209 citations · 1.3k across the 47 of their papers we have counts for
8 papers · 1 filter
Data-Driven Modeling of Landau Damping by Fourier Neural Operator
Shichen Wei, Yuhong Liu, Haiyang Fu +2
The development of machine learning techniques enables us to construct surrogate models from data of direct numerical simulations, which has important implications for modeling com…
Numerical Study of Magnetic Island Coalescence Using Magnetohydrodynamics With Adaptively Embedded Particle-In-Cell Model
Dion Li, Yuxi Chen, Chuanfei Dong +2
Collisionless magnetic reconnection typically requires kinetic treatments that are, in general, computationally expensive compared to fluid-based models. In this study, we use the…
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…
Discovery of double Hall pattern associated with collisionless magnetic reconnection in dusty plasmas
Shu-Di Yang, Liang Wang, Chuanfei Dong
Magnetic reconnection is prevalent in magnetized plasmas in space and laboratories. Despite significant investigations on reconnection in electron-ion plasmas, studies of reconnect…
Role of the Plasmoid Instability in Magnetohydrodynamic Turbulence
Chuanfei Dong, Liang Wang, Yi-Min Huang +2
The plasmoid instability in evolving current sheets has been widely studied due to its effects on the disruption of current sheets, the formation of plasmoids, and the resultant fa…