Dark Matter
: Signatures and Future Detection

Student thesis: Doctoral ThesisDoctor of Philosophy


Signatures of dark matter can be manifold. In the framework of weakly interacting massive particles they can come from annihilations in dark matter rich regions, from collisions of dark matter particles in terrestrial direct search experiments or from production of dark matter at particle accelerators. This thesis focuses on the latter two possibilities.
In the context of collider signatures, we discuss how deviations from background expectations can be interpreted in dark matter models. We look at two examples.
First, we see how anomalies in searches for Supersymmetry point towards
specic mass spectra in the Minimal Supersymmetric Standard Model (MSSM) at
the example of a slight dilepton excess observed by CMS. These spectra are then
constrained further by taking complementary analyses into account via a recasting of their limits. This recasting is necessary, because limits on the MSSM spectrum are strongly model dependent. Second, we investigate how deviations in the Higgs to diphoton decay rate can be explained by new vector-like leptons. As we will show, this model not only provides a valid dark matter candidate, but simultaneously leads to a strong rst order electroweak phase transition that is necessary for the generation of the observed baryon asymmetry in electroweak baryogenesis scenarios.
Future direct dark matter experiments will be challenged by an irreducible background coming from coherent neutrino-nucleus elastic scattering events that mimic dark matter collisions. This creates a lower limit on accessible dark matter-nucleon cross sections. We show that information coming from the direction of the recoiling nucleus can serve as a strong discriminator between neutrino and dark matter events such that this neutrino bound can be avoided. Necessary exposures of directional searches to surpass this limit are computed.
Date of Award2016
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorJohn Ellis (Supervisor) & Malcolm Fairbairn (Supervisor)

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