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Hunting for supersymmetry and dark matter at the electroweak scale
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Macaluso, Sebastian. Hunting for supersymmetry and dark matter at the electroweak scale. Retrieved from https://doi.org/doi:10.7282/t3-q8f3-rp83

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TitleHunting for supersymmetry and dark matter at the electroweak scale
NameMacaluso, Sebastian (author); Shih, David (chair); Halkiadakis, Eva (internal member); Thomas, Scott (internal member); Andrei, Natan (internal member); Reece, Matthew (outside member); Rutgers University; School of Graduate Studies
Date Created2018
Other Date2018-10 (degree)
SubjectPhysics and Astronomy, Supersymmetry, Dark matter (Astronomy), Electroweak interactions
Extent1 online resource (173 pages) : illustrations
DescriptionIn this thesis, we study models of physics beyond the Standard Model (SM) at the electroweak scale and their phenomenology, motivated by naturalness and the nature of dark matter. Moreover, we introduce analyses and techniques relevant in searches at the Large Hadron Collider (LHC). We start by applying computer vision with deep learning to build a boosted top jets tagger at the LHC that outperforms previous state-of-the-art classifiers by a factor of ~2-3 or more in background rejection, over a wide range of tagging efficiencies. Next, we define a cut and count based analysis for supersymmetric top quarks at LHC Run II capable of probing the line in the mass plane where there is just enough phase space to produce an on-shell top quark from the stop decay. We also implement a comprehensive reinterpretation of the 13 TeV ATLAS and CMS searches with the first ~15/fb of data and derive constraints on various simplified models of natural supersymmetry. We discuss how these constraints affect the fine-tuning of the electroweak scale. Finally, we show how a simple extension of the minimal supersymmetric SM, consisting of a dark sector, can explain the dark matter relic abundance and the Higgs mass in a natural way.
NotePh.D.
NoteIncludes bibliographical references
Noteby Sebastian Macaluso
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-q8f3-rp83
Languageeng
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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