Several developments in learning control of quantum systems

This paper summarizes several recent achievements in the area of learning control of quantum systems and draw several new directions for future research. Three learning algorithms including gradient method, differential evolution and reinforcement learning are introduced for quantum control. Quantum state control in closed and open quantum systems is analyzed, where gradient method and differential evolution are employed, respectively. The approach of deep reinforcement learning for quantum gate control is introduced, and a sampling-based learning control is illustrated for robust control of quantum gates.