{"url":"/dataset/stellarators","name":"Stellarators","full_name":null,"description_markdown":"This dataset comprises a collection of stellarator configurations used to train the model over multiple iterations. Within the 1_dataset folder, you’ll find the initial dataset, which was constructed using the Near-Axis Expansion method, leveraging the pyQSC package. Subsequent files in this dataset were generated following the methodology outlined in the accompanying research paper.","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.13623959","introduced_date":"2024-08-31","introduced_date_note":null,"introduced_by":{"paper":"/paper/using-deep-learning-to-design-high-aspect","title":"Using Deep Learning to Design High Aspect Ratio Fusion Devices","first_author":"P. Curvo","url":null},"license":null,"modalities":[],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Stellarators"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}