NEOPIC

Kinetic plasma simulations play a critical role in applications of societal relevance such as nuclear fusion and building the next-generation of compact particle accelerators. They are also widely used in studying astrophysical phenomena and industrial plasma processes. Particle methods, specifically particle-in-cell (PIC), have been the method of choice for such simulations for many decades.

PIC simulations demand high computational costs imposed by the stability requirements of the solvers making them prohibitively expensive for parameter studies, uncertainty quantification and long simulation times.

The ambitious goal of this project is to combine particle schemes with the recently introduced neural operators, achieving fast, accurate kinetic plasma simulations. For the first time, we will demonstrate the applicability of neural operators in solving complex, nonlinear, high dimensional, multi-scale PDE in a massively parallel framework computing the motion of trillions of particles. JSC plays the role of coordinator, designing the particle-in-neural operator scheme for electrostatic plasma simulations and HPC strategies for it.