Variance-Reduction Methods for Monte Carlo Simulation of Radiation Transport Pareja García, Salvador Lallena Rojo, Antonio Miguel Salvat, Francesc Monte Carlo simulation Statistical uncertainties Variance-reduction methods Splitting and Russian roulette Ant colony algorithms Interaction forcing Delta scattering We are thankful to the reviewers for their thorough analysis of the original manuscript and for many comments and suggestions. After a brief description of the essentials of Monte Carlo simulation methods and the definition of simulation efficiency, the rationale for variance-reduction techniques is presented. Popular variance-reduction techniques applicable to Monte Carlo simulations of radiation transport are described and motivated. The focus is on those techniques that can be used with any transport code, irrespective of the strategies used to track charged particles; they operate by manipulating either the number and weights of the transported particles or the mean free paths of the various interaction mechanisms. The considered techniques are 1) splitting and Russian roulette, with the ant colony method as builder of importance maps, 2) exponential transform and interaction-forcing biasing, 3) Woodcock or delta-scattering method, 4) interaction forcing, and 5) proper use of symmetries and combinations of different techniques. Illustrative results from analog simulations (without recourse to variance-reduction) and from variance-reduced simulations of various transport problems are presented. 2021-11-26T10:52:00Z 2021-11-26T10:52:00Z 2021-10-27 info:eu-repo/semantics/article García-Pareja S, Lallena AM and Salvat F (2021) Variance-Reduction Methods for Monte Carlo Simulation of Radiation Transport. Front. Phys. 9:718873. [doi: 10.3389/fphy.2021.718873] http://hdl.handle.net/10481/71773 10.3389/fphy.2021.718873 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España Frontiers Media