{"url":"/dataset/top-jet-w-momentum-reconstruction-dataset","name":"Top Jet W-Momentum Reconstruction Dataset","full_name":null,"description_markdown":"A set of Monte Carlo simulated events, for the evaluation of top quarks' (and their child particles') momentum reconstruction, produced using the HEPData4ML package [1]. Specifically, the entries in this dataset correspond with top quark jets, and the momentum of the jets' constituent particles. This is a newer version of the \"Top Quark Momentum Reconstruction Dataset\", but with sufficiently large changes to warrant this separate posting.\r\n\r\n[1] J. T. Offermann, X. Liu, and T. Hoffman, HEPData4ML (2023), https://github.com/janTOffermann/HEPData4ML.","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.8197723","introduced_date":"2023-07-31","introduced_date_note":null,"introduced_by":{"paper":"/paper/explainable-equivariant-neural-networks-for","title":"Explainable Equivariant Neural Networks for Particle Physics: PELICAN","first_author":"Alexander Bogatskiy","url":null},"license":{"name":"Creative Commons Attribution 4.0","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[],"tasks":[],"languages":[],"variants":["Top Jet W-Momentum Reconstruction Dataset"],"data_loaders":[],"num_papers_in_archive":1,"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":"2026-09-25T09:33:49+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."}