New approach for jet-shape identification of TeV-scale particles at the LHC

TL;DR

This paper introduces a novel jet-shape identification method using linear regression to improve detection of TeV-scale particles decaying into collimated jets at the LHC, aiming to distinguish signal from QCD background.

Contribution

The paper presents a new linear regression-based technique for jet-shape identification tailored for TeV-scale particle searches at the LHC, enhancing signal discrimination.

Findings

Method reduces QCD background in simulations

Effective for heavy particle decay reconstruction

Applicable to various cascade decay channels

Abstract

A new approach to jet-shape identification based on linear regression is discussed. It is designed for searches for new particles at the TeV scale decaying hadronically with strongly collimated jets. We illustrate the method using a Monte Carlo simulation for pp collisions at the LHC with the goal to reduce the contribution of QCD-induced events. We focus on a rather generic example X to ttbar to hadrons, with X being a heavy particle, but the approach is well suited for reconstruction of other decay channels characterized by a cascade decay of known states.