Hidden Turbulence in Sun’s Atmosphere Revealed by New Artificial Intelligence Model

An artificial intelligence model can now detect and predict the hidden turbulent motions taking place inside the Sun’s atmosphere. Developed by a team of researchers in Japan, this neural network has been fed with vertical motion and temperature data that was collected from the surface of the solar photosphere. The solar photosphere is the surface of the Sun and is also considered the lowest layer of the solar atmosphere. The solar photosphere is the surface where solar flares, coronal mass ejections, and sunspots originate and occur. On looking closely, one can figure out that the solar photosphere is not uniform. Granules, the top layers of convection cells in the solar plasma, make up the variable surface of the Sun.

The researchers have developed a novel system of convolutional neural networks that estimates the spatial distribution of horizontal velocity by factoring in the spatial distribution of temperature and vertical velocity. “Our network exhibited a higher performance on almost all the spatial scales when compared to those reported in previous studies,” said Ryohtaroh Ishikawa, lead author of the study, as reported by Science Alert.