Publication: zfit: Scalable pythonic fitting
zfit: Scalable pythonic fitting
Date
Date
Date
Citations
Eschle, J., Puig Navarro, A., Silva Coutinho, R., & Serra, N. (2020). zfit: Scalable pythonic fitting. SoftwareX, 11, 100508. https://doi.org/10.1016/j.softx.2020.100508
Abstract
Abstract
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 TensorF
Metrics
Downloads
Views
Additional indexing
Creators (Authors)
- Eschle, Jonas
- Silva Coutinho, Rafael
- Serra, Nicola
Volume
Volume
Volume
Page range/Item number
Page range/Item number
Page range/Item number
Item Type
Item Type
Item Type
In collections
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
OA Status
OA Status
OA Status
Free Access at
Free Access at
Free Access at
Publisher DOI
Metrics
Downloads
Views
Citations
Eschle, J., Puig Navarro, A., Silva Coutinho, R., & Serra, N. (2020). zfit: Scalable pythonic fitting. SoftwareX, 11, 100508. https://doi.org/10.1016/j.softx.2020.100508
