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dc.contributor.authorGamboa Goni., Rodrigo.
dc.date.accessioned2022-03-04T16:32:51Z
dc.date.available2022-03-04T16:32:51Z
dc.date.issued2020-09-17
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/77159
dc.descriptionPhD Theses.en_US
dc.description.abstractA search for non-resonant Higgs boson pair-production decaying to two bottom quarks and two taus (b b + 􀀀) using a Committee Machine is presented. The search uses 36.1 fb􀀀1 of data with a centre of mass energy of 13 TeV, recorded with the ATLAS detector at the LHC in 2015 and 2016. In addition, using a boosted decision tree, a statistical sensitivity study for the search of the Standard Model Higgs boson production in association with vector bosons (V h) decaying to the b b + 􀀀 nal state is presented, using the same ATLAS data sample. For both searches, a semi-leptonic nal state of the taus is considered. No signi cant excess above the expected background is observed in the data for the non-resonant Higgs boson pair-production decaying to the b b + 􀀀, constraining its cross-section times branching ratio to be less than 57.78 (101.30) fb for the expected (observed) categories, respectively corresponding to 23.67 (41.49) times the Standard Model expectation prediction at 95% con dence level. This is a stricter limit (for the expected value) in comparison with the non-Committee result. The Committee machine approach is 16.9% better than the published decision tree approach. For the statistical sensitivity study a median signi cance of 0.3 is found, which translates into a maximum increase in the expected statistical signi cance for the V h channel of 1.23% (0.5%) with respect to the 2-lepton (combined) individual reported values.en_US
dc.language.isoenen_US
dc.publisherQueen Mary University of London.en_US
dc.titleSearch for non-resonant di-Higgs production to the b b + 􀀀 nal state using a Committee Machine with the ATLAS detector at the LHC using pp collisions at p s = 13 TeV.en_US
dc.typeThesisen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US


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    Theses Awarded by Queen Mary University of London

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