Systematic incorporation of nuclear quantum effects into atomistic simulations by smoothed trajectory analysis

Documents similaires

• Short-range $Δ$-Machine Learning: A cost-efficient strategy to transfer chemical accuracy to condensed phase systems
  par: Mészáros, Bence Balázs, et autres
  Publié: (2025)
• Random sampling versus active learning algorithms for machine learning potentials of quantum liquid water
  par: Stolte, Nore, et autres
  Publié: (2024)
• Nuclear Quantum Effects in Liquid Water Are Negligible for Structure but Significant for Dynamics
  par: Stolte, Nore, et autres
  Publié: (2024)
• Introduction to machine learning potentials for atomistic simulations
  par: Thiemann, Fabian L., et autres
  Publié: (2024)
• Model selection in atomistic simulation
  par: Moussa, Jonathan E.
  Publié: (2023)