Smolyak algorithm assisted robust control for quantum systems with uncertainties

Efficient and systematic numerical methods for robust control design are crucial in quantum systems due to inevitable uncertainties or disturbances. We propose a novel approach that models uncertainties as random variables and quantifies robustness using the expectation of infidelity. By reformulating the robustness measure as a weighted tensor product quadrature, we employ the Smolyak sparse grid algorithm to develop a parametric robust quantum control scheme. This scheme significantly reduces computational cost while improving accuracy. We demonstrate the effectiveness of our Smolyak algorithm assisted gradient-based methods including \textbf{smGOAT} and \textbf{smGRAPE} in robust control problems regarding state transfer and quantum gate realization, with ultrahigh fidelity and strong robustness achieved. Our results contribute to improving the reliability and security of quantum computing and communication systems in the presence of real-world imperfections.