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 ...

In the dynamic realm of optical physics, researchers are continually pushing the boundaries of how light can be manipulated and harnessed for practical applications. As reported in Advanced Photonics ...

Researchers used generative AI to develop a physics-informed technique to classify phase transitions in materials or physical systems that is much more efficient than existing machine-learning ...

Researchers at Archetype AI have developed a foundational AI model capable of learning complex physics principles directly from sensor data, without any pre-programmed knowledge. This breakthrough ...

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 ...

Have you ever imagined an AI solving a complex problem that has challenged scientists for more than a decade? Whether we accept it or not, that moment has arrived. In a recent path-breaking ...

For most theories in physics, the order of operations has little impact on the result. When setting a dial to a certain position, for example, it doesn't matter whether it's turned clockwise or ...

When water freezes, it transitions from a liquid phase to a solid phase, resulting in a drastic change in properties like density and volume. Phase transitions in water are so common most of us ...