Quantifying the unknown: issues in simulation validation and their experimental impact

TL;DR

This paper discusses the challenges in validating Monte Carlo simulations, focusing on quantifying uncertainties, especially epistemic ones, and their effects on experimental results, supported by applications and ongoing projects in Geant4.

Contribution

It introduces methods for uncertainty quantification in simulation validation and reports on ongoing efforts to investigate epistemic uncertainties in Geant4.

Findings

Methods for epistemic uncertainty quantification are discussed.

Applications demonstrate the impact of uncertainties on experimental results.

Ongoing projects aim to improve simulation reliability.

Abstract

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.