QuOCS: The quantum optimal control suite

Quantum optimal control includes a family of pulse-shaping algorithms that aim to unlock the full potential of a variety of quantum technologies. The Quantum Optimal Control Suite (QuOCS) unites experimental focus and model-based approaches in a unified framework. Easy usage and installation presented here and the availability of various combinable optimization strategies is designed to improve the performance of many quantum technology platforms, such as color defects in diamond, superconducting qubits, atom- or ion-based quantum computers. It can also be applied to the study of more general phenomena in physics. In this paper, we describe the software and the toolbox of gradient-free and gradient-based algorithms. We then show how the user can connect it to their experiment. In addition, we provide illustrative examples where our optimization suite solves typical quantum optimal control problems, in both open- and closed-loop settings. Integration into existing experimental control software is already provided for the experiment control software Qudi (Binder et al., 2017 [41]), and further extensions are investigated and highly encouraged. QuOCS is available from GitHub, under Apache License 2.0, and can be found on the PyPI repository.

量子最优控制（Quantum Optimal Control）涵盖一类脉冲整形算法，旨在充分释放各类量子技术的全部潜能。量子最优控制套件（Quantum Optimal Control Suite，简称QuOCS）将实验聚焦与基于模型的研究方法整合于统一框架之中。该套件凭借简便的使用与安装流程，以及各类可组合优化策略的齐备，旨在提升诸多量子技术平台的性能，例如金刚石色心缺陷系统、超导量子比特系统、基于原子或离子的量子计算机等。此外，其亦可用于研究物理学中更为广泛的物理现象。本文首先介绍该软件及其包含的无梯度与基于梯度的算法工具箱，随后阐述用户如何将其与自身实验系统相连接。此外，本文提供了若干示例，展示该优化套件如何在开环与闭环两种设置下解决典型的量子最优控制问题。目前已实现与实验控制软件Qudi（Binder等人，2017年[41]）的集成，同时我们欢迎并鼓励对该套件进行进一步扩展开发。QuOCS可在GitHub平台获取，遵循Apache License 2.0开源协议，同时也可在PyPI软件仓库中找到。