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

M Aaboud1, G Aad2, B Abbott3

  • 1Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda, Morocco.

The European Physical Journal. C, Particles and Fields
|September 26, 2017
PubMed
Summary
This summary is machine-generated.

A new particle flow algorithm improves jet reconstruction accuracy in high-energy physics by combining inner tracker momentum measurements for charged hadrons with calorimeter energy measurements for neutral particles. This method enhances resolution and stability in ATLAS data from the Large Hadron Collider.

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Area of Science:

  • High Energy Physics
  • Particle Physics
  • Collider Physics

Background:

  • Jet reconstruction is crucial for analyzing particle collisions.
  • Traditional methods using only calorimeter data have limitations in accuracy.
  • Charged hadrons and neutral particles require different measurement techniques.

Purpose of the Study:

  • To implement and evaluate a particle flow algorithm for jet reconstruction.
  • To improve the accuracy of jet measurements by integrating inner tracker and calorimeter data.
  • To minimize signal overlap between tracking and calorimetry.

Main Methods:

  • Applied a particle flow algorithm to 20.2 fb⁻¹ of ATLAS data from 8 TeV proton-proton collisions.
  • Used inner tracker momentum measurements for charged hadrons.
  • Retained calorimeter measurements for neutral particle energies.
  • Developed strategies to minimize double-counting of charged hadron signals.

Main Results:

  • Particle flow jets demonstrated improved resolution compared to calorimeter-only jets.
  • Enhanced stability against pile-up effects was observed.
  • The algorithm successfully integrated data from the inner tracker and calorimeter.

Conclusions:

  • The particle flow algorithm offers significant improvements for jet reconstruction in proton-proton collisions.
  • This approach enhances the precision of measurements in high-energy physics experiments.
  • The method is robust and provides better performance in complex collision environments.