This review investigates the landscapes of hybrid quantum–classical optimization algorithms
that are prevalent in many rapidly develo** quantum technologies, where the objective …

Emerging reinforcement learning techniques using deep neural networks have shown great
promise in control optimization. They harness non-local regularities of noisy control …

The last decade has witnessed remarkable progress in the development of quantum
technologies. Although fault-tolerant devices likely remain years away, the noisy …

Abstract The GRadient Ascent Pulse Engineering (GRAPE) method is widely used for
optimization in quantum control. GRAPE is gradient search method based on exact …

Robust and high-precision quantum control is extremely important but challenging for the
functionalization of scalable quantum computation. In this paper, we show that this hard …

Optimization is ubiquitous in the control of quantum dynamics in atomic, molecular, and
optical systems. The ease or difficulty of finding control solutions, which is practically crucial …

Composite pulses are an efficient tool for robust quantum control. In this work, we derive the
form of the composite pulse sequence to implement robust single-qubit gates in a three-level …

Robust control design for quantum unitary transformations has been recognized as a
fundamental and challenging task in the development of quantum information processing …

Robustness of quantum operations or controls is important to build reliable quantum
devices. The robustness-infidelity measure (RIM p) is introduced to statistically quantify in a …

In some aspects, a control system interacts with a quantum system. In some instances, the
quantum system includes qubits that respond to a control signal generated by the control …