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 …

We review the development of generative modeling techniques in machine learning for the
purpose of reconstructing real, noisy, many-qubit quantum states. Motivated by its …

Midcircuit operations, such as qubit state measurement or reset, are central to many tasks in
quantum information science, including quantum computing, entanglement generation, and …

A quantum repeater node is presented based on trapped ions that act as single-photon
emitters, quantum memories, and an elementary quantum processor. The node's ability to …

The control of quantum systems is of fundamental scientific interest and promises powerful
applications and technologies. Impressive progress has been achieved in isolating quantum …

Quantum state tomography is the standard technique for estimating the quantum state of
small systems. But its application to larger systems soon becomes impractical as the …

Intuitively, if a density operator has small rank, then it should be easier to estimate from
experimental data, since in this case only a few eigenvectors need to be learned. We prove …

The Toffoli gate is a three-quantum-bit (three-qubit) operation that inverts the state of a target
qubit conditioned on the state of two control qubits. It makes universal reversible classical …

The geometric aspects of quantum mechanics are emphasized most prominently by the
concept of geometric phases, which are acquired whenever a quantum system evolves …

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 …