论文标题
最小化量子门校准中的统计误差
Minimising statistical errors in calibration of quantum-gate sets
论文作者
论文摘要
量子门的校准是在通往可靠量子计算机的途中克服的必要障碍。在最近的一篇论文中，已经引入了一个名为GATE SET校准协议（GSC）的协议，并用于从多Qubit量子门中学习连贯的错误。在这里，我们以多种方式扩展了这项研究：首先，我们对测量不确定性进行统计分析。其次，我们发现明确的测量设置可以最大程度地减少这种不确定性，同时还要求协议仅涉及少数不同的大门，从而有助于物理可靠性。我们从数值上证明，仅通过向GSC添加两个单量门门，CNOT门校准中产生的统计误差就会划分为两个以上。
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.
