Learning control of quantum systems using frequency-domain optimization algorithms

Abstract

We investigate two classes of quantum control problems by using frequency-domain optimization algorithms in the context of ultrafast laser control of quantum systems. In the first class, the system model is known and a frequency-domain gradient-based optimization algorithm is applied to searching for an optimal control field to selectively and robustly manipulate the population transfer in atomic Rubidium. The other class of quantum control problems involves an experimental system with an unknown model. In the case, we introduce a differential evolution algorithm with a mixed strategy to search for optimal control fields and demonstrate the capability in an ultrafast laser control experiment for the fragmentation of Pr(hfac)${}_3$ molecules.

11 pages, 11 figures

References in corpus (5)

• High-Fidelity Single-Shot Toffoli Gate via Quantum Control
• Learning Robust and High-Precision Quantum Controls
• Identifying Strong-Field Effects in Indirect Photofragmentation Reactions
• Robust Learning Control Design for Quantum Unitary Transformations
• Learning control of quantum systems using frequency-domain optimization algorithms

Cited by in corpus (4)

• Orientational quantum revivals induced by a single-cycle terahertz pulse
• Cyclic three-level-pulse-area theorem for enantioselective state transfer of chiral molecules
• Learning control of quantum systems using frequency-domain optimization algorithms
• Fast, high precision dynamics in quantum optimal control theory