Exploring the Sun's upper atmosphere with neural networks: Reversed patterns and the hot wall effect
We have developed an inversion procedure designed for high-resolution solar spectro-polarimeters, such as those of Hinode and the DKIST. The procedure is based on artificial neural networks trained with profiles generated from random atmospheric stratifications for a high generalization capability. When applied to Hinode data, we find a hot fine
Socas-Navarro, H. et al.
Fecha de publicación:
8
2021