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 …

Photons have been a flagship system for studying quantum mechanics, advancing quantum
information science, and develo** quantum technologies. Quantum entanglement …

Realizing a long coherence time quantum memory is a major challenge of current quantum
technology. Until now, the longest coherence-time of a single qubit was reported as 660 s in …

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 …

We present an efficient machine-learning (ML) algorithm for predicting any unknown
quantum process E over n qubits. For a wide range of distributions D on arbitrary n-qubit …

Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics.
In this Letter, we propose the first algorithm to achieve the Heisenberg limit for learning an …

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

While quantum state tomography is notoriously hard, most states hold little interest to
practically minded tomographers. Given that states and unitaries appearing in nature are of …

Linear optics underpins fundamental tests of quantum mechanics and quantum
technologies. We demonstrate a single reprogrammable optical circuit that is sufficient to …

Over the past several decades, quantum information science has emerged to seek answers
to the question: can we gain some advantage by storing, transmitting and processing …