"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 ...

Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

Researchers from Tel Aviv University have developed a new method for simulating complex quantum systems that can be combined with cutting edge AI techniques The density of 6 fermions in a 2D harmonic ...

Machine learning has emerged as a powerful tool in condensed matter physics, offering new perspectives on the exploration of quantum many-body systems, phase transitions and exotic states of matter.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

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 ...

Quantum computing has moved from physics labs into boardroom slide decks, promising to crack problems that leave even the ...

Quantum physics has a reputation for needing exotic hardware, from liquid-helium-cooled qubits to sprawling AI clusters, just to crunch through basic simulations. Now a new “physics shortcut” is ...

About a year and a half ago, quantum control startup Quantum Machines and Nvidia announced a deep partnership that would bring together Nvidia’s DGX Quantum computing platform and Quantum Machine’s ...

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: ...