At the intersection of machine learning and quantum computing, quantum machine learning
has the potential of accelerating data analysis, especially for quantum data, with …

Integrated quantum photonics uses classical integrated photonic technologies and devices
for quantum applications. As in classical photonics, chip-scale integration has become …

Quantum technology promises to revolutionize how we learn about the physical world. An
experiment that processes quantum data with a quantum computer could have substantial …

Motivated by far-reaching applications ranging from quantum simulations of complex
processes in physics and chemistry to quantum information processing, a broad effort is …

“Quantum sensing” describes the use of a quantum system, quantum properties, or quantum
phenomena to perform a measurement of a physical quantity. Historical examples of …

Recent years have witnessed an explosion of interest in quantum devices for the production,
storage, and transfer of energy. This Colloquium concentrates on the field of quantum …

Recent decades have witnessed great developments in the field of quantum simulation—
where synthetic systems are built and studied to gain insight into complicated, many-body …

Quantum computers can exploit a Hilbert space whose dimension increases exponentially
with the number of qubits. In experiment, quantum supremacy has recently been achieved …

Single-photon emitters play an important role in many leading quantum technologies. There
is still no'ideal'on-demand single-photon emitter, but a plethora of promising material …

The coherent superposition of states, in combination with the quantization of observables,
represents one of the most fundamental features that mark the departure of quantum …