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PyUnfold: A Python Package for Iterative Unfolding

Data Analysis, Statistics and Probability 2018-06-12 v1 Instrumentation and Methods for Astrophysics High Energy Physics - Experiment

Abstract

PyUnfold is a Python package for incorporating imperfections of the measurement process into a data analysis pipeline. In an ideal world, we would have access to the perfect detector: an apparatus that makes no error in measuring a desired quantity. However, in real life, detectors have finite resolutions, characteristic biases that cannot be eliminated, less than full detection efficiencies, and statistical and systematic uncertainties. By building a matrix that encodes a detector's smearing of the desired true quantity into the measured observable(s), a deconvolution can be performed that provides an estimate of the true variable. This deconvolution process is known as unfolding. The unfolding method implemented in PyUnfold accomplishes this deconvolution via an iterative procedure, providing results based on physical expectations of the desired quantity. Furthermore, tedious book-keeping for both statistical and systematic errors produces precise final uncertainty estimates.

Keywords

Cite

@article{arxiv.1806.03350,
  title  = {PyUnfold: A Python Package for Iterative Unfolding},
  author = {James Bourbeau and Zigfried Hampel-Arias},
  journal= {arXiv preprint arXiv:1806.03350},
  year   = {2018}
}

Comments

17 pages

R2 v1 2026-06-23T02:24:10.399Z