Identification of Parton Pairs in a Dijet Event and Investigation of Its Effects on Dijet Resonance Search

TL;DR

This study explores how distinguishing parton pairs in dijet events can enhance the search for new particles at the LHC, demonstrating that multivariate methods can significantly improve signal detection.

Contribution

The paper introduces a multivariate approach to identify parton pair types in dijet events on an event-by-event basis, improving resonance search sensitivity.

Findings

Multivariate approach filters out 80% of non-target parton pairs.

Over half of quark-quark or gluon-gluon pairs are retained.

Signal significance for gluon-gluon resonances improves up to 4 times.

Abstract

Being able to distinguish parton pair type in a dijet event could significantly improve the search for new particles that are predicted by the theories beyond the Standard Model at the Large Hadron Collider. To explore whether parton pair types manifesting themselves as a dijet event could be distinguished on an event-by-event basis, I performed a simulation based study considering observable jet variables. I found that using a multivariate approach can filter out about 80% of the other parton pairs while keeping more than half of the quark-quark or gluon-gluon parton pairs in an inclusive QCD dijet distribution. The effects of event-by-event parton pair tagging for dijet resonance searches were also investigated and I found that improvement on signal significance after applying parton pair tagging can reach up to 4 times for gluon-gluon resonances.