5 papers
A Deep Learning Framework for Predicting Solar EUV Irradiance During Significant Flares
Sathvik Soman, Jason T. L. Wang, Haimin Wang +1
We present FlareEUV, a multimodal deep learning framework for predicting daily extreme ultraviolet (EUV) irradiance at 6.5 nm over three consecutive days during significant solar f…
Reconstructing Synthetic SDO/AIA 193 A EUV Images from He I 10830 A Observations with Diffusion Model Translator
Marco Marena, Qin Li, Haimin Wang +3
Routine full-disk EUV imaging has been available only since the modern era, such as SOHO and SDO. To extend EUV coronal context into earlier periods, we leverage the multi-decade a…
Out-of-Sample Validation of MagNet
Aryiadna Yesmanchyk, Yan Xu, Jason T. L. Wang +3
Machine learning is starting to be used in almost every industry and academic research, and solar physics is no exception. A newly developed machine learning model named MagNet hel…
Reconstruction of Solar EUV Irradiance Using CaII K Images and SOHO/SEM Data with Bayesian Deep Learning and Uncertainty Quantification
Haodi Jiang, Qin Li, Jason T. L. Wang +2
Solar extreme ultraviolet (EUV) irradiance plays a crucial role in heating the Earth's ionosphere, thermosphere, and mesosphere, affecting atmospheric dynamics over varying time sc…
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…