'11-year cycle of activity': How AI is helping scientists track over time changes in our Sun
Produced by Abhinav Yadav
Produced by Abhinav Yadav
A new study shows how artificial intelligence (AI) is giving scientists a deeper look into the Sun’s secrets. By using AI, researchers can now connect old data with new, making it easier to study how the Sun changes over time.
The Sun follows an 11-year cycle of activity, but our tools to study it are changing faster. New solar telescopes capture stunning images, but they don’t always match up with older data. That makes it tough to track the Sun's behavior for long-term studies.
AI bridges the gap between old and new images. It "translates" blurry or low-quality solar images into clearer ones as if they were taken with modern equipment. This helps scientists study sunspots, solar flares, and magnetic fields more accurately.
Scientists trained two neural networks (AI models). One model simulates what bad-quality images look like. The second model learns to fix them, sharpening the old pictures. This process helps reveal details lost in the past.
Using this method, AI improved images from the Solar and Heliospheric Observatory. A sunspot from 2010 (NOAA 11106) was reprocessed, and now we can see its magnetic structure in far more detail. This is a big leap for solar science!
The goal? To let all solar data speak the same language no matter when or where it was captured. It’s like giving older images an upgrade, without losing what made them scientifically valuable in the first place.
This AI method will help track the Sun's changes over decades, offering insights into space weather, solar eruptions, and long-term climate impacts on Earth. It’s a step toward better solar forecasting for future space missions.