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Dataset . 2022
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Dataset . 2022
License: CC BY
Data sources: Datacite
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Fast Calorimeter Simulation Challenge 2022 - Dataset 3

Authors: Faucci Giannelli, Michele; Kasieczka, Gregor; Krause, Claudius; Nachman, Ben; Salamani, Dalila; Shih, David; Zaborowska, Anna;

Fast Calorimeter Simulation Challenge 2022 - Dataset 3

Abstract

This is dataset 3 of the “Fast Calorimeter Simulation Challenge 2022”. It consists of four files with 50k GEANT4-simulated showers each of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV. The detector geometry is similar to dataset 2, but has a much higher granularity. Each of the 45 layer has now 18 radial and 50 angular bins, totalling 18x50x45=40500 voxels. This dataset was produced using the Par04 Geant4 example. dataset_3_1.hdf5 and dataset_3_2.hdf5 should be used for training, dataset_3_3.hdf5 and dataset_3_4.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/

Keywords

CaloChallenge, Calorimeter, Generative Model

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selected citations
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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