Saved in:
Bibliographic Details
Main Authors: Niess, Valentin, Vernet, Kinson, Terray, Luca
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.02414
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918024820293632
author Niess, Valentin
Vernet, Kinson
Terray, Luca
author_facet Niess, Valentin
Vernet, Kinson
Terray, Luca
contents 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).
format Preprint
id arxiv_https___arxiv_org_abs_2412_02414
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Goupil: A Monte Carlo engine for the backward transport of low-energy gamma-rays
Niess, Valentin
Vernet, Kinson
Terray, Luca
Computational Physics
Nuclear Experiment
Geophysics
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).
title Goupil: A Monte Carlo engine for the backward transport of low-energy gamma-rays
topic Computational Physics
Nuclear Experiment
Geophysics
url https://arxiv.org/abs/2412.02414