Improving sensitivity of vectorlike top partner searches with jet substructure

TL;DR

This paper enhances the detection of vectorlike top partners by employing advanced jet substructure techniques and comparing fixed versus dynamic jet clustering methods to improve sensitivity in boosted events.

Contribution

It introduces a novel analysis using jet substructure with fixed and dynamic radius clustering to improve sensitivity for vectorlike top partner searches.

Findings

Dynamic radius clustering improves signal sensitivity over fixed radius.

Jet substructure techniques effectively distinguish signal from background.

Multivariate analysis enhances detection significance.

Abstract

Vectorlike quark partners appear in many BSM models and remain an important area of research, as they can offer insights into the electroweak symmetry breaking mechanism. In this work, we have focused on studying the production of a heavy vectorlike top partner in association with a SM top quark via chromomagnetic coupling and the four decay modes of the top partner, namely, $bW$, $tZ$, $th$, and $tg$. The signal has been studied in final states with one fat jet, at least one $b$-tagged jet, one lepton, and missing energy. This study focuses on the extensive use of jet substructure techniques in jets clustered with fixed and dynamically varying radius to deal with events containing differently sized jets. Important kinematic information, along with jet substructure and event shape observables, has been used in a multivariate analysis to extract signal with high significance. A comparative study between fixed and dynamically varying radius clustering of jets is also presented, leading to an improvement in signal sensitivity in the highly boosted scenario.