Saturday15 February 2025
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Predicting solar flares: scientists have made a breakthrough thanks to AI.

Solar activity impacts satellites, GPS networks, and electrical grids, frequently causing disruptions in terrestrial technologies. However, with the help of AI, researchers have been able to enhance the accuracy of forecasts related to coronal mass ejections from the Sun, which will help mitigate adverse effects.
Ученые сделали прорыв в прогнозировании солнечных выбросов с помощью искусственного интеллекта.

The Sun may appear to be a stable celestial body in the sky, but in reality, it is a turbulent sphere of electrically charged gas. Its activity is shaped by complex magnetic forces, leading to unpredictable solar phenomena that challenge scientists, writes Science Alert.

Understanding and predicting these disturbances is crucial, especially regarding coronal mass ejections (CMEs), which can impact terrestrial technologies and communication systems. A recent study explores how artificial intelligence can enhance the forecasting of solar events.

Researchers trained machine learning models using decades of solar data, focusing on the active region AR13664. Their findings indicate that AI detected early warning signs of increased solar activity, potentially improving methods for predicting future solar flares.

КВМ, солнечная активность, магнитная буря, солнце, плазма, солнечная активность

CMEs are massive bursts of plasma ejected from the Sun's corona due to sudden shifts in magnetic force lines. These ejections can travel at speeds ranging from hundreds to thousands of kilometers per second, sometimes reaching Earth in just a few days. Interacting with our planet's magnetosphere, they can trigger geomagnetic storms that disrupt satellites, GPS networks, and power grids, while also creating stunning auroras.

солнце, солнечная активность, Земля, КВМ, магнитные бури

A team of scientists led by Sabrina Guastavino from the University of Genoa applied artificial intelligence methods to analyze a solar storm that occurred in May 2024. Their machine learning models processed extensive historical data to uncover complex patterns that traditional methods might overlook.

The study aimed to predict solar flares, track CME formation, and forecast geomagnetic storms. Their model demonstrated a high level of accuracy, significantly improving predictions compared to conventional approaches.

The study's results have broad implications: accurate forecasts can help mitigate disruptions to energy infrastructure, communication networks, and satellite operations. Additionally, better predictions of auroral activity can enhance the experience for skywatchers eager to witness these natural light displays.

We also reported on the study of a 1900-year-old scroll discovered in the Judean Desert. Researchers found that it is a record of a legal case, representing the longest legal text of its kind.