A joint research team between the Center for Quantum Information and Quantum Biology (QIQB) at The University of Osaka and ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

Complex network theory has become a key analytical framework in modern physics for studying structure, dynamics, and emergent behaviour in complex systems.

The hope for quantum computers is that the devices will be able to solve complex tasks such as predicting how chemicals react or cracking encrypted text. One of the main reasons that the machines are ...

A computational physics approach to modeling rigid object motion using spring forces in Python. This focuses on how spring ...

A physics-based Python simulation exploring collision behavior in an AstroBlaster system, focusing on momentum transfer, ...

Quantum computing is moving fast, and by 2026, knowing about quantum programming languages will be a big deal. It’s not just ...

Abstract: A Low-fidelity Physics-guided, High-fidelity Neural Simulation (LPHN-Sim) is devised for parallel-in-time dynamic simulation of networked microgrids (NMGs). Three contributions are presented ...

In the age of Industry 4.0, manufacturers are expected to develop increasingly sophisticated, digitally integrated products while controlling development costs and accelerating time to market.

Zurich-based Fainite AG has received €165,000 (CHF 150,000) from Venture Kick to advance physics-based simulations and expand access to advanced engineering analysis across a wider range of ...

Abstract: Fast simulation of power grid dynamics under multi-contingency (e.g., $N{-}k$ events and cascading failures) is crucial for identifying vulnerabilities and ...

“Force fields” have long captured our imagination — the invisible shields of science-fiction lore that protect starships and superheroes from harm. But in the world of scientific discovery, force ...