Abstract
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.
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