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zfit

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 07 Nov 2024Publisher:Zenodo
Authors: Eschle, Jonas; Navarro, Albert Puig; Coutinho, Rafael Silva; Serra, Nicola; Marinangeli, Matthieu; Iason Krommydas;
Code repository: https://github.com/zfit/zfit/tree/0.27.1

doi: 10.5281/zenodo.2602042 , 10.5281/zenodo.15890273 , 10.5281/zenodo.14324288 , 10.5281/zenodo.14048358 , 10.5281/zenodo.14606570 , 10.5281/zenodo.15025342 , 10.5281/zenodo.17643229 , 10.5281/zenodo.14371320 , 10.5281/zenodo.14399022 , 10.5281/zenodo.15858601 , 10.5281/zenodo.15576285

Abstract

Statistical modeling is a key element in many scientific fields and especially in High-Energy Physics (HEP) analysis. The standard framework to perform this task in HEP is the C++ ROOT/RooFit toolkit; with Python bindings that are only loosely integrated into the scientific Python ecosystem. In this paper, zfit, a new alternative to RooFit written in pure Python, is presented. Most of all, zfit provides a well defined high-level API and workflow for advanced model building and fitting, together with an implementation on top of TensorFlow, allowing a transparent usage of CPUs and GPUs. It is designed to be extendable in a very simple fashion, allowing the usage of cutting-edge developments from the scientific Python ecosystem in a transparent way.

If you use this software, please cite it using the metadata from this file.

Keywords

likelihood, model fitting, HEP, statistical inference

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average