Optimization of variance reduction techniques used in EGSnrc Monte Carlo Codes

Abstract

Monte Carlo (MC) simulations are often used in calculations of radiation transport to enable accurate prediction of radiation-dose, even though the computation is relatively time-consuming. In a typical MC simulation, significant computation time is allocated to following non-important events. To address this issue, variance reduction techniques (VRTs) have been suggested for reducing the statistical variance for the same computation time. Among the available MC simulation codes, electron gamma shower (National Research Council of Canada) (EGSnrc) is a general-purpose coupled electron-photon transport code that also features an even-handed, rich set of VRTs. The most well-known VRTs are the photon splitting, Russian roulette (RR), and photon cross-section enhancement (XCSE) techniques. The objective of this work was to determine the optimal combination of VRTs that increases the simulation speed and the efficiency of simulation, without compromising its accuracy. Selection of VRTs was performed using EGSnrc MC User codes, such as cavity and egs_chamber, for simulating various ion chamber geometries using 6 MV photon beams and 1.25 MeV 60Co photon beams. The results show that the combination of XCSE and RR yields the highest efficiency for ion-chamber dose calculations inside a 30 cm × 30 cm × 30 cm water phantom. Hence, properly selecting a different VRT without altering the underlying physics increases the efficiency of MC simulations for ion-chamber dose calculation.

Enhancement of the EGSnrc code egs_chamber for fast fluence calculations of charged particles

“…It is noteworthy that the investigation of VR-techniques can become quite tedious due to the interference of the different techniques [31] or the dependency on radiation setups because several VRT parameters have to be considered together in every beam setup [10] . For this reason we investigated the efficiency gain due to XCSE only.…”

“…For this reason we investigated the efficiency gain due to XCSE only. Additionally, it is found in [31] that XCSE offers the greatest efficiency enhancement when the VRTs are considered individually. The aim at this point is to compare the charged particle fluence scoring techniques and the corresponding efficiency gain resulting from XCSE in egs_chamber systematically in a given scenario.…”

egs++: Optimization of Simulation Transport Parameters

“…Mohammed et al (2016) studied the effect of reducing the time and the variance (statistical error) of simulation using different variance reduction techniques (VRTs) on simulation results obtained with EGSnrc (Mohammed et al, 2016). Another studies was compared the presence and effect of VRTs to the EGSnrc simulation (Shanmugasundaram & Chandrasekaran, 2018;Tuan et al, 2019). Other than that, optimal efficiency improving techniques (EITs) parameter selection depends on the simulation geometry and xray source in egs_cbct (Thing & Mainegra-Hing, 2014).…”