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

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.