Machine Learning COFFIES “Hears” Sunspots Before We Can See Them
In this age of neural net “AI”, even the most skeptical of Butlerians have to agree that these machine learning models can be very, very good at pattern recognition if nothing else. NASA is on the same page, and to take advantage of that pattern recognition, they’ve built a machine learning module called COFFIES, which stands for Consequence Of Fields and Flows in the Interior and Exterior of the Sun , because at NASA everything is an acronym, or at least a backronym. Like most such names, this one is at least vaguely descriptive: the model is trying to predict what’s going on in the material flows and magnetic fields deep within our local star, and using those inferences is able to predict active regions– that’s sunspots to us chickens — up to 12 hours before they visibly form. The measurements used here are indirect — we can’t chart the magnetohydrodynamic snarls deep inside a star directly, but we can measure the magnetic fiel...