Published June 1, 2025 | Version v1
Dataset Open

Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 2

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. ROR icon IBM Research - India
  • 12. ROR icon Heidelberg University
  • 13. University of Washington
  • 14. ROR icon National Tsing Hua University
  • 15. ROR icon IBM Research - Thomas J. Watson Research Center
  • 16. ROR icon Shanghai Jiao Tong University
  • 17. ROR icon University College London
  • 18. ROR icon National Energy Research Scientific Computing Center
  • 19. ROR icon Forschungszentrum Jülich
  • 20. Yale University

Description

These are all the submitted samples to dataset 2 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.6366271 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
_3 conv. L2LFlows arXiv:2405.20407
_4 CaloINN arXiv:2312.09290
_5 MDMA arXiv:2305.15254 arXiv:2408.04997
_7 Calo-VQ arXiv:2405.06605
_8 CaloScore arXiv:2206.11898, arXiv:2308.03847
_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
_15 SuperCalo arXiv:2308.11700
_22 DeepTree arXiv:2311.12616, arXiv:2312.00042
_23 CaloPointFlow arXiv:2403.15782
_27 CaloVAE+INN arXiv:2312.09290
_30 CaloLatent ML4PS@NeurIPS
_32 CaloDiT ACAT
_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 (13.9 GB)

Name Size Download all
md5:c5e4827faffce1ac0aeea7749de5f9f3
739.1 MB Download
md5:430c1dee23b46343e4acfa41f6079144
759.4 MB Download
md5:59ed21469e376a69436a7775c7f0b322
725.8 MB Download
md5:5dff5a57b37603b5f63ed809cdc82b09
725.9 MB Download
md5:e1dc931e92589f3cced2f6983e8af7ee
725.9 MB Download
md5:8ad8a812ad621248e11ca27debf358e8
686.3 MB Download
md5:d364fec36ca0c715b26cbdf30c76e1ea
707.0 MB Download
md5:0cf64c86d46ed8ced458477446587fdd
1.3 GB Download
md5:019effa4af6cef164bf45c798ab84f47
717.5 MB Download
md5:d7993d62f5f7fc2e64a77d8ae3fd8420
789.1 MB Download
md5:053192b7e062ec80ed5ed4c7cd391c8a
680.7 MB Download
md5:fd1d66db6e17ec8dd25c1f65f34a3d9f
727.9 MB Download
md5:a1d25f85d84e2f17e67700c1c3904621
707.8 MB Download
md5:1e9b134ffbe7f37665cba4cc6cad53bb
571.3 MB Download
md5:d625fcbaf007c51f9e1c2adbd8fa847e
1.9 GB Download
md5:6e2871ec4adb9541109e24de328087d2
736.3 MB Download
md5:ddd297d6cecb57b6694a0c78a851dcf1
765.7 MB Download

Additional details

Identifiers

arXiv
arXiv:2410.21611

Related works

Is derived from
Dataset: 10.5281/zenodo.6366271 (DOI)
Is supplement to
Dataset: 10.5281/zenodo.15961728 (DOI)
Dataset: 10.5281/zenodo.15961924 (DOI)
Dataset: 10.5281/zenodo.15962527 (DOI)

Software

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