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About

This Python program contains a simple analysis and comparison of multiple statistical weighting methods, including inPlot/sPlot1 and Q-Factors2. It is intended to show the need for a correction in the Q-Factors method, which occasionally fails because it does not use the proper event weighting scheme.

Usage

  1. Clone the repository: git clone git@github.com:denehoffman/qfactors_splot.git
  2. Install the required libraries: pip install -r requirements.txt
  3. Run the analysis script: python analysis.py
  4. Profit?

SLURM Usage

  1. Modify 'run_analysis.sh'
  2. Execute the SLURM submission script: ./submit_jobs.sh

Disclaimer

This analysis is part of an ongoing project which will eventually be published, please don't scoop me, I'll know it and raise hell :)

References

Footnotes

  1. M. Pivk and F.R. Le Diberder. “sPlot: A statistical tool to unfold data distributions”. In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equip- ment 555 (1-2 Dec. 2005), pp. 356–369. issn: 01689002. doi: 10.1016/j. nima.2005.08.106. arXiv:physics/0402083 ↩

  2. M Williams, M Bellis, and C A Meyer. “Multivariate side-band subtraction using probabilistic event weights”. In: Journal of Instrumentation 4 (10 Oct. 2009), P10003–P10003. issn: 1748-0221. doi: 10.1088/1748- 0221/ 4/10/P10003. arXiv:0809.2548 ↩