Use and Citations

Warning: This is a development version and should not be cited. To find the specific version to cite, please go to ReadTheDocs.

Citation

The preferred BibTeX entry for citation of pyhf includes both the Zenodo archive and the JOSS paper:

@software{pyhf,
  author = "{Heinrich, Lukas and Feickert, Matthew and Stark, Giordon}",
  title = "{pyhf: v0.6.0}",
  version = {0.6.0},
  doi = {10.5281/zenodo.1169739},
  url = {https://github.com/scikit-hep/pyhf},
}

@article{pyhf_joss,
  doi = {10.21105/joss.02823},
  url = {https://doi.org/10.21105/joss.02823},
  year = {2021},
  publisher = {The Open Journal},
  volume = {6},
  number = {58},
  pages = {2823},
  author = {Lukas Heinrich and Matthew Feickert and Giordon Stark and Kyle Cranmer},
  title = {pyhf: pure-Python implementation of HistFactory statistical models},
  journal = {Journal of Open Source Software}
}

Use in Publications

Updating list of citations and use cases of pyhf:

  • Waleed Abdallah and others. Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2. 2020. arXiv:2003.07868.

  • Gaël Alguero, Jan Heisig, Charanjit K. Khosa, Sabine Kraml, Suchita Kulkarni, Andre Lessa, Philipp Neuhuber, Humberto Reyes-González, Wolfgang Waltenberger, and Alicia Wongel. New developments in SModelS. In Tools for High Energy Physics and Cosmology. 12 2020. arXiv:2012.08192.

  • Gaël Alguero, Sabine Kraml, and Wolfgang Waltenberger. A SModelS interface for pyhf likelihoods. Sep 2020. arXiv:2009.01809.

  • J. Alison and others. Higgs Boson Pair Production at Colliders: Status and Perspectives. In B. Di Micco, M. Gouzevitch, J. Mazzitelli, and C. Vernieri, editors, Double Higgs Production at Colliders. 9 2019. arXiv:1910.00012.

  • B.C. Allanach, Tyler Corbett, and Maeve Madigan. Sensitivity of Future Hadron Colliders to Leptoquark Pair Production in the Di-Muon Di-Jets Channel. Eur. Phys. J. C, 80(2):170, 2020. arXiv:1911.04455, doi:10.1140/epjc/s10052-020-7722-3.

  • Andrei Angelescu, Darius A. Faroughy, and Olcyr Sumensari. Lepton Flavor Violation and Dilepton Tails at the LHC. Eur. Phys. J. C, 80(7):641, 2020. arXiv:2002.05684, doi:10.1140/epjc/s10052-020-8210-5.

  • Jack Y. Araz and others. Proceedings of the second MadAnalysis 5 workshop on LHC recasting in Korea. Mod. Phys. Lett. A, 36(01):2102001, 2021. arXiv:2101.02245, doi:10.1142/S0217732321020016.

  • Johann Brehmer, Felix Kling, Irina Espejo, and Kyle Cranmer. MadMiner: Machine learning-based inference for particle physics. Comput. Softw. Big Sci., 4(1):3, 2020. arXiv:1907.10621, doi:10.1007/s41781-020-0035-2.

  • G. Brooijmans and others. Les Houches 2019 Physics at TeV Colliders: New Physics Working Group Report. In 2020. arXiv:2002.12220.

  • Matthew Feickert, Lukas Heinrich, and Giordon Stark. Likelihood preservation and statistical reproduction of searches for new physics. EPJ Web Conf., 2020. doi:10.1051/epjconf/202024506017.

  • Lukas Heinrich, Holger Schulz, Jessica Turner, and Ye-Ling Zhou. Constraining A₄ Leptonic Flavour Model Parameters at Colliders and Beyond. 2018. arXiv:1810.05648.

  • Charanjit K. Khosa, Sabine Kraml, Andre Lessa, Philipp Neuhuber, and Wolfgang Waltenberger. SModelS database update v1.2.3. LHEP, 158:2020, 5 2020. arXiv:2005.00555, doi:10.31526/lhep.2020.158.

  • Jeffrey Krupa and others. GPU coprocessors as a service for deep learning inference in high energy physics. 7 2020. arXiv:2007.10359.

  • ATLAS Collaboration. Reproducing searches for new physics with the ATLAS experiment through publication of full statistical likelihoods. Geneva, Aug 2019. URL: https://cds.cern.ch/record/2684863.

  • ATLAS Collaboration. Search for new phenomena in events with two opposite-charge leptons, jets and missing transverse momentum in \(pp\) collisions at \(\sqrt s = 13\,\text TeV\) with the ATLAS detector. ATLAS-CONF-2020-046, 2020. URL: https://cds.cern.ch/record/2728056.

Published Likelihoods

Updating list of HEPData entries for publications using HistFactory JSON likelihoods: