zfit: scalable pythonic fitting
| Main Authors: | Rafael Silva Coutinho, Albert Puig Navarro, Jonas Eschle |
|---|---|
| Format: | info Proceeding eJournal |
| Terbitan: |
, 2019
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| Online Access: |
https://zenodo.org/record/3599416 |
Daftar Isi:
- Statistical modelling is a key element for High-Energy Physics (HEP) analysis. Currently, most of this modelling is performed with the ROOT/RooFit toolkit which is written in C++ and provides Python bindings which are only loosely integrated into the scientific Python ecosystem. We present zfit, a new alternative to RooFit, written in pure Python. Built on top of TensorFlow (a modern, high level computing library for massive computations), zfit provides a high level interface for advanced model building and fitting. It is also designed to be extendable in a very simple way, allowing the usage of cutting-edge developments from the scientific Python ecosystem in a transparent way. In this talk, the main features of zfit are introduced, and its extension to data analysis, especially in the context of HEP experiments, is discussed.