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arXiv 2007.02537quant-ph
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Experimental Learning of Pure Quantum States using Sequential Single-Shot Measurement Outcomes

Sang Min Lee, Hee Su Park, Jinhyoung Lee, Jaewan Kim, Jeongho Bang

英文摘要:

We experimentally implement a machine-learning method for accurately identifying unknown pure quantum states. The method, called single-shot measurement learning, achieves the theoretical optimal accuracy for $ε= O(N^{-1})$ in state learning and reproduction, where $ε$ and $N$ denote the infidelity and number of state copies, without employing computationally demanding tomographic methods. This merit results from the inclusion of weighted randomness in the learning rule governing the exploration of diverse learning routes. We experimentally verify the advantages of our scheme by using a linear-optics setup to prepare and measure single-photon polarization qubits. The experimental results show highly accurate state learning and reproduction exhibiting infidelity of $O(N^{-0.983})$ down to $10^{-5}$, without estimation of the experimental parameters.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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