title: Monte Carlo variance reduction techniques: an overview with some practical examples.
abstract: Since the first developments of Monte Carlo radiation transport codes, the importance of solving deep penetration problems in the phase space was pointed out. Whilst natural Monte Carlo radiation transport models are rather easy and straightforward to be implemented, apart from geometry extreme complexities that could limit the modelling capabilities of the user, the possibility to obtain results with high precision and reasonable CPU time, when the scored events contributing to the response of interest are characterised by a low probability of occurrence, can be guaranteed only through biased games for which the user needs a robust expertise. The present paper wanted to present in a concise way the main aspects of the variance reduction techniques and some practical application to help the users in becoming more familiar with such a necessary tool.
authors.affiliation: ENEA, IRP-Radiation Protection Institute, 16 via dei Colli I-40136, Bologna, Italy. gianfranco.gualdrini@enea.it
authors.forename: G
authors.initials: G
authors.lastname: Gualdrini
authors.forename: P
authors.initials: P
authors.lastname: Ferrari
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D003198:Computer Simulation; D017076:Computer-Aided Design; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D009502:Neutrons; D017785:Photons; D011835:Radiation Protection / Q000379:methods*; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage