The development of quantum computing across several technologies and platforms has
reached the point of having an advantage over classical computers for an artificial problem …

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

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 …

Quantum matter, the research field studying phases of matter whose properties are
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …

Over the past few years, machine learning has emerged as a powerful computational tool to
tackle complex problems in a broad range of scientific disciplines. In particular, artificial …

We study the problem of learning the Hamiltonian of a many-body quantum system from
experimental data. We show that the rate of learning depends on the amount of control …

Machine learning can help us in solving problems in the context of big-data analysis and
classification, as well as in playing complex games such as Go. But can it also be used to …

Characterizing the interactions and dynamics of quantum mechanical systems is an
essential task in developing quantum technologies. We propose an efficient protocol based …

Abstract Machine-learning driven models have proven to be powerful tools for the
identification of phases of matter. In particular, unsupervised methods hold the promise to …

Metamaterial systems have opened new, unexpected, and exciting paths for the design of
acoustic devices that only few years ago were considered completely out of reach. However …