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Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment

Since several decades, the predictions of the Standard Model (SM) of particle physics are being probed and validated. One major success of the Large Hadron Collider (LHC) at CERN was the discovery of the Higgs boson in 2012. With the increasing amount of proton-proton collisions recorded with the ex...

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Autor principal: Guth, Manuel
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2765038
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author Guth, Manuel
author_facet Guth, Manuel
author_sort Guth, Manuel
collection CERN
description Since several decades, the predictions of the Standard Model (SM) of particle physics are being probed and validated. One major success of the Large Hadron Collider (LHC) at CERN was the discovery of the Higgs boson in 2012. With the increasing amount of proton-proton collisions recorded with the experiments located at the LHC, precise Higgs measurements are now possible and rare processes are accessible. ATLAS and CMS recently discovered the production process of a Higgs boson in association with a pair of top quarks using LHC RUN II data. The $t\bar{t} H(H\rightarrow b\bar{b})$ process allows for a direct measurement of the Top-Yukawa coupling which is the strongest fermion-Higgs coupling in the Standard Model and plays therefore an important role in Higgs physics. The challenging final state with at least 4 $b$-jets requires an advanced analysis strategy as well as sophisticated $b$-jet identification methods. $b$-tagging is not only crucial in the $t\bar{t} H(b\bar{b})$ analysis, but most physics analyses within ATLAS are making use of it. The reoptimisation of the deep-learning-based heavy flavour tagger in ATLAS is shown in this thesis for two different jet collections. Various improvements were made resulting in a drastic performance increase up to a factor two in certain regions of the phase space. The $t\bar{t} H(b\bar{b})$ analysis is performed using $139\,fb^{-1}$ of RUN II ATLAS data at a centre-of-mass energy of $\sqrt{s}=13\,\text{TeV}$. The signal strength, being the ratio of the measured cross-section over the predicted cross-section in the SM, was measured to be $0.43^{+0.20}_{-0.19}(\text{stat.})^{+0.30}_{-0.27}(\text{syst.})$ with an observed (expected) significance of $1.3\;(3.0)$ standard deviations in the inclusive cross-section measurement. In addition, a simplified template cross-section (STXS) measurement in different Higgs $p_\text{T}$ bins is performed which is possible because of the ability to reconstruct the Higgs boson. The measurement is limited by the capability to describe the challenging irreducible $t\bar{t}+b\bar{b}$ background and by systematic uncertainties.
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spelling cern-27650382021-05-10T20:12:19Zhttp://cds.cern.ch/record/2765038engGuth, ManuelSearch for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS ExperimentParticle Physics - ExperimentSince several decades, the predictions of the Standard Model (SM) of particle physics are being probed and validated. One major success of the Large Hadron Collider (LHC) at CERN was the discovery of the Higgs boson in 2012. With the increasing amount of proton-proton collisions recorded with the experiments located at the LHC, precise Higgs measurements are now possible and rare processes are accessible. ATLAS and CMS recently discovered the production process of a Higgs boson in association with a pair of top quarks using LHC RUN II data. The $t\bar{t} H(H\rightarrow b\bar{b})$ process allows for a direct measurement of the Top-Yukawa coupling which is the strongest fermion-Higgs coupling in the Standard Model and plays therefore an important role in Higgs physics. The challenging final state with at least 4 $b$-jets requires an advanced analysis strategy as well as sophisticated $b$-jet identification methods. $b$-tagging is not only crucial in the $t\bar{t} H(b\bar{b})$ analysis, but most physics analyses within ATLAS are making use of it. The reoptimisation of the deep-learning-based heavy flavour tagger in ATLAS is shown in this thesis for two different jet collections. Various improvements were made resulting in a drastic performance increase up to a factor two in certain regions of the phase space. The $t\bar{t} H(b\bar{b})$ analysis is performed using $139\,fb^{-1}$ of RUN II ATLAS data at a centre-of-mass energy of $\sqrt{s}=13\,\text{TeV}$. The signal strength, being the ratio of the measured cross-section over the predicted cross-section in the SM, was measured to be $0.43^{+0.20}_{-0.19}(\text{stat.})^{+0.30}_{-0.27}(\text{syst.})$ with an observed (expected) significance of $1.3\;(3.0)$ standard deviations in the inclusive cross-section measurement. In addition, a simplified template cross-section (STXS) measurement in different Higgs $p_\text{T}$ bins is performed which is possible because of the ability to reconstruct the Higgs boson. The measurement is limited by the capability to describe the challenging irreducible $t\bar{t}+b\bar{b}$ background and by systematic uncertainties.CERN-THESIS-2021-035oai:cds.cern.ch:27650382021-04-23T21:40:39Z
spellingShingle Particle Physics - Experiment
Guth, Manuel
Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment
title Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment
title_full Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment
title_fullStr Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment
title_full_unstemmed Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment
title_short Search for $t\bar{t}H\;(H\rightarrow b\bar{b})$ Production in the Lepton + Jets Channel and Quark Flavour Tagging with Deep Learning at the ATLAS Experiment
title_sort search for $t\bar{t}h\;(h\rightarrow b\bar{b})$ production in the lepton + jets channel and quark flavour tagging with deep learning at the atlas experiment
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2765038
work_keys_str_mv AT guthmanuel searchfortbarthhrightarrowbbarbproductionintheleptonjetschannelandquarkflavourtaggingwithdeeplearningattheatlasexperiment