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.

量子科学和技术中一个反复出现的挑战是精确控制其基本动力学，从而产生所需的量子运算，通常由一组量子门描述。这些门可能会受到特定于应用的错误的影响，导致它们的控制依赖于所选电路、质量测量和门组本身。一个自然的解决方案是以面向应用程序的方式应用量子最优控制。反过来，这需要定义一个有意义的上下文门集性能度量。因此，我们以金刚石中氮空位中心的宏观集合为试验台，探索和比较了量子过程断层扫描、线性反转门集断层扫描、随机线性门集断层扫描和随机基准测试作为闭环量子最优控制实验措施的适用性。我们的工作展示了这些措施之间的相对权衡以及如何显著提高门集性能，从而在所有研究的方法中得到改进。