AI-assisted prediction of laser-plasma instabilities for inertial confinement fusion

Predicting and controlling hot electron generation from laser-plasma instabilities(LPI) is a critical challenge in direct-drive inertial confinement fusion (ICF). In this project we leverage generative AI to develop physics-informed ignition-scale LPI packages that can be incorporated into ICF design codes. We will present preliminary results utilizing generic large language models (LLMs) to model hot electron generation and employ diffusion-model-based scientific simulation methodologies as an alternative to costly particle-in-cell (PIC) simulations. Additionally, we will address the trustworthiness of these generative AI models.