collaborators

5 papers

physics.plasm-ph2026

Counter-streaming heat-flux closure for electron-only collisionless magnetic reconnection

Madox C. McGrae-Menge, Jacob R. Pierce, Maria Almanza +6

In electron-only collisionless magnetic reconnection (MR), a regime of growing importance in turbulent space plasmas, electrons develop strongly non-Maxwellian distributions that i…

cs.AI2026

The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)

Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97

This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…

physics.plasm-ph2025

Data-driven multi-species heat flux closures for two-stream-unstable plasmas with nonlinear sparse regression

Emil R. Ingelsten, Madox C. McGrae-Menge, E. Paulo Alves +1

The dual aims of accuracy and computational efficiency in computational plasma physics lend themselves well to the use of fluid models. The first of these goals, however, is only s…

physics.plasm-ph2025

Embedding physical symmetries into machine-learned reduced plasma physics models via data augmentation

Madox C. McGrae-Menge, Jacob R. Pierce, Frederico Fiuza +1

Machine learning is offering powerful new tools for the development and discovery of reduced models of nonlinear, multiscale plasma dynamics from the data of first-principles kinet…

physics.plasm-ph2025

Data-driven discovery of a heat flux closure for electrostatic plasma phenomena

Emil R. Ingelsten, Madox C. McGrae-Menge, E. Paulo Alves +1

Progress in understanding multi-scale collisionless plasma phenomena requires employing tools which balance computational efficiency and physics fidelity. Collisionless fluid model…