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arXiv 2206.03417quant-ph
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最小化量子门集校准中的统计误差

Minimising statistical errors in calibration of quantum-gate sets

Yaiza Aragonés-Soria, René Otten, Tobias Hangleiter, Pascal Cerfontaine, David Gross

AI总结:

本研究针对量子门校准的统计误差问题,拓展GSC协议,通过统计分析测量不确定性、设计最优测量设置,新增两个单量子比特门即可将CNOT门校准误差减半以上,提升了量子门校准的精度与物理可实现性。

摘要:

量子门校准是实现可靠量子计算机过程中必须克服的障碍。近期有论文提出了名为Gate Set Calibration protocol(GSC,门集校准协议)的方案,用于从多量子比特门中提取相干误差。本文从多方面拓展了该研究:首先,对测量不确定性开展了统计分析;其次,找到了可最小化该不确定性的明确测量设置,同时要求协议仅涉及少量不同的门,以提升物理可实现性。数值实验表明,仅需在GSC基础上新增两个单量子比特门,CNOT门校准产生的统计误差就会降低至原来的二分之一以下。

英文摘要:

Calibration of quantum gates is a necessary hurdle to overcome on the way to a reliable quantum computer. In a recent paper, a protocol called Gate Set Calibration protocol (GSC) has been introduced and used to learn coherent errors from multi-qubit quantum gates. Here, we extend this study in a number of ways: First, we perform a statistical analysis of the measurement uncertainties. Second, we find explicit measurement settings that minimize this uncertainty, while also requiring that the protocol involves only a small number of distinct gates, aiding physical realizability. We numerically demonstrate that, just by adding two more single-qubit gates to GSC, the statistical error produced in the calibration of a CNOT gate is divided by a factor of more than two.

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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