A Comprehensive Search for Leptoquarks Decaying into Top-$\tau$ Final States at the Future LHC

TL;DR

This study explores the potential to detect third-generation scalar leptoquarks decaying into top quarks and tau leptons at the future 14 TeV LHC, using advanced machine learning techniques to improve sensitivity beyond current limits.

Contribution

It introduces machine learning-based tagging and classification methods for identifying leptoquark decay signatures at the LHC, enhancing detection sensitivity for higher mass ranges.

Findings

Significant sensitivity improvements for leptoquark detection at masses beyond current limits.

Expected 95% CL upper limits on production cross-section at 200 and 500 fb⁻¹.

Demonstrated effectiveness of ML techniques in collider phenomenology.

Abstract

We studied the collider phenomenology of third-generation scalar leptoquarks at the Large Hadron Collider (LHC) with a 14 TeV center-of-mass energy. The analysis focuses on leptoquarks decaying exclusively into top quarks and tau leptons, employing machine learning-based tagging techniques for identifying hadronically decaying boosted top quarks, W/Z, and Higgs bosons, as well as a multivariate classifier to distinguish signal events from Standard Model (SM) backgrounds. The expected 95% confidence level (CL) upper limits on the leptoquark production cross-section are computed assuming integrated luminosities of 200 and 500 inverse femtobarns at the 14 TeV LHC. The results demonstrate significant sensitivity improvements for detecting leptoquarks at masses beyond the current experimental limits.