Simulated datasets for detector and particle flow reconstruction: CLD detector model for FCC-ee, machine learning format

Dataset used for: 10.48550/arXiv.2503.00131 Derived from https://zenodo.org/records/14930758, prepared in a machine-learning friendly TFDS format, ready to be used with https://zenodo.org/records/14930299. cld_edm_ttbar_pf.tar: ee -> ttbar, center of mass energy at 365 GeV The TFDS format consists of 2 splits, with roughly 400k events per split, amounting to a total of about 800k events. Contents Each .tar file contains the dataset in the tensorflow-datasets (minimum version v4.9.1), array_record format. Dataset semantics Each dataset consists of events that can be iterated over using the tensorflow-datasets library in either tensorflow or pytorch. Each event has the following information available: X: the reconstruction input features, i.e. tracks and clusters ygen: the ground truth particles with the features ["PDG", "charge", "pt", "eta", "sin_phi", "cos_phi", "energy", "jet_idx"], with "jet_idx" corresponding to the gen-jet assignment of this particle ycand: the baseline Pandora PF particles with the features ["PDG", "charge", "pt", "eta", "sin_phi", "cos_phi", "energy", "jet_idx"], with "jet_idx" corresponding to the gen-jet assignment of this particle The full semantics, including the list of features for X, are available at https://github.com/jpata/particleflow/releases/tag/v2.3.0