Speaker
Giordon Holtsberg Stark
(University of California,Santa Cruz (US))
Description
The HistFactory p.d.f. template $\href{https://cds.cern.ch/record/1456844}{\text{[CERN-OPEN-2012-016]}}$ is per-se independent of its implementation in ROOT and it is useful to be able to run statistical analysis outside of the ROOT, RooFit, RooStats framework. pyhf is a pure-python implementation of that statistical model for multi-bin histogram-based analysis and its interval estimation is based on the asymptotic formulas of "Asymptotic formulae for likelihood-based tests of new physics" $\href{https://arxiv.org/abs/1007.1727}{\text{[arxiv:1007.1727]}}$. pyhf supports modern computational graph libraries such as TensorFlow and PyTorch in order to make use of features such as auto-differentiation and GPU acceleration.
Authors
Giordon Holtsberg Stark
(University of California,Santa Cruz (US))
Matthew Feickert
(Southern Methodist University (US))
Lukas Alexander Heinrich
(CERN)
