Fast Calorimeter Simulation Challenge 2022 - Dataset 1

<p>This is dataset 1 of the &ldquo;Fast Calorimeter Simulation Challenge 2022&rdquo;. It is based on the ATLAS GEANT4 open datasets that were published&nbsp;<a href="http://opendata-qa.cern.ch/record/15012">here</a>. 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 &eta; range (0.2-0.25) and simulated in the ATLAS detector. Each file contains &quot;incident_energies&quot; of shape (num_showers, 1) and &quot;showers&quot; 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&nbsp;<a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SIMU-2018-04/">SIMU-2018-04</a>&nbsp;and in the FastCaloGAN note&nbsp;<a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-SOFT-PUB-2020-006/">ATL-SOFT-PUB-2020-006</a>. 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.</p> <p>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.</p> <p>More details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at&nbsp;<a href="https://calochallenge.github.io/homepage/">https://calochallenge.github.io/homepage/</a></p>