  In the era of digital quantum computing, optimal digitized pulses are
requisite for efficient quantum control. This goal is translated into dynamic
programming, in which a deep reinforcement learning (DRL) agent is gifted. As a
reference, shortcuts to adiabaticity (STA) provide analytical approaches to
adiabatic speed up by pulse control. Here, we select single-component control
of qubits, resembling the ubiquitous two-level Landau-Zener problem for gate
operation. We aim at obtaining fast and robust digital pulses by combining STA
and DRL algorithm. In particular, we find that DRL leads to robust digital
quantum control with operation time bounded by quantum speed limits dictated by
STA. In addition, we demonstrate that robustness against systematic errors can
be achieved by DRL without any input from STA. Our results introduce a general
framework of digital quantum control, leading to a promising enhancement in
quantum information processing.
