An Error Analysis Toolkit for Binned Counting Experiments
Abstract
We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.
Keywords
Cite
@article{arxiv.2103.08677,
title = {An Error Analysis Toolkit for Binned Counting Experiments},
author = {B. Messerly and R. Fine and A. Olivier and Z. Ahmad Dar and F. Akbar and M. V. Ascencio and A. Bashyal and L. Bellantoni and A. Bercellie and J. L. Bonilla and G. Caceres and T. Cai and M. F. Carneiro and G. A. Díaz and J. Felix and L. Fields and A. Filkins and A. Ghosh and S. Gilligan and R. Gran and H. Haider and D. A. Harris and S. Henry and S. Jena and D. Jena and J. Kleykamp and M. Kordosky and D. Last and A. Lozano and X. -G. Lu and K. S. McFarland and C. Nguyen and V. Paolone and G. N. Perdue and M. A. Ramírez and H. Ray and D. Ruterbories and H. Schellman and C. J. Solano Salinas and H. Su and E. Valencia and N. H Vaughan and B. Yaeggy and K. Yang and L. Zazueta},
journal= {arXiv preprint arXiv:2103.08677},
year = {2021}
}