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Exploring selections across channels in Dark Matter searches with top quarks at the ATLAS experiment of the LHC
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics. (ATLAS)
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Current estimates put Dark Matter to 26% of the energy-matter content of the universe,

but very little is known about it other than its gravitational interactions. Eorts to learn

more about Dark Matter include searching for it at high energy particle colliders. The lack

of information about the nature of Dark Matter makes this a complicated task, and many

searches are performed in dierent channels, and considering dierent theoretical models. In

this thesis, I explore two such analyses, performed in the ATLAS collaboration using data

from the ATLAS detector at the Large Hadron Collider at CERN: the tW+MET (missing

transverse energy) nal state and the tt+MET nal state. I have made a generation-level

study of the overlap between the signal regions used, and come to the conclusion that there

is some. I have also compared the models used in these analyses, the 2HDM+a and the

simplied spin-0 pseudoscalar model. Given the simplications made in my study, however,

more sophisticated approaches should be used before anything conclusive can be said.

Place, publisher, year, edition, pages
2019.
Series
FYSAST ; FYSMAS1102
Keywords [en]
LHC, ATLAS, high energy physics, top quarks, dark matter
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-393949OAI: oai:DiVA.org:uu-393949DiVA, id: diva2:1355667
Educational program
Master Programme in Physics
Presentation
2019-09-04, Beurlingsrummet, Ångström, 11:44 (English)
Supervisors
Examiners
Available from: 2019-10-03 Created: 2019-09-30 Last updated: 2019-10-03Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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  • en-US
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  • nn-NB
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Output format
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