Nov 4 – 8, 2019
Adelaide Convention Centre
Australia/Adelaide timezone

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

Nov 5, 2019, 3:30 PM
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.

Consider for promotion Yes

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