GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations
Paper • 2510.07314 • Published • 4
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ValueError
Message: Illegal slicing argument for scalar dataspace
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 87, in _generate_tables
pa_table = _recursive_load_arrays(h5, self.info.features, start, end)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 273, in _recursive_load_arrays
arr = _recursive_load_arrays(dset, features[path], start, end)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 275, in _recursive_load_arrays
arr = _load_array(dset, path, start, end)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 242, in _load_array
arr = dset[start:end]
~~~~^^^^^^^^^^^
File "h5py/_objects.pyx", line 56, in h5py._objects.with_phil.wrapper
File "h5py/_objects.pyx", line 57, in h5py._objects.with_phil.wrapper
File "/usr/local/lib/python3.12/site-packages/h5py/_hl/dataset.py", line 879, in __getitem__
selection = sel2.select_read(fspace, args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/h5py/_hl/selections2.py", line 101, in select_read
return ScalarReadSelection(fspace, args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/h5py/_hl/selections2.py", line 86, in __init__
raise ValueError("Illegal slicing argument for scalar dataspace")
ValueError: Illegal slicing argument for scalar dataspaceNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
This repository contains data used in the paper GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations.
We provide snapshots for the in-distribution and out-of-distribution test cases presented in the paper and to be used with the pre-trained GyroSwin model series.
The data was generated using GKW considering the cyclone base case (CBC) mainly focusing on ion temperature gradient based turbulence. The provided simulations can be found at
📁 preprocessed
├── iteration_8.h5
├── iteration_115.h5
├── iteration_131.h5
├── iteration_148.h5
├── iteration_235.h5
├── iteration_262.h5
├── ood_iteration_0.h5
├── ood_iteration_1.h5
├── ood_iteration_2.h5
├── ood_iteration_3.h5
└── ood_iteration_4.h5
where files starting with ood_ are out-of-distribution with respect to the dataset the GyroSwin models were trained on and the remaining ones are considered in-distribution.
The data contains a single snapshot that was used for autoregressive prediction in the paper. Due to the prohibitive storage demands, we only provide the first snapshot, i.e. they can only be used for autoregressive prediction, but cannot be compared to ground-truth.
Furthermore, normalization statistics are provided at normalization_stats.pkl as they are needed for denormalizing the predictions to the original space before transforming back to fourier space.
Pre-trained model checkpoints
The pre-trained model checkpoints can be found at these links:
Example Usage
A script to run inference using any of our pre-trained models can be found in our Github repository at gyroswin/eval/inference_from_hf.py.
Furthermore, we provide different ways of visualizing 5D Gyrokinetics data in our github repository to visualize the predictions of our GyroSwin models.
Citation
If you found our work useful, please consider citing it:
@inproceedings{paischergyroswin,
title={GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations},
author={Paischer, Fabian and Galletti, Gianluca and Hornsby, William and Setinek, Paul and Zanisi, Lorenzo and Carey, Naomi and Pamela, Stanislas and Brandstetter, Johannes},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems}
}
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