Fermionic dark matter : from models to collider searches
ABSTRACT: In this thesis, we investigate from diverse point of views, the dark matter problem. First, we study the doublet-triplet fermion model, a simple extension of the Standard Model with an extra Z2 symmetry. In this extension, it is possible to have a dark matter candidate at the electroweak s...
- Autores:
-
Bentancur Rodríguez, Amalia
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2019
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/11143
- Acceso en línea:
- http://hdl.handle.net/10495/11143
- Palabra clave:
- Astrofísica
Astrophysics
Física
Physics
Física nuclear
Materia oscura
Colisionadores de hadrones
http://aims.fao.org/aos/agrovoc/c_5833
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 2.5 Colombia (CC BY-NC-ND 2.5 CO)
Summary: | ABSTRACT: In this thesis, we investigate from diverse point of views, the dark matter problem. First, we study the doublet-triplet fermion model, a simple extension of the Standard Model with an extra Z2 symmetry. In this extension, it is possible to have a dark matter candidate at the electroweak scale that evades current strong direct detection constraints. We also include a double-triplet scalar in order to generate neutrino masses at loop-level and to relax the tension on the fermion sector from the current Higgs diphoton decay measurement. In the second part, we again consider the doublet-triplet fermion model but this time under a non-standard cosmology and multi-component dark sectors scenarios. We study restrictions on the model from collider searches, direct detection, and indirect detection experiments. In the third part of this work, we study the case of dark matter production at the LHC as the end product of a short cascade event and we study how to constrain it. We use the Matrix Element Method in order to show that even with very little information, it is possible to obtain the value of the most relevant parameters of the event. |
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