Blar i Department of Physics and Technology på forfatter "Alvestad, Daniel"
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Beyond cuts in small signal scenarios: Enhanced sneutrino detectability using machine learning
Alvestad, Daniel; Fomin, Nikolai; Kersten, Jörn; Mæland, Steffen; Strumke, Inga (Journal article; Peer reviewed, 2023)We investigate enhancing the sensitivity of new physics searches at the LHC by machine learning in the case of background dominance and a high degree of overlap between the observables for signal and background. We use two ... -
Enhancing detectablility of tau-sneutrino signatures using machine learning
Alvestad, Daniel (Master thesis, 2018-06-27)In this thesis, the collider signatures of the scenario with a tau-sneutrino next-to-lightest supersymmetric particle (NLSP) at LHC are studied using machine learning. The parameter region of the non-universal Higgs masses ...