# Jet reconstruction and performance using particle flow with the ATLAS Detector

## TL;DR

This paper presents the implementation and evaluation of a particle flow algorithm in the ATLAS detector, showing improved jet resolution and pile-up stability by combining tracker and calorimeter data from 8 TeV proton-proton collisions.

## Contribution

The paper introduces a particle flow algorithm for ATLAS that enhances jet reconstruction by integrating tracker and calorimeter data, reducing double-counting and improving performance.

## Key findings

- Improved jet resolution with particle flow algorithm.
- Enhanced pile-up stability of reconstructed jets.
- Demonstrated benefits using 8 TeV collision data.

## Abstract

This paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb$^{-1}$ of ATLAS data from 8 TeV proton-proton collisions in Run 1 of the LHC. The algorithm removes calorimeter energy deposits due to charged hadrons from consideration during jet reconstruction, instead using measurements of their momenta from the inner tracker. This improves the accuracy of the charged-hadron measurement, while retaining the calorimeter measurements of neutral-particle energies. The paper places emphasis on how this is achieved, while minimising double-counting of charged-hadron signals between the inner tracker and calorimeter. The performance of particle flow jets, formed from the ensemble of signals from the calorimeter and the inner tracker, is compared to that of jets reconstructed from calorimeter energy deposits alone, demonstrating improvements in resolution and pile-up stability.