Banca de DEFESA: VITOR PAULO CAMPISTA NUNES

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : VITOR PAULO CAMPISTA NUNES
DATE: 11/07/2023
TIME: 13:30
LOCAL: https://meet.google.com/oop-zktv-shk
TITLE:

Dark Matter Production in Future Muon Collider using a  Vectorial Isotriplet Model and the Process µ + µ −→ γ + missing energy

KEY WORDS:

Particle Physics. Dark matter. Machine Learning. Deep Neural Network.

PAGES: 80
BIG AREA: Ciências Exatas e da Terra
AREA: Física
SUBÁREA: Física das Partículas Elementares e Campos
SPECIALTY: Reações Específicas e Fenomiologia de Partículas
SUMMARY:

The Standard Model (SM) is a theory that can explain many phenomena in particle
physics (PF), but there are still many others not explained by the SM. For example, the nature of Dark Matter (DM), which makes up about 27 percent of the entire universe, is a mystery to PF. DM does not interact with ordinary matter in the way we know it, and because of this, it cannot be detected by usual means. There is great expectation DM can be produced by particle accelerators, such as the Large Hadron Collider (LHC), for example. The presence of DM may be associated to missing energies in the experiments. Several SM’s extensions consider a new DM candidate particle that can be a scalar, vector particle, a Dirac fermion, or Majorana. In this dissertation, we consider a spin 1 massive vector boson. The model under study in this dissertation is the so-called spin-one Isotriplet Dark Matter. In this model there are two parameters to be explored: the mass of the DM particle and the coupling variable (a), which ranges from 0 to 4π. In this model the SU (2) L symmetry is broken by the Higgs mechanism and the associated gauge boson has mass, being coupled only to the Higgs scalar field (ϕ). The possibility of implementing Muon colliders as an alternative to the colliders already employed is explored, due to the Muon having a high mass value, there will be very low emission of synchrotron radiation, besides being a fundamental particle, non-composite particle. The chosen channel for the development of this research is the single photon channel µ + µ −→ γ + missing energy. A Deep Neural Network (DNN) was constructed to separate the background and signal events. Initially the ability of the constructed DNN to separate the neutrinos from the SM is investigated in this paper. The variation of different values of center of mass (COM) energy, different values of mass for the DM particle and different values of the parameter a (inherent MIVME variable) were explored.

BANKING MEMBERS:
Externo à Instituição - ANDRE ASEVEDO NEPOMUCENO - UFF
Presidente - 205.483.627-34 - FERNANDO MARROQUIM LEAO DE ALMEIDA JUNIOR - UFRJ
Interno - 1212928 - HERON CARLOS DE GODOY CALDAS