Gyrokinetic adiabatic electron turbulence (256 trajectories) Adiabatic electron gyrokinetic turbulence simulations (GKW): the full 5D distribution function and electrostatic potentials at every timestep, in bfloat16. This is the dataset used to train the GyroSwin neural surrogates. GyroSwin (surrogate model, source of this dataset): https://arxiv.org/abs/2510.07314 PINC (physics informed neural compression): https://arxiv.org/abs/2602.04758v2 Code: https://github.com/ml jku/neural gyrokinetics Parameter scan Cyclone Base Case (CBC) ion temperature gradient turbulence, scanned across the trajectories: Parameter Range ion temperature gradient 3.71 – 11.97 density gradient 0.00 – 6.99 magnetic shear (ŝ) 0.51 – 5.00 safety factor (q) 1.55 – 8.99 Grid resolution (nvpar, nmu, ns, nkx, nky) = (32, 8, 16, 85, 32) , fixed across trajectories. Storage precision (bf16) Data is stored in bfloat16. Reconstruction loss vs float32, over ~4900 random snapshots across all trajectories: quantity mean worst 5D field PSNR ↑ 85.5 72.7 5D field rel. L2 ↓ 1.66e 3 1.69e 3 heat flux rel. L1 ↓ 7.0e 6 2.1e 4 potential rel. L1 ↓ 2.2e 4 4.6e 3 Structure Usage Download the dataset (the full set is large; grab o…
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