Estimations of trigger efficiencies are essential to modern particle physics analyses. A data-driven method provides a framework in which to estimate these efficiencies from the properties of reconstructed candidates, described in this paper. This paper also presents the design, implementation and performance of a software package, TriggerCalib, which provides a first centralised implementation of these calculations and can be seamlessly employed in physics analyses. Additionally, the estimation of statistical and systematic uncertainties is discussed.
@article{arxiv.2505.15951,
title = {A framework and implementation for data-driven trigger efficiency estimation at LHCb},
author = {Johannes Albrecht and James Andrew Gooding and Maxim Lysenko and Abhijit Mathad and Alessandro Scarabotto and Tomasz Skwarnicki},
journal= {arXiv preprint arXiv:2505.15951},
year = {2026}
}
Comments
12 pages, 5 figures. As submitted to European Physical Journal C, Reviewed by Francesco Dettori and Mika Vesterinen