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Register a new userQuantifying the unknown: issues in simulation validation and their experimental impact
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The assessment of the reliability of Monte Carlo simulations is discussed, with emphasis on uncertainty quantification and the related impact on experimental results. Methods and techniques to account for epistemic uncertainties, i.e. for intrinsic knowledge gaps in physics modeling, are discussed with the support of applications to concrete experimental scenarios. Ongoing projects regarding the investigation of epistemic uncertainties in the Geant4 simulation toolkit are reported.
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The issue of how epistemic uncertainties affect the outcome of Monte Carlo simulation is discussed by means of a concrete use case: the simulation of the longitudinal energy deposition profile of low energy protons. A variety of electromagnetic and hadronic physics models is investigated, and their effects are analyzed. Possible systematic effects are highlighted. The results identify requirements for experimental measurements capable of reducing epistemic uncertainties in the simulation.
This paper updates and complements a previously published evaluation of computational methods for total and partial cross sections, relevant to modeling the photoelectric effect in Monte Carlo particle transport. It examines calculation methods that have become available since the publication of the previous paper, some of which claim improvements over previous calculations; it tests them with statistical methods against the same sample of experimental data collected for the previous evaluation. No statistically significant improvements are observed with respect to the calculation method identified in the previous paper as the state of the art for the intended purpose, encoded in the EPDL97 data library. Some of the more recent computational methods exhibit significantly lower capability to reproduce experimental measurements than the existing alternatives.
Radioactive decays are of concern in a wide variety of applications using Monte-Carlo simulations. In order to properly estimate the quality of such simulations, knowledge of the accuracy of the decay simulation is required. We present a validation of the original Geant4 Radioactive Decay Module, which uses a per-decay sampling approach, and of an extended package for Geant4-based simulation of radioactive decays, which, in addition to being able to use a refactored per-decay sampling, is capable of using a statistical sampling approach. The validation is based on measurements of calibration isotope sources using a high purity Germanium (HPGe) detector; no calibration of the simulation is performed. For the considered validation experiment equivalent simulation accuracy can be achieved with per-decay and statistical sampling.
Several models for the Monte Carlo simulation of Compton scattering on electrons are quantitatively evaluated with respect to a large collection of experimental data retrieved from the literature. Some of these models are currently implemented in general purpose Monte Carlo systems; some have been implemented and evaluated for possible use in Monte Carlo particle transport for the first time in this study. Here we present first and preliminary results concerning total and differential Compton scattering cross sections.
Backscattering is a sensitive probe of the accuracy of electron scattering algorithms implemented in Monte Carlo codes. The capability of the Geant4 toolkit to describe realistically the fraction of electrons backscattered from a target volume is extensively and quantitatively evaluated in comparison with experimental data retrieved from the literature. The validation test covers the energy range between approximately 100 eV and 20 MeV, and concerns a wide set of target elements. Multiple and single electron scattering models implemented in Geant4, as well as preassembled selections of physics models distributed within Geant4, are analyzed with statistical methods. The evaluations concern Gean
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