Unfolding algorithms and tests using RooUnfold

TL;DR

The paper introduces RooUnfold, a software package that offers a unified framework for applying, evaluating, and comparing various unfolding algorithms in data analysis, with tools for covariance estimation and multi-dimensional unfolding.

Contribution

It presents RooUnfold as a comprehensive toolkit for unfolding algorithms, including implementation details, evaluation tools, and practical usage experience.

Findings

RooUnfold supports multiple unfolding algorithms including Bayesian, SVD, and TUnfold.

The package provides tools for covariance matrix evaluation and multi-dimensional unfolding.

Performance comparisons of algorithms under different models are demonstrated.

Abstract

The RooUnfold package provides a common framework to evaluate and use different unfolding algorithms, side-by-side. It currently provides implementations or interfaces for the Iterative Bayes, Singular Value Decomposition, and TUnfold methods, as well as bin-by-bin and matrix inversion reference methods. Common tools provide covariance matrix evaluation and multi-dimensional unfolding. A test suite allows comparisons of the performance of the algorithms under different truth and measurement models. Here I outline the package, the unfolding methods, and some experience of their use.