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Search for diboson resonance production at sqrt(s) = 8 TeV with the ATLAS detector

Marsden, Stephen Philip

[Thesis]. Manchester, UK: The University of Manchester; 2015.

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Abstract

A search for heavy exotic diboson resonances decaying to llqq final states is presented using pp collision data collected with the ATLAS detector at the Large Hadron Collider. The analysis uses a data sample corresponding to an integrated luminosity of 20.3 fb^-1 at sqrt(s) = 8 TeV collected between April and December 2012. No significant excess of data events over the predicted Standard Model background is observed and 95% confidence level upper limits are set on the product of the production cross-section and the branching ratio for spin-2 Kaluza-Klein gravitons predicted by the bulk Randall-Sundrum model and for Extended Gauge Model W’ bosons. These results are subsequently combined with limits obtained from searches using the lvll, lvqq, and qqqq final states, and new mass limits are set on both signal models.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Physics
Publication date:
Location:
Manchester, UK
Total pages:
145
Abstract:
A search for heavy exotic diboson resonances decaying to llqq final states is presented using pp collision data collected with the ATLAS detector at the Large Hadron Collider. The analysis uses a data sample corresponding to an integrated luminosity of 20.3 fb^-1 at sqrt(s) = 8 TeV collected between April and December 2012. No significant excess of data events over the predicted Standard Model background is observed and 95% confidence level upper limits are set on the product of the production cross-section and the branching ratio for spin-2 Kaluza-Klein gravitons predicted by the bulk Randall-Sundrum model and for Extended Gauge Model W’ bosons. These results are subsequently combined with limits obtained from searches using the lvll, lvqq, and qqqq final states, and new mass limits are set on both signal models.
Thesis main supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:280288
Created by:
Marsden, Stephen
Created:
27th November, 2015, 16:29:59
Last modified by:
Marsden, Stephen
Last modified:
9th September, 2016, 12:57:42

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