21 citations · 41 across the 4 of their papers we have counts for
5 papers
Toward a Multimodal Foundation Model for Plasma State Reconstruction
Bin Xia, Chuanfei Dong, Boting Li +9
Plasma experiments observe coupled physical states through sparse, heterogeneous, and incomplete diagnostics. We present a proof of concept toward a multimodal foundation model for…
Automated Classification of Plasma Regions at Mars Using Machine Learning
Yilan Qin, Chuanfei Dong, Hongyang Zhou +6
The plasma environment around Mars is highly variable because it is strongly influenced by the solar wind. Accurate identification of plasma regions around Mars is important for th…
Physics-Informed Neural Networks for Modeling the Martian Induced Magnetosphere
Jiawei Gao, Chuanfei Dong, Chi Zhang +6
Understanding the magnetic field environment around Mars and its response to upstream solar wind conditions provide key insights into the processes driving atmospheric ion escape.…
Data-driven modeling of Landau damping by physics-informed neural networks
Yilan Qin, Jiayu Ma, Mingle Jiang +5
Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the lon…
Data-driven, multi-moment fluid modeling of Landau damping
Wenjie Cheng, Haiyang Fu, Liang Wang +6
Deriving governing equations of complex physical systems based on first principles can be quite challenging when there are certain unknown terms and hidden physical mechanisms in t…