• 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 ...
    • Evaluating the price of tiny kinetic mixing 

      Gherghetta, Tony; Kersten, Jörn; Olive, Keith A.; Pospelov, Maxim (Peer reviewed; Journal article, 2019)
      We consider both “bottom-up” and “top-down” approaches to the origin of gauge kinetic mixing. We focus on the possibilities for obtaining kinetic mixings ϵ which are consistent with experimental constraints and are much ...
    • Minimal sterile neutrino dark matter 

      Bringmann, Torsten; Depta, Paul Frederik; Hufnagel, Marco; Kersten, Jörn; Ruderman, Joshua T.; Schmidt-Hoberg, Kai (Journal article; Peer reviewed, 2023)
      We propose a novel mechanism to generate sterile neutrinos νs in the early Universe, by converting ordinary neutrinos να in scattering processes νsνα→νsνs. After initial production by oscillations, this leads to an exponential ...
    • Small-Scale Crisis in Cosmology – Sterile Neutrinos to the Rescue? 

      Kersten, Jörn (Peer reviewed; Journal article, 2019-04-24)
      The ΛCDM standard model of cosmology is in excellent agreement with data on large scales but has difficulty explaining all observations on small scales. I discuss a simple particle physics model involving a new MeV-scale ...