Performance of jet substructure techniques for large-R jets in proton-proton collisions at sqrt(s) = 7 TeV using the ATLAS detector

TL;DR

This study evaluates jet substructure techniques, including grooming algorithms, for large-R jets in high-energy proton-proton collisions, demonstrating improved stability and discrimination power for identifying boosted heavy particles.

Contribution

It provides a comprehensive analysis of jet grooming methods' performance in high-luminosity conditions using the full 2011 ATLAS dataset.

Findings

Groomed jets show reduced sensitivity to pile-up effects.

Jet substructure observables enhance discrimination of boosted objects.

Algorithms improve tagging efficiency for W, Z, and top-quark jets.

Abstract

This paper presents the application of a variety of techniques to study jet substructure. The performance of various modified jet algorithms, or jet grooming techniques, for several jet types and event topologies is investigated for jets with transverse momentum larger than 300 GeV. Properties of jets subjected to the mass-drop filtering, trimming, and pruning algorithms are found to have reduced sensitivity to multiple proton-proton interactions, are more stable at high luminosity and improve the physics potential of searches for heavy boosted objects. Studies of the expected discrimination power of jet mass and jet substructure observables in searches for new physics are also presented. Event samples enriched in boosted W and Z bosons and top-quark pairs are used to study both the individual jet invariant mass scales and the efficacy of algorithms to tag boosted hadronic objects. The analyses presented use the full 2011 ATLAS dataset, corresponding to an integrated luminosity of 4.7 +/- 0.1 /fb from proton-proton collisions produced by the Large Hadron Collider at a center-of-mass energy of sqrt(s) = 7 TeV.