New Delhi: Scientists have achieved a breakthrough in solar physics by simulating the magnetic field in the Sun’s upper atmosphere in semi-real time using artificial intelligence (AI). The research, published in Nature Astronomy, holds great promise for advancing our understanding of the Sun’s behavior and its impact on space weather.
The solar magnetic field is a major driver of space weather, which can damage critical infrastructure such as electricity, aviation and our space-based technology. The main source of severe space weather events is the solar active region, which is the region around sunspots where strong magnetic fields emerge through the solar surface.
Current observational capabilities only allow measuring the magnetic field at the Sun’s surface, however, in the solar atmosphere, energy production and release in the Sun’s corona is high.
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Using the power of physics-informed neural networks, teams from the University of Graz in Austria and the Skolkovo Institute of Science and Technology in Russia have successfully integrated observational data with a physical force-free magnetic field model.
They provided a broader understanding of the connection between observed phenomena and the underlying physics governing the Sun’s activity.
This state-of-the-art 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.
Impressively, this process requires only less than 12 hours of computation time to simulate an observation series of five days. This unprecedented speed enables scientists to conduct real-time analysis and forecasting of solar activity, enhancing our ability to predict space weather events.
“Our use of artificial intelligence in this context represents a transformative advance. The use of AI techniques for numerical simulations allows us to better incorporate observational data and has great potential to further advance our simulation capabilities,” said lead researcher Robert Jarolim of the University of Graz.
“Computing speed holds significant promise for improving space weather forecasting and advancing our knowledge of the Sun’s behavior,” added Skoltech Associate Professor Tatiana Podlachikova.
The team also studied the time evolution of the free magnetic energy within the coronal volume, which is associated with solar flare events on the Sun such as coronal mass ejections — large plasma clouds ejected from the Sun’s atmosphere at velocities of 100-3,500 km/h. s
Comparison of extreme ultraviolet observations confirmed the robustness and accuracy of the method. Importantly, the results revealed a significant decrease in spatial and temporal free magnetic energy, which is directly correlated with solar flares.
