Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
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 …
fields that accomplish given tasks in the operation of a quantum device in the best way …
Learning quantum systems
The future development of quantum technologies relies on creating and manipulating
quantum systems of increasing complexity, with key applications in computation, simulation …
quantum systems of increasing complexity, with key applications in computation, simulation …
Real-time quantum error correction beyond break-even
The ambition of harnessing the quantum for computation is at odds with the fundamental
phenomenon of decoherence. The purpose of quantum error correction (QEC) is to …
phenomenon of decoherence. The purpose of quantum error correction (QEC) is to …
Fast universal control of an oscillator with weak dispersive coupling to a qubit
Full manipulation of a quantum system requires controlled evolution generated by nonlinear
interactions, which is coherent when the rate of nonlinearity is large compared with the rate …
interactions, which is coherent when the rate of nonlinearity is large compared with the rate …
High-fidelity, frequency-flexible two-qubit fluxonium gates with a transmon coupler
We propose and demonstrate an architecture for fluxonium-fluxonium two-qubit gates
mediated by transmon couplers (FTF, for fluxonium-transmon-fluxonium). Relative to …
mediated by transmon couplers (FTF, for fluxonium-transmon-fluxonium). Relative to …
Artificial intelligence and machine learning for quantum technologies
In recent years the dramatic progress in machine learning has begun to impact many areas
of science and technology significantly. In the present perspective article, we explore how …
of science and technology significantly. In the present perspective article, we explore how …
Model-free quantum control with reinforcement learning
Model bias is an inherent limitation of the current dominant approach to optimal quantum
control, which relies on a system simulation for optimization of control policies. To overcome …
control, which relies on a system simulation for optimization of control policies. To overcome …
Pulse-efficient circuit transpilation for quantum applications on cross-resonance-based hardware
We show a pulse-efficient circuit transpilation framework for noisy quantum hardware. This is
achieved by scaling cross-resonance pulses and exposing each pulse as a gate to remove …
achieved by scaling cross-resonance pulses and exposing each pulse as a gate to remove …
[HTML][HTML] Deep reinforcement learning for quantum multiparameter estimation
Estimation of physical quantities is at the core of most scientific research, and the use of
quantum devices promises to enhance its performances. In real scenarios, it is fundamental …
quantum devices promises to enhance its performances. In real scenarios, it is fundamental …
Realizing a deep reinforcement learning agent for real-time quantum feedback
Realizing the full potential of quantum technologies requires precise real-time control on
time scales much shorter than the coherence time. Model-free reinforcement learning …
time scales much shorter than the coherence time. Model-free reinforcement learning …