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arXiv 1712.03213quant-ph
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具有保真度估计的可扩展量子层析成像

Scalable Quantum Tomography with Fidelity Estimation

Jun Wang, Zhao-Yu Han, Song-Bo Wang, Zeyang Li, Liang-Zhu Mu, Heng Fan, Lei Wang

摘要:

我们提出了一个纯量子系统的量子层析成像方案,该方案采用随机基测量和生成学习方法,以及内置的保真度估计方法来评估层析成像状态的可靠性。我们从理论上证明了该方案的有效性,并对三种典型的量子信息态和随机激发态进行了数值模拟实验,验证了该方案的有效性和鲁棒性。当系统规模增大时,满足一定收敛准则所需的副本数以低次多项式的方式增长,从而实现了对实际量子态层析至关重要的可扩展性.

英文摘要:

We propose a quantum tomography scheme for pure qudit systems which adopts random base measurements and generative learning methods, along with a built-in fidelity estimation approach to assess the reliability of the tomographic states. We prove the validity of the scheme theoretically, and we perform numerically simulated experiments on several target states including three typical quantum information states and randomly initiated states, demonstrating its efficiency and robustness. The number of replicas required by a certain convergence criterion grows in the manner of low-degree polynomial when the system scales, thus the scheme achieves high scalability that is crucial for practical quantum state tomography.

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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