"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 ...

From superconductors and AI-driven quantum analysis to black hole physics, Day 2 of QMAT2026 highlighted cutting-edge ...

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of the quantum interactions that take place in materials. In new work, the group ...

This research was published in the journal Science Advances.Discovery of flat-band 2D materials via physics-informed scoring ...

Scientists have combined machine learning with quantum physics to discover two new superconductors and create a much faster way to search for many more. The technique could bring researchers ...

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 ...

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 ...

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: ...

Overview: We built this list around a documented selection process, not personal taste, weighing factors such as authority, teaching quality, and how well each ...