Purification in entanglement distribution with deep quantum neural network |
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| Affiliation: | Department of Communications Science and Engineering, Fudan University, Shanghai 200433, China |
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| Abstract: | Entanglement distribution is important in quantum communication. Since there is no information with value in this process, purification is a good choice to solve channel noise. In this paper, we simulate the purification circuit under true environment on Cirq, which is a noisy intermediate-scale quantum (NISQ) platform. Besides, we apply quantum neural network (QNN) to the state after purification. We find that combining purification and quantum neural network has good robustness towards quantum noise. After general purification, quantum neural network can improve fidelity significantly without consuming extra states. It also helps to obtain the advantage of entangled states with higher dimension under amplitude damping noise. Thus, the combination can bring further benefits to purification in entanglement distribution. |
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| Keywords: | purification quantum neural network entanglement distribution quantum communication |
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