Thesis

Machine Learning Methods to improve the Phase II ATLAS Trigger system

• Call:

  PT-CERN Call 2022/1

• Academic Year:

  2022

• Domain:

  Astrophysics

• Supervisor:

  Patricia Conde Muino

• Co-Supervisor:

  Inês Ochoa

• Institution:

  Instituto Superior Técnico (Universidade de Lisboa)

• Host Institution:

  Laboratório de Instrumentação e Física Experimental de Partículas

• Abstract:

  The objective of this research project will focus on the improvement of the calorimeter clustering and jet reconstruction algorithms, using ML techniques, for the Phase II Upgrade of the ATLAS detector. The methods to explore include several possibilities, from the use of ML to improve the clusters or jets energy measurement to the exploration of Graph Neural Networks for the calorimeter clustering reconstruction.