论文标题
用于自动量子系统标识和设备的软件工具集
Software tool-set for automated quantum system identification and device bring up
论文作者
论文摘要
我们提出了一个软件工具集，将量子设备的理论，最佳控制视图与量子计算所需的实际操作和表征任务相结合。在同一框架中，我们执行基于模型的模拟来创建控制方案，将这些控件与设备（或通过模拟实验过程中的Dexo \ textemdash中的闭环校准）进行校准，并最终通过最小化模拟和实验之间的不匹配，从而改善系统模型，从而导致设备的数字双胞胎。基于模型的模拟器是使用TensorFlow实施的，以实现数字效率，可扩展性和使用自动分化，从而实现了基于梯度的任意模型和控制方案的优化。优化是通过源自机器学习领域的最先进算法进行的。所有这些都带有一个用户友好的Qiskit界面，该接口允许最终用户在高保真可区分的物理模拟器上轻松模拟其量子电路。
We present a software tool-set which combines the theoretical, optimal control view of quantum devices with the practical operation and characterization tasks required for quantum computing. In the same framework, we perform model-based simulations to create control schemes, calibrate these controls in a closed-loop with the device (or in this demo \textemdash by emulating the experimental process) and finally improve the system model through minimization of the mismatch between simulation and experiment, resulting in a digital twin of the device. The model based simulator is implemented using TensorFlow, for numeric efficiency, scalability and to make use of automatic differentiation, which enables gradient-based optimization for arbitrary models and control schemes. Optimizations are carried out with a collection of state-of-the-art algorithms originated in the field of machine learning. All of this comes with a user-friendly Qiskit interface, which allows end-users to easily simulate their quantum circuits on a high-fidelity differentiable physics simulator.
