Comparison of unfolding methods using RooFitUnfold

TL;DR

This paper introduces RooFitUnfold, a software package that standardizes and compares various unfolding algorithms used in particle physics, evaluating their bias, variance, and coverage across multiple test cases.

Contribution

The paper presents RooFitUnfold, a unified framework for applying and comparing multiple unfolding methods with consistent evaluation metrics.

Findings

Richardson-Lucy performs well in low-noise scenarios.

Tikhonov regularization effectively balances bias and variance.

Gaussian Process method provides flexible modeling options.

Abstract

In this paper we describe RooFitUnfold, an extension of the RooFit statistical software package to treat unfolding problems, and which includes most of the unfolding methods that commonly used in particle physics. The package provides a common interface to these algorithms as well as common uniform methods to evaluate their performance in terms of bias, variance and coverage. In this paper we exploit this common interface of RooFitUnfold to compare the performance of unfolding with the Richardson-Lucy, Iterative Dynamically Stabilized, Tikhonov, Gaussian Process, Bin-by-bin and inversion methods on several example problems.