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arXiv · 2211.15838

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

Matthew Feickert·Lukas Heinrich·Giordon Stark
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Abstract

The HistFactory p.d.f. template 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". pyhf supports modern computational graph libraries such as TensorFlow, PyTorch, and JAX in order to make use of features such as auto-differentiation and GPU acceleration. In addition, pyhf's JSON serialization specification for HistFactory models has been used to publish 23 full probability models from published ATLAS collaboration analyses to HEPData.

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Matthew Feickert, Lukas Heinrich, Giordon Stark. 2022-11-29. pyhf: pure-Python implementation of HistFactory with tensors and automatic differentiation. https://arxiv.org/abs/2211.15838

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