Physics-informed Machine Learning

* highlights student work

1. Z. Huang, C. F. Dong, L. Wang, Machine Learning Heat Flux Closure for Multi-Moment Fluid Modeling of Nonlinear Landau Damping, submitted, 2024.

2. S. C. Wei*, Y. H. Liu*, H. Y. Fu, C. F. Dong, L. Wang, Data-Driven Modeling of Landau Damping by Fourier Neural Operator, 2023 International Applied Computational Electromagnetics Symposium (ACES), Hangzhou, China, pp. 01-03 (2023). arXiv:2308.02972

3. Y. Qin*, J. Ma*, M. Jiang*, C. F. Dong, H. Fu, L. Wang, W. Cheng, and Y. Jin, Data-driven modeling of Landau damping by physics-informed neural networks, Phys. Rev. Research 5, 033079 (2023). arXiv:2211.01021

4. W. J. Cheng*, H. Y. Fu, L. Wang,  C. F. Dong, Y. Q. Jin, M. L. Jiang, J. Y. Ma, Y. L. Qin, and K. X. Liu, Data-driven, multi-moment fluid modeling of Landau damping, Computer Physics Communications 282, 108538 (2023). arXiv:2209.04726.