{"url":"/dataset/jetclass","name":"JetClass","full_name":"A Large-Scale Dataset for Deep Learning in Jet Physics","description_markdown":"JetClass is a new large-scale dataset to facilitate deep learning research in particle physics. It consists of 100M particle jets for training, 5M for validation and 20M for testing. The dataset contains 10 classes of jets, simulated with [MadGraph](https://launchpad.net/mg5amcnlo) + [Pythia](https://pythia.org/) + [Delphes](https://cp3.irmp.ucl.ac.be/projects/delphes). A detailed description of the JetClass dataset is presented in the paper [Particle Transformer for Jet Tagging](https://arxiv.org/abs/2202.03772). An interface to use the dataset is provided [here](https://github.com/jet-universe/particle_transformer).","description_withheld":null,"homepage":"https://zenodo.org/record/6619768","introduced_date":"2022-06-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/particle-transformer-for-jet-tagging","title":"Particle Transformer for Jet Tagging","first_author":"Huilin Qu","url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[{"name":"Point cloud","url":"/datasets/modality/point-cloud"},{"name":"Physics","url":"/datasets/modality/physics"}],"tasks":[{"name":"Point Cloud Generation","url":"/task/point-cloud-generation","datasets_with_task":"/datasets/task/point-cloud-generation"},{"name":"Point Cloud Classification","url":"/task/point-cloud-classification","datasets_with_task":"/datasets/task/point-cloud-classification"},{"name":"Jet Tagging","url":"/task/jet-tagging","datasets_with_task":"/datasets/task/jet-tagging"}],"languages":[],"variants":["JetClass"],"data_loaders":[],"num_papers_in_archive":11,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/jet-tagging-on-jetclass","task":"Jet Tagging","dataset_variant":"JetClass","rows":2,"metrics":["Accuracy","AUC","FLOPs","#Params"],"first_row_in_archive_order":{"model":"ParT","paper":"/paper/particle-transformer-for-jet-tagging","metrics":{"#Params":"2140000","AUC":"0.9877","Accuracy":"0.861","FLOPs":"340000000"},"code_links":[{"title":"jet-universe/particle_transformer","url":"https://github.com/jet-universe/particle_transformer"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/particle-transformer-for-jet-tagging","title":"Particle Transformer for Jet Tagging","date":"2022-02-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/particlenet-jet-tagging-via-particle-clouds","title":"ParticleNet: Jet Tagging via Particle Clouds","date":"2019-02-22","rows_on_this_dataset":1,"code_links":6,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":23,"samples_ran":2,"samples_unverified":21,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":24,"samples_ran":3,"samples_unverified":21,"pointer_only_for_licence":1,"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."}