Imagiro: an implementation of Bayesian iterative unfolding for high energy physics

TL;DR

Imagiro is a software package that implements Bayesian iterative unfolding to correct collider event measurements, featuring automated parameter optimization, error estimation, and user-friendly data handling for high energy physics analysis.

Contribution

It introduces a new software tool that simplifies Bayesian unfolding with automated features and error estimation, tailored for high energy physics applications.

Findings

Provides systematic and statistical error estimation.

Automates parameter selection and self-testing.

Facilitates data analysis with ROOT format support.

Abstract

Unfolding of reconstructed event properties to identify the true features of collider events is a complementary method to the established practice of detector calibration, and is particularly relevant to large, composite particle detectors such as those at the Large Hadron Collider. The behaviour of the detector is simulated and used to create a mapping between the true properties of events and their reconstructed equivalents. Unfolding attempts to invert this mapping for use in correcting measurements. Imagiro is a new software package providing Bayesian iterative unfolding with systematic and statistical error estimation. The software is designed to simplify the user experience with automatic self-testing and the calculation of optimal parameters. Methods are provided for loading data and producing plotted results in the widely used ROOT format.