Human brain operates near, but not at, the critical point

A recent study published in Physical Review Letters reveals that many widely used signatures of criticality in brain data may be statistical artifacts. They propose a more robust framework that, when ...

Designing proteins by their motion, not just their shape

Proteins are far more than nutrients we track on a food label. Present in every cell of our bodies, they work like nature's ...
Forbes

Did Van Gogh’s Starry Night Anticipate Physics’ Hardest Problem?

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. The Starry Night, June 1889 (Photo by Art Images via Getty Images) It’s said that life can ...
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Illustrating physics problems with Web VPython in Python

Illustrating physics problems with Web VPython in Python. Learn how to build clear 3D visualizations for motion and forces, and bring physics concepts to life with interactive animations and simple ...
GitHub

Discovery of Unstable Singularities in Fluid Dynamics with Physics-Informed Neural Networks

This repository attempts to replicate the results of the paper Discovery of Unstable Singularities by Yongji Wang, Mehdi Bennani, et al. (17 September 2025). The work presents the first systematic ...
Live Science

New 'physics shortcut' lets laptops tackle quantum problems once reserved for supercomputers and AI

Physicists have transformed a decades-old technique for simplifying quantum equations into a reusable, user-friendly "conversion table" that works on a laptop and returns results within hours. When ...
SciTech Daily

AI Breakthrough Finally Cracks Century-Old Physics Problem

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed an AI framework that tackles one of physics’ most complex computational challenges. Credit: Stock An AI ...
Interesting Engineering

Breakthrough ‘physics shortcut’ solves quantum problems on ordinary laptop

Quantum particles can interact in over a trillion ways at the same time. (Representational image)VICTOR de SCHWANBERG/SCIENCE PHOTO LIBRARY/GettyImages A team of physicists from the University at ...
IEEE

Collaborative Physics-Informed Neural Dynamics Approach for Autonomous Vehicles With Nonconvex Safety-Critical Constraints

Abstract: Increasing complex driving scenarios inevitably expose autonomous vehicles to intricate nonconvex challenges, which are usually simplified or even ignored by current research, leading to ...
decrypt

Google DeepMind AI Cracks Century-Old Fluid Mysteries, Pointing to New Era in Science

DeepMind used physics-informed neural networks to find new solutions to Navier-Stokes equations. The AI uncovered a new family of singularities, later proven mathematically correct. The breakthrough ...
Physics World

Understanding quantum learning dynamics with expressibility metrics

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 ...