"Machine Learning in Quantum Sciences", outcome of a collaborative effort from world-leading experts, offers both an introduction to machine learning and deep neural networks, and an overview of their ...

Atom interferometry, a technique that leverages the wavelike nature of atoms, has been pivotal in precision measurements, including satellite navigation and measuring the Earth's roundness.

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Researchers from the group of theoretical physicist Hans Briegel have collaborated with NVIDIA to develop an AI method that automatically generates efficient quantum circuits, a key bottleneck in ...

Your phone finishes your sentences, your camera detects faces and your streaming app suggests songs you never thought you would want, thanks to classical AI systems. These are powerful logic engines: ...

Microchips power almost every modern device — phones, laptops and even fridges. But behind the scenes, making them is a complex process. But researchers say they have found a way to tap into the power ...

A team of physics educators is focusing on a new approach to teaching quantum physics in schools. Traditional classroom teaching has tended to focus on presenting the history of the origins of quantum ...