Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field Model
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
Exploring the outer atmosphere of the sun has remained a significant bottleneck in astrophysics, given the intricate magnetic formations that significantly influence diverse solar events. Magnetohydrodynamics (MHD) simulations allow us to model the complex interactions between the sun's plasma, magnetic fields, and the surrounding environment. However, MHD simulation is extremely time-consuming, taking days or weeks for simulation. The goal of this study is to accelerate coronal magnetic field simulation using deep learning, specifically, the Fourier Neural Operator (FNO). FNO has been proven to be an ideal tool for scientific computing and discovery in the literature. In this paper, we proposed a global-local Fourier Neural Operator (GL-FNO) that contains two branches of FNOs: the global FNO branch takes downsampled input to reconstruct global features while the local FNO branch takes original resolution input to capture fine details. The performance of the GL-FNO is compared with state-of-the-art deep learning methods, including FNO, U-NO, U-FNO, Vision Transformer, CNN-RNN, and CNN-LSTM, to demonstrate its accuracy, computational efficiency, and scalability. Furthermore, physics-based analysis from domain experts is also performed to demonstrate the reliability of GL-FNO. The results show that GL-FNO not only accelerates the MHD simulation (a few seconds for prediction, more than ×20,000 speed up) but also provides reliable prediction capabilities, thus greatly contributing to the understanding of space weather dynamics. Our code implementation is available at https://github.com/Yutao-0718/GL-FNO.
Identifier
85218072575 (Scopus)
ISBN
[9798350362480]
Publication Title
Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024
External Full Text Location
https://doi.org/10.1109/BigData62323.2024.10825452
First Page
1964
Last Page
1971
Grant
AST-2204384
Fund Ref
National Science Foundation
Recommended Citation
Du, Yutao; Li, Qin; Gnanasambandam, Raghav; Du, Mengnan; Wang, Haimin; and Shen, Bo, "Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field Model" (2024). Faculty Publications. 700.
https://digitalcommons.njit.edu/fac_pubs/700
