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zfit: Scalable pythonic fitting


Eschle, Jonas; Puig Navarro, Albert; Silva Coutinho, Rafael; Serra, Nicola (2020). zfit: Scalable pythonic fitting. SoftwareX, 11:100508.

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. The main features of zfit are introduced, and its extension to data analysis, especially in the context of HEP experiments, is discussed.

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. The main features of zfit are introduced, and its extension to data analysis, especially in the context of HEP experiments, is discussed.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Physics Institute
Dewey Decimal Classification:530 Physics
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Computer Science Applications
Language:English
Date:1 January 2020
Deposited On:12 Aug 2020 14:54
Last Modified:15 Aug 2020 10:01
Publisher:Elsevier
ISSN:2352-7110
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.softx.2020.100508
Project Information:
  • : FunderSNSF
  • : Grant IDPZ00P2_174182
  • : Project TitleFlavour anomalies and matter-antimatter asymmetry in b-baryon decays
  • : FunderSNSF
  • : Grant IDPZ00P2_168169
  • : Project TitleProbing the Standard Model of particle physics with rare beauty decays
  • : FunderSNSF
  • : Grant ID200021_182622
  • : Project TitleFlavour: a portal to discover new physics

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