1 citations · 1 across the 2 of their papers we have counts for
3 papers
Physics-Informed Neural Compression of High-Dimensional Plasma Data
Gianluca Galletti, Gerald Gutenbrunner, Sandeep S. Cranganore +6
High-fidelity scientific simulations are now producing unprecedented amounts of data, creating a storage and analysis bottleneck. A single simulation can generate tremendous data v…
5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence
Gianluca Galletti, Fabian Paischer, Paul Setinek +5
Nuclear fusion plays a pivotal role in the quest for reliable and sustainable energy production. A major roadblock to achieving commercially viable fusion power is understanding pl…
Neural operator surrogate models of plasma edge simulations: feasibility and data efficiency
N. Carey, L. Zanisi, S. Pamela +7
The inclusion of high-fidelity simulations of SOL turbulence and transient MHD events such as ELMs in highly iterative applications remains computationally prohibitive, limiting th…