Banca de DEFESA: NATÁLIA CRISTINA TRINDADE DO NASCIMENTO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : NATÁLIA CRISTINA TRINDADE DO NASCIMENTO
DATE: 12/07/2023
TIME: 14:00
LOCAL: meet.google.com/ady-njah-vpd
TITLE:

Vector Ressonances Contribution to the Dark Matter Search on LHC

KEY WORDS:

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

PAGES: 85
BIG AREA: Ciências Exatas e da Terra
AREA: Física
SUBÁREA: Física das Partículas Elementares e Campos
SPECIALTY: Reações Específicas e Fenomiologia de Partículas
SUMMARY:

Dark matter is one of the great mysteries of the Universe that we still haven’t been able to
unravel, despite all the success in describing the fundamental constituents of matter, only
15% is described by the Standard Model. We know about the existence of this large amount of
matter because of cosmological observations, in which for certain structures in the Universe
to exist in the way we observe, the existence of a mass that we cannot see is necessary. There
are varied approaches to looking for dark matter, and given the success of the Standard Model
in describing known matter in terms of fundamental particles, we believe that dark matter
must be made up of particles that can be accommodated by a model that is an extension
of the Standard Model. In our work, the search for dark matter is linked to the LHC particle
collider and the characteristics of its ATLAS detector and due to the huge amount of data
generated in particle collisions, we use Artificial Intelligence software to help us in this search.
We use artificial deep neural networks, implementing a binary classifier in TensorFlow in
order to separate the events that are from the standard model from the possible dark matter
events, with data generated in CalcHep implementing the ZP-TP-DM model.

BANKING MEMBERS:
Interno - 1217987 - ANDRE LUIZ MOTA
Presidente - 364974 - MARIA ALINE BARROS DO VALE
Externo à Instituição - SERGIO MARTINS DE SOUZA - UFLA