Analysis of counting data: Development of the SATLAS Python package

Published: 11 Oct 2017 | Version 1 | DOI: 10.17632/3hr8f5nkhb.1
Contributor(s):
  • W. Gins,
    W. Gins
    Instituut voor Kern- en Stralingsfysica
  • R. P. de Groote,
    R. P. de Groote
    Instituut voor Kern- en Stralingsfysica
  • M. L. Bissell,
    M. L. Bissell
    University of Manchester
  • C. Granados Buitrago,
    C. Granados Buitrago
    Instituut voor Kern- en Stralingsfysica
  • R. Ferrer,
    R. Ferrer
    Instituut voor Kern- en Stralingsfysica
  • K. M. Lynch,
    K. M. Lynch
    CERN
  • G. Neyens,
    G. Neyens
    Instituut voor Kern- en Stralingsfysica
  • S. Sels
    S. Sels
    Instituut voor Kern- en Stralingsfysica

Description of this data

For the analysis of low-statistics counting experiments, a traditional nonlinear least squares minimization routine may not always provide correct parameter and uncertainty estimates due to the assumptions inherent in the algorithm(s). In response to this, a user-friendly Python package (SATLAS) was written to provide an easy interface between the data and a variety of minimization algorithms which are suited for analysing low, as well as high, statistics data. The advantage of this package is that it allows the user to define their own model function and then compare different minimization routines to determine the optimal parameter values and their respective (correlated) errors. Experimental validation of the different approaches in the package is done through analysis of hyperfine structure data of 203Fr gathered by the CRIS experiment at ISOLDE, CERN.

Experiment data files

This data is associated with the following publication:

Analysis of counting data: Development of the SATLAS Python package

Published in: Computer Physics Communications

Latest version

  • Version 1

    2017-10-11

    Published: 2017-10-11

    DOI: 10.17632/3hr8f5nkhb.1

    Cite this dataset

    Gins, W.; de Groote, R. P.; Bissell, M. L.; Granados Buitrago, C.; Ferrer, R.; Lynch, K. M.; Neyens, G.; Sels, S. (2017), “Analysis of counting data: Development of the SATLAS Python package”, Mendeley Data, v1 http://dx.doi.org/10.17632/3hr8f5nkhb.1

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Categories

Computational Physics, Data Analysis

Licence

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The files associated with this dataset are licensed under a MIT License licence.

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