Solar Active Region Magnetograms Generation by Attention Generative Adversarial Networks


 Learning the mapping of magnetograms and EUV images is important for understanding the solar eruption mechanism and space weather forecasting. Previous works are mainly based on the pix2pix model for full-disk magnetograms generation and obtain good performance. However, in general, we are more concerned with the magnetic field distribution in the active regions (ARs) where various solar storms such as the solar flare and coronal mass ejection (CME) happen. In this paper, we fuse the self-attention mechanism with the pix2pix model which allows more computation resource and greater weight for strong magnetic region. In addition, the attention features are concatenated by the Residual Hadamard Production (RHP) with the abstracted features after the encoder. We named our model as RHP-attention pix2pix. From the experiments, we can find that the proposed model can generate magnetograms with finer strong magnetic structures, such as sunspots. In addition, the polarity distribution of generated magnetograms is more consistent with observed ones.