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

Quantum reservoir networks combine the intelligence of neural networks with the potential of
quantum computing in a single platform. This platform operates on the architecture of …

Gate set tomography (GST) is a protocol for detailed, predictive characterization of logic
operations (gates) on quantum computing processors. Early versions of GST emerged …

Quantum computers solve ever more complex tasks using steadily growing system sizes.
Characterizing these quantum systems is vital, yet becoming increasingly challenging. The …

Generative adversarial learning is one of the most exciting recent breakthroughs in machine
learning. It has shown splendid performance in a variety of challenging tasks such as image …

The exponential growth in Hilbert space with increasing size of a quantum system means
that accurately characterizing the system becomes significantly harder with system …

Quantum metrology promises unprecedented measurement precision but suffers in practice
from the limited availability of resources such as the number of probes, their coherence time …

Reconstructing quantum states is an important task for various emerging quantum
technologies. The process of reconstructing the density matrix of a quantum state is known …

This paper introduces a novel and efficient technique for quantum state estimation, coined
as low-rank matrix-completion quantum state tomography for characterizing pure quantum …

Quantum properties, such as entanglement and coherence, are indispensable resources in
various quantum information processing tasks. However, there still lacks an efficient and …