CERN Accelerating science

Generic Processes & Materials - Workplan 2021

  • Fast simulation:
    • modernisation of EM shower parametrisation, including automated tuning procedures
    • implementation of example of machine learning inference within G4 using external libraries for calorimetry fast simulation
  • Geometrical biaising:
    • Support geometrical biasing
    • Try to merge extended examples with generic biasing where possible/necessary.
  • Generic Biasing:
    • Continue enriching event biasing options:​
      • DXTRAN-like biasing
      • Implicit capture
      • Occurrence biasing of charged particles, with cross-section changing over the step
      • AMS (Adaptive Multilevel Splitting)
    • Extend generic biasing scheme for at rest case
    • Statistical test suite to verify correctness of biasing wrt to analog
  • Materials:
    • Remove obsolete and improve existing interfaces to materials for the major release
    • Maintenance of basic classes G4Material and associated
  • Improvement of Reverse MC
    • Final Migration and test in MT mode
    • Proton simulation validation
    • Heavy ions.
    • Possible further improvement