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@PHDTHESIS{Filatov:580449,
author = {Filatov, Oleg},
othercontributors = {Raspiareza, Alexei and Gallo-Voss, Elisabetta},
title = {{T}au identification algorithms and study of the {CP}
structure of the {Y}ukawa coupling between the {H}iggs boson
and tau leptons in {CMS}},
school = {Universität Hamburg},
type = {Dissertation},
address = {Hamburg},
publisher = {Verlag Deutsches Elektronen-Synchrotron DESY},
reportid = {PUBDB-2023-01292, DESY-THESIS-2023-005},
series = {DESY-THESIS},
pages = {191},
year = {2023},
note = {Dissertation, Universität Hamburg, 2023},
abstract = {The measurement of the CP properties of the Yukawa coupling
of the Higgs boson to τleptons is presented. The data set
used for the analysis is collected by the CMS experiment
atthe LHC during the Run 2 data-taking period in
proton-proton collisions at √s = 13 TeV andcorresponds to
an integrated luminosity of 137 fb$^{−1}$. The Yukawa
coupling between the Higgsboson and $τ$ leptons is
parametrised in terms of the effective mixing angle
α$^{Hττ}$, where the valueα$^{Hττ}$ = 0◦(90◦)
corresponds to the SM scenario of the pure CP-even (CP-odd)
H$ττ$ coupling.The angle between the decay planes of the
$τ$ leptons is used as the observable encoding the CP
nature of the Higgs boson. The measurement is performed in
the $τ$$_e$$τ$$_h$ channel where oneτ lepton decays into
an electron and the other hadronically. The results are
combined with themeasurement in the $τ$$_q$$τ$$_h$ and
$τ$$_h$$τ$$_h$ channels. The observed (expected) value of
the effectivemixing angle for the combination is measured to
be: α$^{Hττ}$ = −1 ± 19◦(0 ± 21◦) @68.3\% CL.The
results are compatible with the SM expectation and the pure
CP-odd hypothesis isrejected at the observed (expected)
significance level of 3.0 (2.6) standard deviations.The
improvements to the $τ$ lepton identification in CMS in the
context of the Run 3 preparationare described. Retraining
and optimisation of the DeepTau algorithm with the addition
ofthe adversarial fine-tuning procedure are performed. The
resulting model improves upon theprevious DeepTau model in
terms of the background rejection by 10-50\% and has a
betterdescription of data with simulation in the H →
$ττ$ selection region.A new algorithm called Tau
Transformer (TaT) is proposed to overcome the limitations of
theDeepTau architecture. The TaT core is based on
self-attention layers and features the embeddingmodule
allowing for the multimodality treatment of the input
representation. Comparison of theTaT model with the
retrained DeepTau model and a comparable ParticleNet-based
architectureshows consistently improved performance by up to
50\% in the misidentification rate across the $p\tiny{T}$,
$η$, and decay mode ranges of interest.},
cin = {CMS},
cid = {I:(DE-H253)CMS-20120731},
pnm = {611 - Fundamental Particles and Forces (POF4-611) / PHGS,
VH-GS-500 - PIER Helmholtz Graduate School
$(2015_IFV-VH-GS-500)$},
pid = {G:(DE-HGF)POF4-611 / $G:(DE-HGF)2015_IFV-VH-GS-500$},
experiment = {EXP:(DE-H253)LHC-Exp-CMS-20150101},
typ = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
doi = {10.3204/PUBDB-2023-01292},
url = {https://bib-pubdb1.desy.de/record/580449},
}