• Constraint Preserving Mixers for the Quantum Approximate Optimization Algorithm 

      Fuchs, Franz Georg; Lye, Kjetil Olsen; Nilsen, Halvor Møll; Stasik, Alexander Johannes; Sartor, Giorgio (Peer reviewed; Journal article, 2022)
      The quantum approximate optimization algorithm/quantum alternating operator ansatz (QAOA) is a heuristic to find approximate solutions of combinatorial optimization problems. Most of the literature is limited to quadratic ...
    • Data quality issues for vibration sensors: a case study in ferrosilicon production 

      Waszak, Maryna; Moen, Terje; Eidnes, Sølve; Stasik, Alexander Johannes; Hansen, Anders; Bouquet, Gregory; Pultier, Antoine; Ma, Xiang; Tørlen, Idar; Henriksen, Bjørn; Aamodt, Arianeh; Roman, Dumitru (Chapter, 2022)
      Digitisation in the mining and metal processing industries plays a key role in their modernisation. Production processes are more and more supported by a variety of sensors that produce large amounts of data that meant to ...
    • Pseudo-Hamiltonian neural networks with state-dependent external forces 

      Stasik, Alexander Johannes; Sterud, Camilla; Bøhn, Eivind Eigil; Riemer-Sørensen, Signe (Peer reviewed; Journal article, 2023)
      Hybrid machine learning based on Hamiltonian formulations has recently been successfully demonstrated for simple mechanical systems, both energy conserving and not energy conserving. We introduce a pseudo-Hamiltonian ...