Introduction

  • Uncertainties are always divided into statistical and systematic components
  • Many precision measurements also divide out luminosity and/or theory uncertainties

Uncertainty sources

  • Data in CMS plots carry error bars that serve as a “best estimate” of the variance of the Poisson distribution that governs the expected observations for each observable.
  • Systematic uncertainties are assumed to follow Gaussian or log-normal probability distributions.
  • Collision-based uncertainties come from the luminosity and pileup calculations.
  • Detector-based uncertainties come from corrections to the energy response for different physics objects.
  • Scale factor-based uncertainties come from the calculation methods used to measure efficiencies for various reconstruction, identification, isolation, and trigger algorithms.
  • Analysis methods also bring in uncertainties that need to be determined by the analysis team.

Physics object corrections

  • The available 2016 corrections and a summary website can be accessed from the Open Data Portal (a “record” page for the corrections is forthcoming).
  • Mandatory corrections such as pileup and jet energy corrections are provided.
  • Scale factors for many reconstruction and identification algorithms are also provided.
  • The summary webpage is the best reference to understand the names, inputs, and outputs of the corrections.

Uncertainties challenge

  • The correctionlib software provides a method to open and read corrections in the common JSON format.
  • The evaluate method takes in a correction’s required inputs and returns a correction value.
  • For event-weight corrections, save shifted event weight arrays to create shifted histograms.
  • ROOT histograms can be created simply from arrays of data and weights for statistical analysis.