论文标题
连续监视嘈杂的中间量子处理器
Continuous monitoring for noisy intermediate-scale quantum processors
论文作者
论文摘要
我们提供了一个中间尺度量子处理器的连续监视系统,该系统允许根据执行的量子电路集和产生的测量结果提取嘈杂天然门的估计和读取测量结果。与用于校准和基准测试量子处理器的标准方法相反,已执行的电路(已输入监视系统)被假定不在任何控件中。我们提供了将系统应用于从量子模拟器获得的合成生成的数据以及从基于云的公共量子量子处理器收集的实验数据的结果。在这两种情况下,我们都证明了开发的方法为模拟器/处理器的固有声音提供了宝贵的结果。考虑到我们的方法在无需运行其他算法的情况下仅使用已实现电路的已访问数据,因此监视系统可以补充现有方法。我们预计,我们的监视系统可以成为近期视野中各种量子计算机的有用工具,包括公共可访问的基于云的平台,并减少其基准测试和校准所需的资源。
We present a continuous monitoring system for intermediate-scale quantum processors that allows extracting estimates of noisy native gate and read-out measurements based on the set of executed quantum circuits and resulting measurement outcomes. In contrast to standard approaches for calibration and benchmarking quantum processors, the executed circuits, which are input to the monitoring system, are assumed to be out of any control. We provide the results of applying our system to the synthetically generated data obtained from a quantum emulator, as well as to the experimental data collected from a publicly accessible cloud-based quantum processor. In the both cases, we demonstrate that the developed approach provides valuable results about inherent noises of emulators/processors. Considering that our approach uses only already accessible data from implemented circuits without the need to run additional algorithms, the monitoring system can complement existing approaches. We expect that our monitoring system can become a useful tool for various quantum computers in the near-term horizon, including publicly accessible cloud-based platforms, and reduce resources that are required for their benchmarking and calibration.