Optimisation of large-radius jet reconstruction for the ATLAS detector in 13 TeV proton-proton collisions

TL;DR

This paper presents an optimized large-radius jet reconstruction method for the ATLAS detector at the LHC, improving performance in identifying high-energy hadronic decays and pile-up stability using new inputs and a novel 'unified flow object' approach.

Contribution

The paper introduces a comprehensive optimization of large-radius jet reconstruction, including a new 'unified flow object' input, enhancing ATLAS's ability to analyze high-energy particle decays.

Findings

Improved jet definitions outperform the current ATLAS baseline.

The 'unified flow object' enhances performance across kinematic ranges.

Optimized jets show better pile-up stability and decay identification.

Abstract

Jet substructure has provided new opportunities for searches and measurements at the LHC, and has seen continuous development since the optimization of the large-radius jet definition used by ATLAS was performed during Run 1. A range of new inputs to jet reconstruction, pile-up mitigation techniques and jet grooming algorithms motivate an optimisation of large-radius jet reconstruction for ATLAS. In this paper, this optimisation procedure is presented, and the performance of a wide range of large-radius jet definitions is compared. The relative performance of these jet definitions is assessed using metrics such as their pileup stability, ability to identify hadronically decaying $W$ bosons and top quarks with large transverse momenta. A new type of jet input object, called a 'unified flow object' is introduced which combines calorimeter- and inner-detector-based signals in order to achieve optimal performance across a wide kinematic range. Large-radius jet definitions are identified which significantly improve on the current ATLAS baseline definition, and their modelling is studied using $pp$ collisions recorded by the ATLAS detector at $\sqrt{s}=13$ TeV during 2017.