Resource type
Thesis type
(Thesis) Ph.D.
Date created
2022-08-30
Authors/Contributors
Author (aut): Jäger, Benjamin
Abstract
The Higgs boson is a unique tool in the search for the fundamental laws of nature, as it is connected to many of the open fundamental questions the Standard Model (SM) of particle physics cannot answer. Precision measurements of the properties of the Higgs boson, including its interactions with other fundamental particles, provide a powerful tool to test the predictions of the SM and possibly find deviations from them.
As part of a broad Higgs boson physics program at the Large Hadron Collider (LHC), this thesis presents cross-section measurements of Higgs boson production via gluon fusion (ggF) and vector-boson fusion (VBF) in decays to W bosons. The H -> WW* decay is the second most likely decay of the Higgs boson and, in the VBF production mode, the most sensitive channel to measure the coupling of the Higgs boson to vector bosons at the LHC. The measurement is based on pp collisions at a center-of-mass energy of \sqrt{s} = 13 TeV recorded by the ATLAS experiment at the LHC between 2015 and 2018, corresponding to an integrated luminosity of 139 / fb. The measurements of the inclusive ggF and VBF cross sections times branching fraction result in 12.0 +-1.4 pb and 0.75 +0.19 -0.16 pb, respectively. In addition, Higgs boson production is measured in 11 exclusive kinematic regions. All results are found to be consistent with their corresponding SM predictions. The H -> WW* analysis is also an important input to combined Higgs boson measurements, which provide some of the most precise measurements of Higgs boson interactions to date and are briefly summarized in this work.
The measurement of the VBF, H -> WW* process is drastically improved over previous results by the implementation of a binary classifier based on a deep neural network (DNN) that distinguishes the VBF, H -> WW* signal from other physical processes. The development and optimization of the DNN are presented in this thesis. This thesis also presents the measurement of the jet energy resolution, which is essential for many physics analyses performed with the ATLAS experiment, such as the H -> WW* analysis, due to the abundance of jets in pp collisions.
As part of a broad Higgs boson physics program at the Large Hadron Collider (LHC), this thesis presents cross-section measurements of Higgs boson production via gluon fusion (ggF) and vector-boson fusion (VBF) in decays to W bosons. The H -> WW* decay is the second most likely decay of the Higgs boson and, in the VBF production mode, the most sensitive channel to measure the coupling of the Higgs boson to vector bosons at the LHC. The measurement is based on pp collisions at a center-of-mass energy of \sqrt{s} = 13 TeV recorded by the ATLAS experiment at the LHC between 2015 and 2018, corresponding to an integrated luminosity of 139 / fb. The measurements of the inclusive ggF and VBF cross sections times branching fraction result in 12.0 +-1.4 pb and 0.75 +0.19 -0.16 pb, respectively. In addition, Higgs boson production is measured in 11 exclusive kinematic regions. All results are found to be consistent with their corresponding SM predictions. The H -> WW* analysis is also an important input to combined Higgs boson measurements, which provide some of the most precise measurements of Higgs boson interactions to date and are briefly summarized in this work.
The measurement of the VBF, H -> WW* process is drastically improved over previous results by the implementation of a binary classifier based on a deep neural network (DNN) that distinguishes the VBF, H -> WW* signal from other physical processes. The development and optimization of the DNN are presented in this thesis. This thesis also presents the measurement of the jet energy resolution, which is essential for many physics analyses performed with the ATLAS experiment, such as the H -> WW* analysis, due to the abundance of jets in pp collisions.
Document
Extent
233 pages.
Identifier
etd22156
Copyright statement
Copyright is held by the author(s).
Supervisor or Senior Supervisor
Thesis advisor (ths): Stelzer, Bernd
Language
English
Member of collection
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