12–23 Aug 2019
SLAC
America/Los_Angeles timezone

zfit: scalable pythonic fitting

Not scheduled
20m
51/1-102 - Kavli Auditorium (SLAC)

51/1-102 - Kavli Auditorium

SLAC

150

Speaker

Jonas Eschle

Description

Statistical modelling is a key element for HEP analysis. Currently, most of this modelling is performed with the ROOT/RooFit toolkit which is written in C++ and poorly integrated with the scientific Python ecosystem. zfit is a new alternative to RooFit, written in pure Python while still allowing to use HEP standard minimizers and file formats. 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.

Primary author

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