During the last ten years, superconducting circuits have passed from being interesting
physical devices to becoming contenders for near-future useful and scalable quantum …

Laser-cooled and trapped atomic ions form an ideal standard for the simulation of interacting
quantum spin models. Effective spins are represented by appropriate internal energy levels …

Quantum Machine Learning bridges the gap between abstract developments in quantum
computing and the applied research on machine learning. Paring down the complexity of the …

Various fundamental phenomena of strongly correlated quantum systems such as high-T c
superconductivity, the fractional quantum-Hall effect and quark confinement are still awaiting …

Quantum simulators are devices that actively use quantum effects to answer questions about
model systems and, through them, real systems. In this review we expand on this definition …

Numerical simulation of quantum systems is crucial to further our understanding of natural
phenomena. Many systems of key interest and importance, in areas such as …

The review article presents the recent progress in quantum computing and simulation within
the field of biological sciences. The article is designed mainly into two portions: quantum …

Abstract Quantum Machine Learning (QML) is a field that combines the principles of
Quantum Computing (QC) and Machine Learning (ML). QC works by taking advantage of …

The field of quantum simulation, which aims at using a tunable quantum system to simulate
another, has been develo** fast in the past years as an alternative to the all-purpose …

We propose general methodology of deterministic single-mode quantum interaction
nonlinearly modifying single quadrature variable of a continuous-variable system. The …