Astronomical and cosmological observations suggest that 80% of the matter content of the universe is made up of dark matter. However, except for its gravitational interactions with ordinary matter particles, there is no evidence of its interactions via other known forces. A variety of extensions to the Standard Model of particle physics predict the existence of a weakly interacting massive particle which can account for the existence of dark matter. Even though these hypothetical particles can explain the abundance of dark matter in the universe, previous searches showed no direct evidence of their existence. In this thesis, a search for dark matter production in proton-proton collisions at the Large Hadron Collider (LHC) at CERN is presented.
The observation of a new particle compatible with the Standard Model Higgs boson in 2012 by the ATLAS and CMS experiments at the LHC enabled new search channels for dark matter production at particle colliders. This thesis describes a search for dark matter produced in association with a Higgs boson decaying to a bottom quark and an anti-bottom quark (bb̅) with the ATLAS experiment. The search was conducted using proton-proton collision data gathered from 2015 and 2016 at a center-of-mass energy of 13 TeV at the LHC. The analysis is performed by selecting final states compatible with a Higgs boson decaying to a bb̅ pair recoiling against dark matter particles which are detected as large missing transverse energy. The observations show no significant deviation from Standard Model expectations without dark matter. The results are converted to limits on the parameter space of a Z'-2HDM signal model as well as limits on production cross sections of beyond the Standard Model processes with the same final state signature of a Higgs boson and large missing transverse energy, without any further assumptions.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/35746 |
| Date | 23 May 2019 |
| Creators | Yigitbasi, Efe |
| Contributors | Butler, John M |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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