Physics-Informed Neural Networks (PINN) are neural networks encoding the problem
governing equations, such as Partial Differential Equations (PDE), as a part of the neural …

This review aims at providing an up-to-date status and a general introduction to the subject
of the numerical study of energetic particle acceleration and transport in turbulent …

Abstract The Particle-In-Cell (PIC) method has been developed by Oscar Buneman, Charles
Birdsall, Roger W. Hockney, and John Dawson in the 1950s and, with the advances of …

Magnetohydrodynamics (MHD)-based global space weather models have mostly been
developed and maintained at academic institutions. While the “free spirit” approach of …

Coulomb collisions provide plasma resistivity and diffusion but in many low-density
astrophysical plasmas such collisions between particles are extremely rare. Scattering of …

We report a new particle in cell (PIC) method based on the semi-implicit approach. The
novelty of the new method is that unlike any of its semi-implicit predecessors at the same …

Computational models based on a fluid description of the plasma, such as
magnetohydrodynamic (MHD) and extended magnetohydrodynamic (XMHD) codes are …

We review the application of particle simulation techniques to the full kinetic study of space
weather events. We focus especially on the methods designed to overcome the difficulties …

The primary target of the Magnetospheric MultiScale (MMS) mission is the electron-scale
diffusion layer around reconnection sites. Here we study where these regions are found in …

We have recently developed a new modeling capability to embed the implicit particle‐in‐cell
(PIC) model iPIC3D into the Block‐Adaptive‐Tree‐Solarwind‐Roe‐Upwind‐Scheme …