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Artificial Intelligence Helps Stanford Physicists Predict Dangerous Solar Flares


Credit: NASA/SDO and the AIA; EVE; and HMI science teams

Credit: NASA/SDO and the AIA; EVE; and HMI science teams

Solar flares can release the energy equivalent of many atomic bombs, enough to cut out satellite communications and damage power grids on Earth, 93 million miles away. The flares arise from twisted magnetic fields that occur all over the sun’s surface, and they increase in frequency every 11 years, a cycle that is now at its maximum.

Using artificial intelligence techniques, Stanford solar physicists Monica Bobra and Sebastien Couvidat have automated the analysis of the largest ever set of solar observations to forecast solar flares using data from the Solar Dynamics Observatory (SDO), which takes more data than any other satellite in NASA history. Their study identifies which features are most useful for predicting solar flares.

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