Abstract: Quantum optimal control has become a universal toolbox for accomplishing a large variety of tasks on experimental quantum devices in the best way possible. In this talk, I will give an overview of several recent studies in my group regarding the development and applications of quantum optimal control techniques in engineering quantum dynamics and performing quantum state tomography. Specifically, we have developed an analytical quantum optimal control method for finding the exact speed limit of a desired quantum evolution for a Hamiltonian with inequality constraints, relevant to many studies of Lieb-Robinson-type bounds. Using modern machine learning techniques, we have also developed numerical quantum optimal control algorithms that can facilitate the experimental design of speed-optimal quantum gates, preparation of many-body ground states, and efficient quantum state tomography for structured quantum states. For quantum state tomography, we further show that our optimization algorithm can saturate the Cramer-Rao bound, which lower bounds the sample complexity and is efficiently computable for most quantum states with efficient classical representations. These studies altogether aim to bridge gaps between experimental optimal control protocols and rigorous theoretical bounds.
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Reception following the colloquium in the h-Bar.