Higgs Boson decays into a pair of bottom quarks : observation with the ATLAS detector and machine learning applications / Cecilia Tosciri.
2021
QC793.5.B62
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Title
Higgs Boson decays into a pair of bottom quarks : observation with the ATLAS detector and machine learning applications / Cecilia Tosciri.
Author
ISBN
9783030879389 (electronic bk.)
3030879380 (electronic bk.)
3030879372
9783030879372
3030879380 (electronic bk.)
3030879372
9783030879372
Publication Details
Cham, Switzerland : Springer, 2021.
Language
English
Description
1 online resource
Item Number
10.1007/978-3-030-87938-9 doi
Call Number
QC793.5.B62
Dewey Decimal Classification
539.7/21
Summary
This thesis presents the analysis that led to the observation of the Standard Model (SM) Higgs boson decay into pairs of bottom quarks. The analysis, based on a multivariate strategy, exploits the production of a Higgs boson associated with a vector boson. The analysis was performed on a dataset corresponding to a luminosity of 79.8/fb collected by the ATLAS experiment during Run-2 at a centre-of-mass energy of 13 TeV. An excess of events over the expected background is observed in a combination with complementary Hbb searches. The analysis was extended to provide a finer interpretation of the signal measurement. The cross sections of the V H(H2!bb) process have been measured in exclusive regions of phase space and used to search for deviations from the SM with an effective field theory approach. The results are discussed in this book. A novel technique for the fast simulation of the ATLAS forward calorimeter response is also presented. The new technique is based on similarity search, a branch of machine learning that enables quick and efficient searches for vectors similar to each other.
Note
"Doctoral Thesis accepted by University of Oxford, Oxford, UK."
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Includes bibliographical references.
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Source of Description
Online resource; title from PDF title page (SpringerLink, viewed October 27, 2021).
Series
Springer theses, 2190-5061
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Table of Contents
Introduction
Theoretical Introduction
Machine Learning
The LHC and the ATLAS Detector
Physics Object Reconstruction.
Theoretical Introduction
Machine Learning
The LHC and the ATLAS Detector
Physics Object Reconstruction.