Published September 21, 2020 | Version v1

Searches for new phenomena in inclusive and tagged dijet distributions at $\sqrt{s}$ = l3 TeV

Authors/Creators

  • 1. Lund U
  • 1. Lund U

Description

Dijets are produced in abundance at the Large Hadron Collider as predicted by quantum chromodynamics (QCD). However, several theories beyond the Standard Model of Particle Physics predicts new phenomena, which also result in dijet final states. This thesis presents searches for such new phenomena using different techniques. One approach is to look for jets, that originate from top quarks. We know, that the top quark, being the heaviest fundamental particle, has a large coupling to the Higgs field. Therefore, it is appealing to think, that the top quark could play a special role in understanding the fine tuning problem of the Higgs mass. One model of interest is the topcolor assisted technicolor, which predicts a $Z\prime_{TC2}$ boson, that would appear as a resonance in the invariant mass spectrum. Limits are set on this theory by using the $139 fb^{−1}$ of data collected at √s = 13 TeV by ATLAS. Another approach is to have a more inclusive selection and not only look at the invariant mass spectrum, but also the angular distribution of the two jets. This makes it possible to look for non­-resonant signals like those coming from a contact interaction with a compositeness scale, "$\Lambda$", which is much higher than the center ­of ­mass energy at the Large Hadron Collider. Limits are set on this theory by using $37 fb^{−1}$ of data. Studies, conducted to improve this analysis, are also presented. A prerequisite to perform these searches is to have well ­calibrated jets. Different methods are used to calibrate the jets at different transverse momentum, $p_{T}$, ranges. In order to calibrate high-$p_{T}$ jets, the calorimeter response to the single particles, that make up the jet, is studied. In this way it is possible to estimate the uncertainty on the jet energy scale at the highest $p_{T}$, where there are very few events in data.

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CERN-THESIS-2020-124.pdf

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Additional details

Identifiers

CDS
2734072
CDS Report Number
CERN-THESIS-2020-124

Related works

Is version of
Book: 978-91-7895-616-6 (ISBN)
Book: 978-91-7895-617-3 (ISBN)

CERN

Department
PH - Physics Department
Programme
No program participation
Accelerator
CERN LHC
Experiment
ATLAS
Studies
Not applicable

Linked records