Determination of Linear Force-Free Magnetic Field Constant Alpha Using Deep Learning

Modeling the coronal magnetic field of the Sun is an important objective in heliophysics. In this study, we illustrate how to use deep learning to estimate the parameter for a magnetic field model. A linear force-free magnetic field configuration is employed to model, as an initial illustration, an active region by using two magnetic dipoles and to determine the associated linear force-free field (LFFF) alpha parameter from a set of pseudo-coronal loop images, which serve as training and validation sets to existing deep learning algorithms. Our results show very high accuracy of determining the LFFF parameter alpha from pseudo-coronal loop images.