4-8 November 2019
Adelaide Convention Centre
Australia/Adelaide timezone

pyhf: a pure Python implementation of HistFactory with tensors and autograd

5 Nov 2019, 15:30
Hall F (Adelaide Convention Centre)

Hall F

Adelaide Convention Centre

Poster Track 6 – Physics Analysis Posters


Matthew Feickert (Southern Methodist University (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.

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Primary authors

Lukas Alexander Heinrich (CERN) Matthew Feickert (Southern Methodist University (US)) Giordon Holtsberg Stark (University of California,Santa Cruz (US)) Kyle Stuart Cranmer (New York University (US))

Presentation Materials