Thesis

Searching for dark matter with the ATLAS detector using unconventional signatures

Details

  • Call:

    PT-CERN Call 2020/2

  • Academic Year:

    2020/2021

  • Domain:

    Astroparticle Physics

  • Supervisor:

    Nuno Castro

  • Co-Supervisor:

    Marek Tasevsky

  • Institution:

    Universidade do Minho

  • Host Institution:

    Laboratório de Instrumentação e Física Experimental de Partículas

  • Abstract:

    Although we have a wealth of evidence for the existence of dark matter, its nature is still a complete mystery which collider data can take an important role in uncovering. For this, the LHC collaborations have developed a comprehensive search programme for dark matter signatures, mostly based on X in addition to missing transverse energy topologies, with X being a gauge boson, a Higgs or jets. The current proposal aims at exploring for rare dark matter signatures by tagging either a top quark plus missing energy, the monotop signature, or pairs of soft leptons with scattered protons tagged at very small polar angles. The monotop signatures can be a powerful probe of specific dark matter signals appearing in models involving preferential couplings beyond the Standard Model to the top quark. Such signatures rely on the tagging of a highly boosted top quark, together with significant amounts of missing transverse energy. Proper modelling of the expected backgrounds, as well as advanced machine learning techniques, will be explored to enhance the expected sensitivity of this search, allowing to fully benefit from the ATLAS dataset to be collected during the third operation phase of the LHC. Close collaboration with the theory community will be pursued, allowing to explore the phenomenological implications of the obtained results. Complementary to this search, the current proposal also targets another rare signature, where the two scattered LHC protons emit two photons that annihilate to produce a pair of sleptons, which are particles used by theories beyond Standard Model, that decay into two neutralinos and two soft leptons, with the neutralinos being candidates for particles of Dark Matter. The protons, which stay intact after the interaction, are scattered through very small angles and can be detected with the ATLAS Forward Proton tagging detectors (AFP), effectively converting the LHC into a photon-photon collider. Since there is no underlying event, the two leptons are the only particles produced centrally. The invariant mass of the particles produced centrally can be measured precisely by determining the proton energy loss with the AFP detectors, even in the case of neutrinos in the final state. The tagging of the protons can provide a way of triggering signatures where the leptons are too soft to be triggered by themselves. This final state can be used to search for dark matter in photon-induced processes, using also the capability of the forward proton tagging detectors. Given the novelty of such searches in this setting, machine learning algorithms with the capacity of detecting generic new physics candidates will be developed. Such search for dark matter is challenging due to the low transverse momentum of the leptons produced. An adequate strategy for triggering this kind of processes is therefore needed. It implies the combination of proton tagging information with muon/electron triggers reconstructed with the ATLAS central detectors, already at the first level trigger and probably making use of the topological trigger processors. The development and optimisation of such a trigger strategy is also an objective of this project. The student will develop the work in the framework of the ATLAS international collaboration, and will be integrated in the ATLAS Portuguese Group, in close collaboration with the Institute of Physics of the Czech Academy of Sciences. The candidate will also contribute to the ATLAS data taking activities and to the commissioning and performance studies of the AFP detector, fundamental for the success of this project. Frequent presentations to the Collaboration of the results achieved are expected and the obtained results will lead to different publications in reference journals and presentations in international conferences and workshops.