Acknowledgements

Citing popclass

If you use popclass in your work we request that you cite the following papers and repositories.

@article{Sallaberry2025,
    doi = {10.21105/joss.07769},
    url = {https://doi.org/10.21105/joss.07769},
    year = {2025},
    publisher = {The Open Journal},
    volume = {10}, number = {109},
    pages = {7769},
    author = {Greg Sallaberry and Zofia Kaczmarek and Peter McGill and Scott E. Perkins and William A. Dawson and Caitlin G. Begbie},
    title = {popclass: A Python Package for Classifying Microlensing Events}, journal = {Journal of Open Source Software}
}

@ARTICLE{2025ApJ...981..183K,
   author = {{Kaczmarek}, Zofia and {McGill}, Peter and {Perkins}, Scott E. and {Dawson}, William A. and {Huston}, Macy and {Ho}, Ming-Feng and {Abrams}, Natasha S. and {Lu}, Jessica R.},
    title = "{On Finding Black Holes in Photometric Microlensing Surveys}",
  journal = {\apj},
 keywords = {Gravitational microlensing, Black holes, Bayesian statistics, Classification, Sky surveys, 672, 162, 1900, 1907, 1464, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics},
     year = 2025,
    month = mar,
   volume = {981},
   number = {2},
      eid = {183},
    pages = {183},
      doi = {10.3847/1538-4357/adb1d7},
archivePrefix = {arXiv},
       eprint = {2410.14098},
primaryClass = {astro-ph.SR},
   adsurl = {https://ui.adsabs.harvard.edu/abs/2025ApJ...981..183K},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2024ApJ...961..179P,
    author = {{Perkins}, Scott E. and {McGill}, Peter and {Dawson}, William and {Abrams}, Natasha S. and {Lam}, Casey Y. and {Ho}, Ming-Feng and {Lu}, Jessica R. and {Bird}, Simeon and {Pruett}, Kerianne and {Golovich}, Nathan and {Chapline}, George},
    title = "{Disentangling the Black Hole Mass Spectrum with Photometric Microlensing Surveys}",
    journal = {\apj},
    keywords = {Gravitational microlensing, Microlensing parallax, Dark matter, Primordial black holes, Black holes, Astrophysical black holes, Bayesian statistics, Astrostatistics techniques, Astrostatistics tools, 672, 2144, 353, 1292, 162, 98, 1900, 1886, 1887, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies},
    year = 2024,
    month = feb,
    volume = {961},
    number = {2},
    eid = {179},
    pages = {179},
    doi = {10.3847/1538-4357/ad09bf},
    archivePrefix = {arXiv},
    eprint = {2310.03943},
    primaryClass = {astro-ph.IM},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2024ApJ...961..179P},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Contributors

The projects founding contributors (in reverse alphabetical order) are:

For a complete list current contributor see Github.

Funding

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory (LLNL) under Contract DE-AC52-07NA27344. The theoretical foundation of this work was established under support from Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development Program under project 22-ERD-037. The software implementation for this project was funded under the LLNL Space Science Institute’s Institutional Scientific Capability Portfolio funds in partnership with LLNL’s Academic Engagement Office.

Disclaimer

This work was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes.