Goupil: A Monte Carlo engine for the backward transport of low-energy gamma-rays

TL;DR

Goupil is a Python-based Monte Carlo library that efficiently simulates low-energy gamma-ray transport in complex geometries, enabling accurate detector response modeling with high event rates.

Contribution

It introduces a backward sampling algorithm tailored for low-energy gamma-ray transport, improving efficiency in large-source-to-detector size ratios.

Findings

Accurately simulates detector response to gamma isotopes within 1%

Achieves event rates of a few kHz on standard CPUs

Effective for geometries with large source sizes relative to detectors

Abstract

Goupil is a software library designed for the Monte Carlo transport of low-energy gamma-rays, such as those emitted from radioactive isotopes. The library is distributed as a Python module. It implements a dedicated backward sampling algorithm that is highly effective for geometries where the source size largely exceeds the detector size. When used in conjunction with a conventional Monte Carlo engine (i.e., Geant), the response of a scintillation detector to gamma-active radio-isotopes scattered over the environment is accurately simulated (to the nearest percent) while achieving events rates of a few kHz (with a ~2.3 GHz CPU).