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Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms

Maloney, Shane A.; Muñoz-Jaramillo, Andrés; Wright, Paul J. +7 more

Superresolution (SR) aims to increase the resolution of images by recovering detail. Compared to standard interpolation, deep learning-based approaches learn features and their relationships to leverage prior knowledge of what low-resolution patterns look like in higher resolution. Deep neural networks can also perform image cross-calibration by l…

CAMEL. II. A 3D Coronal Mass Ejection Catalog Based on Coronal Mass Ejection Automatic Detection with Deep Learning

Zhang, Yan; Feng, Li; Lu, Lei +5 more

Coronal mass ejections (CMEs) are major drivers of geomagnetic storms, which may cause severe space weather effects. Automating the detection, tracking, and three-dimensional (3D) reconstruction of CMEs is important for operational predictions of CME arrivals. The COR1 coronagraphs on board the Solar Terrestrial Relations Observatory spacecraft ha…

An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning

Shen, Fang; Yang, Yi; Li, Yucong +2 more

Coronal mass ejections (CMEs) constitute the major source of severe space weather events, with the potential to cause enormous damage to humans and spacecraft in space. It is becoming increasingly important to detect and track CMEs, since there are more and more space activities and facilities. We have developed a new algorithm to automatically de…

CME Arrival Time Prediction via Fusion of Physical Parameters and Image Features

Xu, Long; Huang, Xin; Zhao, Dong +1 more

Coronal mass ejections (CMEs) are among the most intense phenomena in the Sun–Earth system, often resulting in space environment effects and consequential geomagnetic disturbances. Consequently, quickly and accurately predicting CME arrival time is crucial to minimize the harm caused to the near-Earth space environment. To forecast the arrival tim…

A Multibranch Deep Neural Network for the Superresolution of Solar Magnetograms

Xu, Long; Zhao, Dong; Dou, Fengping +1 more

The existing superresolution (SR) models for solar magnetograms are mostly borrowed from the SR models for natural images. They are less effective for processing solar magnetograms with a very large dynamic range and very rich image features. In this paper, a multibranch superresolution (MBSR) model is specially designed for solar magnetograms. Fi…