Downloads provided by UsageCounts
This is dataset 2 of the “Fast Calorimeter Simulation Challenge 2022”. It consists of two files with 100k GEANT4-simulated showers each of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV. The detector has a concentric cylinder geometry with 45 layers, where each layer consists of active (silicon) and passive (tungesten) material. Each layer has 144 readout cells, 9 in radial and 16 in angular direction, yielding a total of 9x16x45 = 6480 voxels. dataset_2_1.hdf5 should be used for training, dataset_2_2.hdf5 can be used as reference in the 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/
CaloChallenge, Calorimeter, Generative Model
CaloChallenge, Calorimeter, Generative Model
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 125 | |
| downloads | 98 |

Views provided by UsageCounts
Downloads provided by UsageCounts