论文标题
量子估计，控制和学习：机遇和挑战
Quantum estimation, control and learning: opportunities and challenges
论文作者
论文摘要
量子系统的估计和控制理论的发展是实用量子技术的基本任务。本愿景文章在量子估计，控制和学习的新兴领域中简要介绍了具有挑战性的问题和潜在机会。主题涵盖量子状态估计，量子参数识别，量子过滤，量子开环控制，量子反馈控制，用于量子系统估计和控制的机器学习以及量子机器学习。
The development of estimation and control theories for quantum systems is a fundamental task for practical quantum technology. This vision article presents a brief introduction to challenging problems and potential opportunities in the emerging areas of quantum estimation, control and learning. The topics cover quantum state estimation, quantum parameter identification, quantum filtering, quantum open-loop control, quantum feedback control, machine learning for estimation and control of quantum systems, and quantum machine learning.
