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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Evaluation of the CaloINN generative network - Fast detector simulation

Authors: Favaro, Luigi; Florian, Ernst;

Evaluation of the CaloINN generative network - Fast detector simulation

Abstract

These are the sampled used in the paper "Normalizing Flows for High-Dimensional Detector Simulations" for the evaluation of the CaloINN and the CaloVAE+INN models. Each zip file contains the generated showers stored in the CaloChallenge format together with figures of high-level observables. We include the layer energy deposition, the center of energy, the width of the center of energy, the layer sparsity, the ratio E_tot/E_inc, and the full voxel energy distribution. For these features we provide: energy inclusive histograms for all the datasets; for dataset 1, three incident energies: 256 MeV, 8.192GeV, 262.144 GeV; for dataset 2 and 3, three incident energy windows, (1-10), (10-100), (100-1000) GeV; separation power between Geant4 and our samples calculatd from the histograms.

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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).
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!
1
Average
Average
Average