9 citations · 9 across the 11 of their papers we have counts for
6 papers · 1 filter
MVPinn: Integrating Milne-Eddington Inversion with Physics-Informed Neural Networks for GST/NIRIS Observations
Qin Li, Bo Shen, Haodi Jiang +5
We introduce MVPinn, a Physics-Informed Neural Network (PINN) approach tailored for solving the Milne-Eddington (ME) inversion problem, specifically applied to spectropolarimetric…
Formation of chromospheric fan-shaped jets through magnetic reconnection
Annu Bura, Tanmoy Samanta, Avijeet Prasad +4
Recurrent chromospheric fan-shaped jets highlight the highly dynamic nature of the solar atmosphere. They have been named as ''light walls'' or ''peacock jets'' in high-resolution…
Unveiling the Dynamics and Genesis of Small-scale Fine Structure Loops in the Lower Solar Atmosphere
Annu Bura, Tanmoy Samanta, Alphonse Sterling +4
Recent high-resolution solar observations have unveiled the presence of small-scale loop-like structures in the lower solar atmosphere, often referred to as unresolved fine structu…
Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model
Jialiang Li, Vasyl Yurchyshyn, Jason T. L. Wang +6
We present a novel deep generative model, named GenMDI, to improve the temporal resolution of line-of-sight (LOS) magnetograms of solar active regions (ARs) collected by the Michel…
Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model
Hongyang Zhang, Ju Jing, Jason T. L. Wang +6
We present a transformer model, named DeepHalo, to predict the occurrence of halo coronal mass ejections (CMEs). Our model takes as input an active region (AR) and a profile, where…
Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning
Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang +6
The application of machine learning to the study of coronal mass ejections (CMEs) and their impacts on Earth has seen significant growth recently. Understanding and forecasting CME…