金刚石氮空位中心集合闭环优化控制的门集评估指标

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Philipp J. Vetter, Thomas Reisser, Maximilian G. Hirsch, Tommaso Calarco, Felix Motzoi, Fedor Jelezko, Matthias M. Müller
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引用次数: 0

摘要

量子科学与技术领域经常面临的一个挑战是如何精确控制其基本动态,从而实现所需的量子操作,这些操作通常由一组量子门描述。这些量子门可能会受到特定应用误差的影响,从而导致其控制取决于所选电路、质量度量和量子门集本身。一个自然的解决方案是以应用为导向的方式应用量子优化控制。反过来,这就需要定义一种有意义的测量方法来衡量上下文门组的性能。因此,我们探索并比较了量子过程层析成像、线性反转门集层析成像、随机线性门集层析成像和随机基准作为闭环量子优化控制实验测量方法的适用性,并将金刚石中的氮空位中心宏观集合作为测试平台。我们的工作证明了这些测量方法之间的相对权衡,以及如何显著提高门集性能,从而改进所有研究方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Gate-set evaluation metrics for closed-loop optimal control on nitrogen-vacancy center ensembles in diamond

Gate-set evaluation metrics for closed-loop optimal control on nitrogen-vacancy center ensembles in diamond

A recurring challenge in quantum science and technology is the precise control of their underlying dynamics that lead to the desired quantum operations, often described by a set of quantum gates. These gates can be subject to application-specific errors, leading to a dependence of their controls on the chosen circuit, the quality measure and the gate-set itself. A natural solution would be to apply quantum optimal control in an application-oriented fashion. In turn, this requires the definition of a meaningful measure of the contextual gate-set performance. Therefore, we explore and compare the applicability of quantum process tomography, linear inversion gate-set tomography, randomized linear gate-set tomography, and randomized benchmarking as measures for closed-loop quantum optimal control experiments, using a macroscopic ensemble of nitrogen-vacancy centers in diamond as a test-bed. Our work demonstrates the relative trade-offs between those measures and how to significantly enhance the gate-set performance, leading to an improvement across all investigated methods.

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来源期刊
npj Quantum Information
npj Quantum Information Computer Science-Computer Science (miscellaneous)
CiteScore
13.70
自引率
3.90%
发文量
130
审稿时长
29 weeks
期刊介绍: The scope of npj Quantum Information spans across all relevant disciplines, fields, approaches and levels and so considers outstanding work ranging from fundamental research to applications and technologies.
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