The U.S. Department of Energy now has two major supercomputing systems aimed at accelerating fusion energy research through ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...

Carbon forms the graphite in pencils, the diamonds in jewelry and the molecules that make up every living thing. But under extreme conditions—like the heat and pressure of intense explosions—carbon ...

A new AI framework called THOR is transforming how scientists calculate the behavior of atoms inside materials. Instead of relying on slow simulations that take weeks of supercomputer time, the system ...

Methodology of the CondensNet model. CondensNet is a physically constrained DL parametrisation coupled with a climate dynamics engine to support hybrid modelling. The network architecture mainly has ...

Large language models lack grounding in physical causality — a gap world models are designed to fill. Here's how three distinct architectural approaches (JEPA, Gaussian splats, and end-to-end ...

Evaluation of deep learning tools underscores the strengths, limitations and opportunities for next‑generation hybrid ...

The original version of this story appeared in Quanta Magazine. When she was 10 years old, Rose Yu got a birthday present that would change her life—and, potentially, the way we study physics. Her ...

With wildfires growing more destructive both in the United States and around the world, University at Buffalo researchers have conducted one of the most extensive evaluations to date of artificial ...