Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC

TL;DR

This paper discusses data-driven methods used by the ATLAS experiment at CERN to estimate fake and non-prompt lepton backgrounds, which are crucial for accurate measurements and searches involving leptons.

Contribution

It introduces three data-driven techniques for estimating fake/non-prompt lepton backgrounds and evaluates their implementation and performance within the ATLAS experiment.

Findings

Three methods for background estimation are described.

The methods are implemented and tested in ATLAS analyses.

Performance assessments demonstrate their effectiveness.

Abstract

Measurements and searches performed with the ATLAS detector at the CERN Large Hadron Collider often involve signatures with one or more prompt leptons. Such analyses are subject to `fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.