论文标题
通过动态重复速率，通过不安的测量进行的最小量子运行时表征和校准
Minimum quantum run-time characterization and calibration via restless measurements with dynamic repetition rates
论文作者
论文摘要
量子处理器的性能取决于设备的特性和对照脉冲的质量。表征基于云的量子计算机并校准控制它们的脉冲对于高保真操作是必需的。但是，这段时间的密集型任务吞噬了设备的可用性。在这里，我们以动态重复速率显示不安的测量值，可以加快校准和表征任务。在量子设备上进行5.3倍的随机基准测定要比使用活动重置时要快，而无需丢弃任何数据。此外，我们通过参数扫描和误差放大门序列校准了一个Qubit，并在主动重置上显示了量子设备上的速度高达40倍。最后，我们提出了一种执行不安的量子过程断层扫描的方法，以减轻焦躁不安的状态准备误差。这些结果减少了表征和校准任务的足迹。因此，量子计算机可以花更多的时间运行应用程序，或者更频繁地运行校准以维持门的保真度。
The performance of a quantum processor depends on the characteristics of the device and the quality of the control pulses. Characterizing cloud-based quantum computers and calibrating the pulses that control them is necessary for high-fidelity operations. However, this time intensive task eats into the availability of the device. Here, we show restless measurements with a dynamic repetition rate that speed-up calibration and characterization tasks. Randomized benchmarking is performed 5.3 times faster on the quantum device than when an active reset is used and without discarding any data. In addition, we calibrate a qubit with parameter scans and error-amplifying gate sequences and show speed-ups of up to a factor of forty on the quantum device over active reset. Finally, we present a methodology to perform restless quantum process tomography that mitigates restless state preparation errors. These results reduce the footprint of characterization and calibration tasks. Quantum computers can thus either spend more time running applications or run calibrations more often to maintain gate fidelity.
