collaborators

5 papers

physics.plasm-ph2026

Real-time virtual circuits for plasma shape control via neural network emulators: experimental demonstration on MAST Upgrade

Nicola C. Amorisco, Kamran Pentland, Adriano Agnello +12

Conventional plasma shape control in tokamaks relies on virtual circuits (VCs) that are computed offline from linearisations around a small, tailored number of reference equilibria…

physics.plasm-ph2026

The FreeGSNKE Pulse Design Tool (FPDT): a computational framework for evolutive plasma scenario and control design

K. Pentland, N. C. Amorisco, A. Ross +8

We present the FreeGSNKE Pulse Design Tool (FPDT), an open-source, Python-based computational framework that enables in silico testing and predictive design of tokamak plasma scena…

physics.plasm-ph2026

TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics

Tobia Boschi, Andrea Loreti, Nicola C. Amorisco +13

We present TokaMind, to our knowledge the first open-source foundation model for tokamak plasma dynamics, based on a Multi-Modal Transformer (MMT) and pretrained on heterogeneous d…

physics.plasm-ph2026

TokaMark: A Comprehensive Benchmark for MAST Tokamak Plasma Models

Cécile Rousseau, Samuel Jackson, Rodrigo H. Ordonez-Hurtado +13

Development and operation of commercially viable fusion energy reactors such as tokamaks require accurate predictions of plasma dynamics from sparse, noisy, and incomplete sensors…

physics.plasm-ph2024

Validation of the static forward Grad-Shafranov equilibrium solvers in FreeGSNKE and Fiesta using EFIT++ reconstructions from MAST-U

K. Pentland, N. C. Amorisco, O. El-Zobaidi +10

A key aspect in the modelling of magnetohydrodynamic (MHD) equilibria in tokamak devices is having access to fast, accurate, and stable numerical simulation methods. There is an in…