Published June 1, 2025 | Version v1
Dataset Open

Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 3

Creators

  • 1. ROR icon Chalmers University of Technology
  • 2. ROR icon Universität Hamburg
  • 3. ROR icon Austrian Academy of Sciences
  • 4. ROR icon SLAC National Accelerator Laboratory
  • 5. ROR icon Stanford University
  • 6. ROR icon University of Geneva
  • 7. ROR icon Rutgers, The State University of New Jersey
  • 8. ROR icon European Organization for Nuclear Research
  • 9. ROR icon Fermi National Accelerator Laboratory
  • 10. ROR icon Deutsches Elektronen-Synchrotron DESY
  • 11. CERN
  • 12. ETH Zürich
  • 13. ROR icon Lawrence Berkeley National Laboratory
  • 14. ROR icon Heidelberg University
  • 15. University of Washington
  • 16. ROR icon National Tsing Hua University
  • 17. ROR icon Shanghai Jiao Tong University
  • 18. ROR icon National Energy Research Scientific Computing Center
  • 19. ROR icon Forschungszentrum Jülich
  • 20. Yale University
  • 21. ROR icon IBM Research - Thomas J. Watson Research Center

Description

These are all the submitted samples to dataset 3 of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 100k calorimeter showers of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV.

The training data (based on Geant4) can be found at https://doi.org/10.5281/zenodo.6366324, the paper describing the results is available on arXiv:2410.21611, and further 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/.

The subscripts in the file names corresponds to the individual submissions: 

ID number Submission name Original reference
_1 CaloDiffusion arXiv:2308.03876
_2 L2LFlows-MAF arXiv:2302.11594, arXiv:2405.20407
_3 conv. L2LFlows arXiv:2405.20407
_5 MDMA arXiv:2305.15254, arXiv:2408.04997
_6 CaloClouds arXiv:2305.04847,  arXiv:2309.05704
_7 Calo-VQ arXiv:2405.06605
_9 CaloScore distilled arXiv:2206.11898, arXiv:2308.03847
_10 CaloScore single-shot arXiv:2206.11898, arXiv:2308.03847
_13 iCaloFlow teacher arXiv:2305.11934
_14 iCaloFlow student arXiv:2305.11934
_21 Geant4-Transformer DOI
_23 CaloPointFlow arXiv:2403.15782
_27 CaloVAE+INN arXiv:2312.09290
_31 Calo-VQ(norm) arXiv:2405.06605
_33 CaloDREAM arXiv:2405.09629

The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.

 

Files

Files (41.5 GB)

Name Size Download all
md5:4449cd998950df6372a0aa496f304db9
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md5:d23df8304d4afdebc92803c882944eb7
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md5:aad395d937281d83a5e447cfafa91e1d
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md5:9384731f5e59b29f13af6a98ff8c69c5
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md5:627f59ddac4f3c375d536ee872ce1376
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md5:8c1984ae07473ff722de38aa1810469c
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md5:18f908a594aa4974d64f3f657a411ab6
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md5:7068f70d225c522e4a81888b5ea05d46
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md5:c736dcd6281983e603e1746ba7cbfd43
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md5:2f8fa8e1c9d32b37b5c1c785b5fd3954
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md5:b144164d8624d37825311eb80718521a
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md5:239773067a3755881fb288bd4879d867
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md5:da41189dd058b66255157c05ce1d0f2f
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md5:7eb9e7ea8527c994626aad4c20fd1bfc
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md5:f88788817a775b849c977fa6a07328b7
2.2 GB Download

Additional details

Identifiers

arXiv
arXiv:2410.21611

Related works

Is derived from
Dataset: 10.5281/zenodo.6366324 (DOI)
Is supplement to
Dataset: 10.5281/zenodo.15961728 (DOI)
Dataset: 10.5281/zenodo.15961924 (DOI)
Dataset: 10.5281/zenodo.15962050 (DOI)

Software

Repository URL
https://github.com/CaloChallenge/homepage