Data-driven construction of a generalized kinetic collision operator from molecular dynamics
Zhao, Yue, Burby, Joshua W., Christlieb, Andrew, Lei, Huan
–arXiv.org Artificial Intelligence
We introduce a data-driven approach to learn a generalized kinetic collision operator directly from molecular dynamics. Unlike the conventional (e.g., Landau) models, the present operator takes an anisotropic form that accounts for a second energy transfer arising from the collective interactions between the pair of collision particles and the environment. Numerical results show that preserving the broadly overlooked anisotropic nature of the collision energy transfer is crucial for predicting the plasma kinetics with non-negligible correlations, where the Landau model shows limitations.
arXiv.org Artificial Intelligence
Apr-4-2025
- Country:
- North America > United States > Texas (0.28)
- Genre:
- Research Report > New Finding (0.34)
- Industry:
- Energy (0.47)
- Technology: