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Robust Quantum Operation for Two-Level Systems Using Sampling-Based Learning Control

机译:两级系统基于采样的学习控制的鲁棒量子操作

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Robust control design for operation of quantum systems has been considered as a demanding and challenging task in the development of quantum technologies. In this paper, we apply the sampling-based learning control (SLC) approach to design a control law for manipulating two-level quantum systems with uncertainties. The gradient-based learning and optimization algorithm is adopted to find the optimal piece-wise control fields for an augmented system by sampling the domain of uncertainties. Numerical results demonstrate the effectiveness of the proposed method for unitary operation of two-level quantum systems even when there are large uncertainties.
机译:在量子技术的发展中,用于量子系统的鲁棒控制设计已被认为是一项艰巨而艰巨的任务。在本文中,我们应用基于采样的学习控制(SLC)方法来设计用于操纵具有不确定性的两级量子系统的控制律。采用基于梯度的学习和优化算法,通过对不确定性域进行采样来找到增强系统的最优分段控制域。数值结果表明,即使存在较大的不确定性,该方法对于二能级量子系统的统一操作也是有效的。

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