Quantum optimal control, a toolbox for devising and implementing the shapes of external
fields that accomplish given tasks in the operation of a quantum device in the best way …

Catalysts open up new reaction pathways that can speed up chemical reactions while not
consuming the catalyst. A similar phenomenon has been discovered in quantum information …

Shortcuts to adiabaticity are well-known methods for controlling the quantum dynamics
beyond the adiabatic criteria, where counterdiabatic (CD) driving provides a promising …

The quantum alternating operator ansatz (QAOA) is a prominent example of variational
quantum algorithms. We propose a generalized QAOA called CD-QAOA, which is inspired …

Closed loop quantum control uses measurement to control the dynamics of a quantum
system to achieve either a desired target state or target dynamics. In the case when the …

In this work, we put forward an approach of constructing the optimal composite pulse
sequence for robust population transfer in two-level systems. This approach is quite …

Machine learning techniques provide a remarkable tool for advancing scientific research,
and this area has significantly grown in the past few years. In particular, reinforcement …

We experimentally investigate deep reinforcement learning (DRL) as an artificial intelligence
approach to control a quantum system. We verify that DRL explores fast and robust digital …

In this work, we develop a supervised learning model for implementing robust quantum
control in composite-pulse systems, where the training parameters can be either phases …

The exotic nature of quantum mechanics differentiates machine learning applications in the
quantum realm from classical ones. Stream learning is a powerful approach that can be …