Searches for dark matter candidates in mono-W/Z final states with the ATLAS detector

The nature of Dark Matter in the Universe is one of the main questions in particle physics in the following decade. It already constitutes one of the pillars of the research program at the LHC at CERN where proton-proton collisions are produced with a centre-of-mass energy of 13 TeV. If dark matter particles were produced at the LHC, they would escape through the detectors unnoticed. However, those particles carry away energy and momentum, so their existence can be detected from the amount of energy and momentum after a collision. The mono-V (V ≡ W or Z boson) final state, in which a hadronically decaying vector boson is produced in association with invisible particles is considered as a golden channel. This project will focus on approaches based on neural networks to separate dark matter candidates from different background sources, using Monte-Carlo simulated samples and the full Run 2 data taken by the ATLAS detector.