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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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Lenguaje: | eng |
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2021
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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. |
id | cern-2765038 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2021 |
record_format | invenio |
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 |