What the new RooFit can do for your analysis
Stephan Hageboeck
TL;DR
The paper discusses recent improvements to RooFit, a toolkit for statistical modeling in particle physics, highlighting faster data processing, enhanced interfaces, and easier usability in C++ and Python.
Contribution
It introduces modernized features in RooFit, including speed enhancements and interface improvements, enabling more efficient and user-friendly data analysis.
Findings
Unbinned fits are several times faster.
RooFit now offers more standard-like interfaces.
Usability in C++ and Python has been improved.
Abstract
RooFit is a toolkit for statistical modelling and fitting, and together with RooStats it is used for measurements and statistical tests by most experiments in particle physics. Since one year, RooFit is being modernised. In this talk, improvements already released with ROOT will be discussed, such as faster data loading, vectorised computations and more standard-like interfaces. These allow for speeding up unbinned fits by several factors, and make RooFit easier to use from both C++ and Python.
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