 for almost all teleported information. Due to the simple structure of QNN, CVQTS scheme based on QNN can be applied to any other inputs and improves the maneuverability and realizability in the experiment.
机译:本文提出了一种基于量子神经网络(QNN)的新型连续可变量子隐形传态(CVQTS)方案,以实现高效和通信安全。为了在二维希尔伯特空间中实现隐形传送,连续可变量子态通过连续可变量子隐形传送通道(CVQTC)中的N-1个分束器(N分离器)阵列分成N个模式。 QNN用于跟踪和恢复失真信号。它间接使用了QNN训练来获取权重参数。为了确保通信安全性,仅提取少量信息作为训练期望。结果表明,对于几乎所有的传送信息,我们的方案都能将保真度提高到接近1。由于QNN的简单结构,基于QNN的CVQTS方案可以应用于任何其他输入,并提高了实验的可操作性和可实现性。

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