The future development of quantum technologies relies on creating and manipulating
quantum systems of increasing complexity, with key applications in computation, simulation …

Transforming stand-alone qubits into a functional, general-purpose quantum processing unit
requires an architecture where many-body quantum entanglement can be generated and …

The performance of a wide range of quantum computing algorithms and protocols depends
critically on the fidelity and speed of the employed qubit readout. Examples include gate …

High-fidelity and rapid readout of a qubit state is key to quantum computing and
communication, and it is a prerequisite for quantum error correction. We present a readout …

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 …

Quantum computing devices are inevitably subject to errors. To leverage quantum
technologies for computational benefits in practical applications, quantum algorithms and …

Machine learning (ML) is a promising approach for performing challenging quantum-
information tasks such as device characterization, calibration, and control. ML models can …

Superconducting quantum processors comprising flux-tunable data and coupler qubits are a
promising platform for quantum computation. However, magnetic flux crosstalk between the …

Efficient quantum state measurement is important for maximizing the extracted information
from a quantum system. For multiqubit quantum processors, in particular, the development of …

Qudits provide a resource-efficient alternative to qubits for quantum information processing.
The multilevel nature of the transmon, with its individually resolvable transition frequencies …