London

Scientists have achieved a breakthrough in solar physics by utilising artificial intelligence (AI) to simulate the magnetic field in the upper atmosphere of the sun in quasi real-time. 

The research, published in Nature Astronomy, holds immense promise for advancing our understanding of the sun’s behaviour and its impact on space weather.

The solar magnetic field is the main driver of space weather, which can cause damage to critical infrastructures like electricity, aviation, and our space-based technology. The main source of severe space weather events are solar active regions, which are regions around sunspots where strong magnetic fields emerge through the solar surface.

Current observing capabilities only allow measuring the magnetic field at the surface of the sun, however, the energy buildup and release happens higher up in the solar atmosphere, the sun’s corona.

By leveraging the capabilities of physics-informed neural networks, the team from the University of Graz in Austria and Skolkovo Institute of Science and Technology in Russia, successfully managed to integrate observational data with the physical force-free magnetic field model.

They provided a comprehensive understanding of the connection between the observed phenomena and the underlying physics that governs the sun’s activity.

This cutting-edge method marks a significant milestone in solar physics and opens up new opportunities for numerical simulations of the sun.

The researchers simulated the evolution of an observed solar active region and demonstrated the ability to perform force-free magnetic field simulations in real-time.