Nov 2 – 6, 2020
IP2I, Lyon
Europe/Zurich timezone

pyhf: pure-Python implementation of HistFactory with tensors and automatic differentiation

Not scheduled
IP2I, Lyon

IP2I, Lyon

Institut de Physique des 2 Infinis (IP2I) Lyon, France
Higgs and colliders Collider


Matthew Feickert (Univ. Illinois at Urbana Champaign (US))


The HistFactory p.d.f. template [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" [arXiv:1007.1727]. pyhf supports modern computational graph libraries such as TensorFlow and PyTorch in order to make use of features such as autodifferentiation and GPU acceleration.

Primary authors

Matthew Feickert (Univ. Illinois at Urbana Champaign (US)) Dr Giordon Holtsberg Stark (University of California,Santa Cruz (US)) Lukas Alexander Heinrich (CERN)

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