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Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing
Scintillator detector response modeling has become an essential tool in various research fields such as particle and nuclear physics, astronomy or geophysics. Yet, due to the system complexity and the requirement for accurate electron response measurements, model inference and calibration remains a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682496/ https://www.ncbi.nlm.nih.gov/pubmed/38012127 http://dx.doi.org/10.1038/s41467-023-42574-y |
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author | Breitenmoser, David Cerutti, Francesco Butterweck, Gernot Kasprzak, Malgorzata Magdalena Mayer, Sabine |
author_facet | Breitenmoser, David Cerutti, Francesco Butterweck, Gernot Kasprzak, Malgorzata Magdalena Mayer, Sabine |
author_sort | Breitenmoser, David |
collection | PubMed |
description | Scintillator detector response modeling has become an essential tool in various research fields such as particle and nuclear physics, astronomy or geophysics. Yet, due to the system complexity and the requirement for accurate electron response measurements, model inference and calibration remains a challenge. Here, we propose Compton edge probing to perform non-proportional scintillation model (NPSM) inference for inorganic scintillators. We use laboratory-based gamma-ray radiation measurements with a NaI(Tl) scintillator to perform Bayesian inference on a NPSM. Further, we apply machine learning to emulate the detector response obtained by Monte Carlo simulations. We show that the proposed methodology successfully constrains the NPSM and hereby quantifies the intrinsic resolution. Moreover, using the trained emulators, we can predict the spectral Compton edge dynamics as a function of the parameterized scintillation mechanisms. The presented framework offers a simple way to infer NPSMs for any inorganic scintillator without the need for additional electron response measurements. |
format | Online Article Text |
id | pubmed-10682496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106824962023-11-30 Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing Breitenmoser, David Cerutti, Francesco Butterweck, Gernot Kasprzak, Malgorzata Magdalena Mayer, Sabine Nat Commun Article Scintillator detector response modeling has become an essential tool in various research fields such as particle and nuclear physics, astronomy or geophysics. Yet, due to the system complexity and the requirement for accurate electron response measurements, model inference and calibration remains a challenge. Here, we propose Compton edge probing to perform non-proportional scintillation model (NPSM) inference for inorganic scintillators. We use laboratory-based gamma-ray radiation measurements with a NaI(Tl) scintillator to perform Bayesian inference on a NPSM. Further, we apply machine learning to emulate the detector response obtained by Monte Carlo simulations. We show that the proposed methodology successfully constrains the NPSM and hereby quantifies the intrinsic resolution. Moreover, using the trained emulators, we can predict the spectral Compton edge dynamics as a function of the parameterized scintillation mechanisms. The presented framework offers a simple way to infer NPSMs for any inorganic scintillator without the need for additional electron response measurements. Nature Publishing Group UK 2023-11-28 /pmc/articles/PMC10682496/ /pubmed/38012127 http://dx.doi.org/10.1038/s41467-023-42574-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Breitenmoser, David Cerutti, Francesco Butterweck, Gernot Kasprzak, Malgorzata Magdalena Mayer, Sabine Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing |
title | Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing |
title_full | Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing |
title_fullStr | Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing |
title_full_unstemmed | Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing |
title_short | Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing |
title_sort | emulator-based bayesian inference on non-proportional scintillation models by compton-edge probing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682496/ https://www.ncbi.nlm.nih.gov/pubmed/38012127 http://dx.doi.org/10.1038/s41467-023-42574-y |
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