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From the 1 of 5 linked papers with an AI index.

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5 papers

physics.plasm-ph2026

A Shortcut to Statistically Steady-State Turbulence with Flow Matching

Gianluca Galletti, Gerald Gutenbrunner, William Hornsby +5

The paper presents GyroFlow, a latent generative model that directly creates statistically steady‑state snapshots of gyrokinetic turbulence, avoiding the costly transient simulatio…

physics.plasm-ph2026

GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations

Fabian Paischer, Gianluca Galletti, William Hornsby +5

Nuclear fusion plays a pivotal role in the quest for reliable and sustainable energy production. A major roadblock to viable fusion power is understanding plasma turbulence, which…

physics.plasm-ph2026

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…

cs.DC2025

A Performance Analysis of Task Scheduling for UQ Workflows on HPC Systems

Chung Ming Loi, Anne Reinarz, Mikkel Lykkegaard +3

Uncertainty Quantification (UQ) workloads are becoming increasingly common in science and engineering. They involve the submission of thousands or even millions of similar tasks wi…

physics.plasm-ph2025

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…