Brand Dean, Sinayskiy Ilya, Petruccione Francesco
Department of Physics, School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, 7604, South Africa.
School of Chemistry and Physics, University of KwaZulu-Natal, Durban, 4001, South Africa.
Sci Rep. 2024 Feb 27;14(1):4769. doi: 10.1038/s41598-024-54598-5.
In recent years, Noisy Intermediate Scale Quantum (NISQ) computers have been widely used as a test bed for quantum dynamics. This work provides a new hardware-agnostic framework for modelling the Markovian noise and dynamics of quantum systems in benchmark procedures used to evaluate device performance. As an accessible example, the application and performance of this framework is demonstrated on IBM Quantum computers. This framework serves to extract multiple calibration parameters simultaneously through a simplified process which is more reliable than previously studied calibration experiments and tomographic procedures. Additionally, this method allows for real-time calibration of several hardware parameters of a quantum computer within a comprehensive procedure, providing quantitative insight into the performance of each device to be accounted for in future quantum circuits. The framework proposed here has the additional benefit of highlighting the consistency among qubit pairs when extracting parameters, which leads to a less computationally expensive calibration process than evaluating the entire device at once.
近年来,噪声中等规模量子(NISQ)计算机已被广泛用作量子动力学的试验平台。这项工作为在用于评估设备性能的基准程序中对量子系统的马尔可夫噪声和动力学进行建模提供了一个新的硬件无关框架。作为一个易于理解的例子,该框架的应用和性能在IBM量子计算机上得到了展示。该框架通过一个简化的过程同时提取多个校准参数,这个过程比之前研究的校准实验和断层扫描程序更可靠。此外,这种方法允许在一个综合程序中对量子计算机的几个硬件参数进行实时校准,为未来量子电路中要考虑的每个设备的性能提供定量洞察。这里提出的框架还有一个额外的好处,即突出了提取参数时量子比特对之间的一致性,这导致校准过程的计算成本低于一次性评估整个设备。