Published June 30, 2023 | Version v3
Dataset Open

Fast Calorimeter Simulation Challenge 2022 - Dataset 1

  • 1. INFN Rome 2
  • 2. ROR icon Universität Hamburg
  • 3. Rutgers University
  • 4. LBL, Berkeley
  • 5. Geneva University
  • 6. Warsaw U. of Tech.

Description

This is dataset 1 of the “Fast Calorimeter Simulation Challenge 2022”. It is based on the ATLAS GEANT4 open datasets that were published here. There are four files, two for photons and two for charged pions. Each dataset contains the voxelised shower information obtained from single particles produced at the calorimeter surface in the η range (0.2-0.25) and simulated in the ATLAS detector. Each file contains "incident_energies" of shape (num_showers, 1) and "showers" of shape (num_showers, num_voxels). There are 15 incident energies from 256 MeV up to 4 TeV produced in powers of two. 10k events are available in each sample with the exception of those at higher energies that have a lower statistics. These samples were used to train the corresponding two GANs presented in the AtlFast3 paper SIMU-2018-04 and in the FastCaloGAN note ATL-SOFT-PUB-2020-006. The number of radial and angular bins varies from layer to layer and is also different for photons and pions, resulting in 368 voxels for photons and 533 for pions.

dataset_1_photons_1.hdf5 and dataset_1_pions_1.hdf5 should be used for training, dataset_1_photons_2.hdf5 and dataset_1_pions_2.hdf5 for evaluation.

More details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/

Files

Files (685.1 MB)

Name Size Download all
md5:005d2adeda7db034b388112661265656
173.8 MB Download
md5:4767715ed56e99565fd9c67340661e70
173.7 MB Download
md5:6a5f52722064a1bcd8a0bc002f16515d
167.3 MB Download
md5:fee7457b40127bc23c8ab909e2638ca0
170.3 MB Download

Additional details

Related works

Is continued by
Dataset: 10.5281/zenodo.6366270 (DOI)
Dataset: 10.5281/zenodo.6366323 (DOI)
Is derived from
Dataset: 10.7483/OPENDATA.ATLAS.UXKX.TXBN (DOI)
Is described by
https://calochallenge.github.io/homepage/ (URL)