In the past 20 years, impressive progress has been made both experimentally and
theoretically in superconducting quantum circuits, which provide a platform for manipulating …

Abstract Quantum Optimal Control is an established field of research which is necessary for
the development of Quantum Technologies. In recent years, Machine Learning techniques …

STIRAP (stimulated Raman adiabatic passage) is a powerful laser-based method, usually
involving two photons, for efficient and selective transfer of populations between quantum …

We review the physical phenomena that arise when quantum mechanical energy levels are
modulated in time. The dynamics resulting from changes in the transition frequency is a …

We deploy a combination of reinforcement learning-based approaches and more traditional
optimization techniques to identify optimal protocols for population transfer in a multi-level …

The procedure of stimulated-Raman adiabatic passage (STIRAP), one of many well-
established techniques for quantum-state manipulation, finds widespread application in …

We show that spontaneous Raman scattering of incident radiation can be observed in cavity-
QED systems without external enhancement or coupling to any vibrational degree of …

Light-matter interaction and understanding the fundamental physics behind is essential for
emerging quantum technologies. Solid-state devices may explore new regimes where …

The possibility to manipulate quantum coherence and interference, apart from its
fundamental interest in quantum mechanics, is essential for controlling nonlinear optical …

We employ a machine learning-enabled approach to quantum state engineering based on
evolutionary algorithms. In particular, we focus on superconducting platforms and consider a …