The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

The prospect of achieving quantum advantage with quantum neural networks (QNNs) is
exciting. Understanding how QNN properties (for example, the number of parameters M) …

Quantum metrology is one of the most promising applications of quantum technologies. The
aim of this research field is the estimation of unknown parameters exploiting quantum …

For a large class of variational quantum circuits, we show how arbitrary-order derivatives
can be analytically evaluated in terms of simple parameter-shift rules, ie, by running the …

The development of estimation and control theories for quantum systems is a fundamental
task for practical quantum technology. This vision article presents a brief introduction to …

To harness the potential of noisy intermediate-scale quantum devices, it is paramount to find
the best type of circuits to run hybrid quantum-classical algorithms. Key candidates are …

The extraordinary sensitivity of plasmonic sensors is well-known in the optics and photonics
community. These sensors exploit simultaneously the enhancement and the localization of …

The interest in a system often resides in the interplay among different parameters governing
its evolution. It is thus often required to access many of them at once for a complete …

We study multiparameter sensing of two-dimensional (2D) and three-dimensional (3D)
vector fields within the Bayesian framework for SU (2) quantum interferometry. We establish …