A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Researchers from Google Quantum AI report that their quantum processor, Willow, ran an algorithm for a quantum computer that solved a complex physics problem thousands of times faster than the world's ...

The team has improved the capabilities of physics-informed neural networks (PINNs), a type of artificial intelligence that incorporates physical laws into the learning process. Researchers from the ...

The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

John Hopfield, one of this year’s winners of the Nobel Prize in Physics, is a true polymath. His career started with probing the physics of solid states during the field’s heyday in the 1950s before ...