3 papers
physics.plasm-ph2026
MPEX AI Digital Twins Milestone Report
Gary Staebler, Rhea Barnett, Mark Cianciosa +13
This is the six month progress report to Fusion Energy Science (FES) and the American Science Cloud (AmSC) on the MPEX AI Digtial Twins project that was started in October 2025. Th…
physics.plasm-ph2026
MPEX AI Digital Twins
Gary Staebler, Rhea Barnett, Mark Cianciosa +10
Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analy…
physics.plasm-ph2026
A machine learning framework for developing quasilinear saturation rules of turbulent transport from linear gyrokinetic data
Preeti Sar, Sebastian De Pascuale, Harry Dudding +1
A new neural network model for a quasilinear saturation rule has been developed to map linear gyrokinetic data to nonlinear saturated potential magnitudes to predict the total ener…