Quantum optimal control of superconducting qubits based on
machine-learning characterization
Quantum optimal control of superconducting qubits based on
machine-learning characterization
Implementing fast and high-fidelity quantum operations using open-loop quantum optimal control relies on having an accurate model of the quantum dynamics. Any deviations between this model and the complete dynamics of the device, such as the presence of spurious modes or pulse distortions, can degrade the performance of optimal controls …