Abstract
Context. The Full-disk Vector MagnetoGraph (FMG) is one of the three payloads on the Advanced Space-based Solar Observatory (ASO-S). The FMG is set to observe the full disk vector magnetic field at a single wavelength point. The magnetograph in orbit will encounter the wavelength shift problem caused by the Doppler effect in the magnetic field, which mainly comes from the Sun’s rotation velocity and the satellite–sun relative velocity. Aims. We look to use neural networks for single-wavelength calibration to solve the wavelength shift problem. Methods. We used the existing data from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO). To simulate plausible single-wavelength observations, we used the Stokes polarization image from the HMI at a single wavelength point. We also input the satellite orbital velocity given by the HMI data file and the solar rotation velocity to the network. We developed a set of data preprocessing methods before entering the network and we trained the network to get the calibration model. Results. By analyzing and comparing the prediction of the neural network with the target magnetogram, we believe that our network model has learned a single-wavelength full-disk calibration model. The mean absolute error (MAE) of the longitudinal field and the transverse field of the full disk are 3.68 G and 28.08 G, respectively. The MAE error of the azimuth angle of pixels above 300 G is 12.29°.
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