Blar i UiS Brage på forfatter "Alvestad, Daniel"

Viser treff 1-4 av 4

    • Beyond cuts in small signal scenarios: Enhanced sneutrino detectability using machine learning 

      Alvestad, Daniel; Fomin, Nikolai; Kersten, Jörn; Mæland, Steffen; Strumke, Inga (Peer reviewed; Journal article, 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 ...

    • Real-Time Complex Langevin - A Differential Programming Perspective 

      Alvestad, Daniel (PhD thesis UiS;, Doctoral thesis, 2023)
      In this thesis, I aim to find solutions to the NP-hard sign-problem that arises when modeling strongly correlated systems in real-time. I will use the complex Langevin (CLE) method, and address its problem of runaway ...

    • Stable solvers for real-time Complex Langevin 

      Alvestad, Daniel; Larsen, Rasmus Normann; Rothkopf, Alexander Karl (Peer reviewed; Journal article, 2021-08)
      This study explores the potential of modern implicit solvers for stochastic partial differential equations in the simulation of real-time complex Langevin dynamics. Not only do these methods offer asymptotic stability, ...

    • Towards learning optimized kernels for complex Langevin 

      Alvestad, Daniel; Larsen, Rasmus Normann; Rothkopf, Alexander Karl (Peer reviewed; Journal article, 2023)
      We present a novel strategy aimed at restoring correct convergence in complex Langevin simulations. The central idea is to incorporate system-specific prior knowledge into the simulations, in order to circumvent the NP-hard ...