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Search for leptonically interacting dark matter with the XENON1T electronic recoil data

Abstract : The present thesis, focus on the experimental testing of theories beyond the Standard Model, predicting a specific particle nature for the dark matter (DM) and, specifically, in the effort to directly detect leptonically interacting DM particles with the use of the low-background, underground detector XENON1T. We, initially, investigate the electronic recoil (ER) background in the search of a possible modulation, which is expected due to the relative motion between the Earth and the DM halo. In the absence of observation of WIMP-induced nuclear recoils, an alternative interpretation through a leptophilic DM, finds its place as a natural hypothesis that should be tested, taking advantage of the long-term stability of the ER background of the XENON1T detector. Then, we focus on the search of leptonically interacting DM particles with mass in the sub-GeV scale, emerging in the framework of so-called,”hidden sector" theories, predicting a leptophilic DM with mass in MeV scale, that could interact with the target causing inelastic atomic processes, such as ionization. It is in the region of this expected signal that a huge and, so far, incomprehensible background arises, driven by the so-called single electrons, small charge signals that appear to derive from a multitude of quantum processes in the atomic level of LXe. What can we infer about leptophilic DM without the possibility of background subtraction? Can we classify the processes that create this background? How can machine learning techniques, like Neural Networks, mitigate such backgrounds? These are some of the questions, about the exciting topic of DM direct detection, that we will try to address in this work.
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Submitted on : Saturday, October 1, 2022 - 1:04:00 AM
Last modification on : Wednesday, October 19, 2022 - 4:04:33 AM


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  • HAL Id : tel-03793329, version 1


Jean-Philippe Zopounidis. Search for leptonically interacting dark matter with the XENON1T electronic recoil data. High Energy Physics - Experiment [hep-ex]. Sorbonne Université, 2020. English. ⟨NNT : 2020SORUS364⟩. ⟨tel-03793329⟩



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