Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that ...

Particle physics may have been an early adopter, but AI has now spread throughout physics. This shouldn’t be too surprising. Physics is data-heavy and computationally intensive, so it benefits from ...

New research shows that metasurfaces could be used as strong linear quantum optical networks. The approach could eliminate ...

The sPHENIX particle detector, the newest experiment at the Relativistic Heavy Ion Collider (RHIC) at the U.S. Department of ...

Scientists have built a graphene-based device that can taste with near-human accuracy in a breakthrough that pushes artificial sensing closer to human ability. The system uses machine learning to ...

Microsoft Microsoft's latest AI model can accurately forecast the weather: “It doesn’t know the laws of physics, so it could make up something completely crazy” ...

Solar System Physics Simulator An interactive educational desktop application that simulates our solar system with accurate physics. Users can manipulate celestial objects and observe the effects on ...

Fang, Z. and Yan, Q. (2024) Towards Accurate Prediction of Configurational Disorder Properties in Materials Using Graph Neural Networks. npj Computational Materials, 10, Article No. 91.

Fractional excitons: When quasiparticles that carry fractional charges pair up, new quantum particles are formed. (Courtesy: Demin Liu) A newly-discovered class of quasiparticles known as fractional ...

In machine-learning-assisted high-throughput defect studies, a defect-aware latent representation of the supercell structure is crucial for the accurate prediction of defect properties. The ...