UK achieves 1,000 times faster 5D plasma modeling for nuclear fusion

Scientists from the UK Atomic Energy Authority (UKAEA), Johannes Kepler University Linz (JKU), and Emmi AI have developed GyroSwin, an AI-powered tool that models fusion plasma turbulence up to 1,000 times faster than traditional 5D gyrokinetic simulations. These simulations, which track plasma behavior across three spatial dimensions plus two velocity dimensions, are crucial for designing fusion reactors but typically require days on supercomputers. GyroSwin uses machine learning to learn the underlying plasma dynamics, enabling accurate predictions in seconds while preserving key physical features such as turbulent fluctuations and sheared plasma flows, which are essential for meaningful scientific interpretation. This breakthrough addresses a major bottleneck in fusion research by drastically reducing computational time and cost, facilitating millions of simulations needed to optimize future fusion power plants like the UK’s Spherical Tokamak for Energy Production (STEP). By accelerating the modeling of plasma turbulence, GyroSwin supports the development of practical fusion energy—a clean, virtually limitless power