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From the 1 of 10 linked papers with an AI index.

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10 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…

cs.LG2026

A fully GPU-based workflow for building physics emulators of hypersonic flows

Fabian Paischer, Dylan Rubini, Deniz A. Bezgin +6

The ability to resolve complex physical phenomena with high fidelity and at low computational cost is central to addressing key challenges in modern engineering. A prime example li…

cs.LG2026

ANTIC: Adaptive Neural Temporal In-situ Compressor

Sandeep S. Cranganore, Andrei Bodnar, Gianluca Galletti +2

The persistent storage requirements for high-resolution, spatiotemporally evolving fields governed by large-scale and high-dimensional partial differential equations (PDEs) have re…

physics.plasm-ph2026

gyaradax: Local Gyrokinetics JAX Code

Gianluca Galletti, Eric Volkmann, Johannes Brandstetter

Gyrokinetic simulations are essential for understanding and controlling turbulence in fusion plasmas, yet they are oftentimes implemented in legacy codebases, in many cases CPU-bou…

cs.LG2026

Stabilizing Test-Time Adaptation of High-Dimensional Simulation Surrogates via D-Optimal Statistics

Anna Zimmel, Paul Setinek, Gianluca Galletti +2

Machine learning surrogates are increasingly used in engineering to accelerate costly simulations, yet distribution shifts between training and deployment often cause severe perfor…