How to Improve Top Tagging

TL;DR

This paper presents enhancements to kinematic top tagging algorithms for LHC data, including optimized jet algorithms, combined pruning and filtering techniques, and the integration of bottom tagging, with evaluations across different regimes.

Contribution

It introduces specific improvements and tests for top tagging algorithms, focusing on jet algorithm choices, pruning/filtering combination, and bottom tagging integration.

Findings

Different jet algorithms suit different transverse momentum ranges.

Combining pruning and filtering significantly improves signal-to-background ratio.

Adding bottom tagging does not enhance the kinematic selection for HEPTopTagger.

Abstract

In time for the first tests on LHC data we introduce a set of improvements and tests of purely kinematic top tagging algorithms. First, we show how different jet algorithms can be used for different transverse momentum regimes. Combining pruning and filtering in the reconstruction can enhance the signal over background ratio significantly, while larger jet radii only give minor improvements. Finally, bottom tagging can be added to the top tagger, but at least for the HEPTopTagger does not improve the kinematic selection algorithm.