{"title":"Modeling the stochastic-deterministic boundary in luminescence: Consequences for dose estimation","authors":"Eren Şahiner","doi":"10.1016/j.radmeas.2025.107529","DOIUrl":null,"url":null,"abstract":"<div><div>Kinetic models based on deterministic ordinary differential equations (ODEs) are effective for macroscopic systems, but a breakdown of their foundational assumptions is observed for single-grain and nanodosimetric applications where particle numbers are small. In this study, the metrological consequences of this stochastic-deterministic divergence are quantitatively investigated. The study's primary contribution is to deconvolve the divergence into two distinct components: a robust, inherent imprecision and a model-dependent, systematic inaccuracy. Intrinsic physical stochasticity is confirmed to be a dominant source of imprecision, generating an irreducible dose uncertainty of over 20 % that accounts for a significant fraction of single-grain overdispersion. Conversely, a systematic inaccuracy (e.g., a >50 % dose bias), initially observed in a simplified model, is demonstrated to be a methodological artifact, not a universal consequence of discreteness. It is shown that this systematic bias can be reduced to negligible levels (<1 %) by using either a more physically realistic multi-trap model or a correctly specified simple model. Based on this deconvolution, analytical protocols are assessed. An \"Average-Dose-First\" protocol is identified as the superior method, as it provides an accurate final dose estimate while correctly propagating measurement uncertainty. A general framework for understanding and partitioning variance in luminescence data is thereby established. Practical recommendations are provided for improving the accuracy of modern luminescence science by selecting appropriate models and using correct statistical protocols, with a strong emphasis on the critical need for model validation.</div></div>","PeriodicalId":21055,"journal":{"name":"Radiation Measurements","volume":"189 ","pages":"Article 107529"},"PeriodicalIF":2.2000,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiation Measurements","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1350448725001581","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Kinetic models based on deterministic ordinary differential equations (ODEs) are effective for macroscopic systems, but a breakdown of their foundational assumptions is observed for single-grain and nanodosimetric applications where particle numbers are small. In this study, the metrological consequences of this stochastic-deterministic divergence are quantitatively investigated. The study's primary contribution is to deconvolve the divergence into two distinct components: a robust, inherent imprecision and a model-dependent, systematic inaccuracy. Intrinsic physical stochasticity is confirmed to be a dominant source of imprecision, generating an irreducible dose uncertainty of over 20 % that accounts for a significant fraction of single-grain overdispersion. Conversely, a systematic inaccuracy (e.g., a >50 % dose bias), initially observed in a simplified model, is demonstrated to be a methodological artifact, not a universal consequence of discreteness. It is shown that this systematic bias can be reduced to negligible levels (<1 %) by using either a more physically realistic multi-trap model or a correctly specified simple model. Based on this deconvolution, analytical protocols are assessed. An "Average-Dose-First" protocol is identified as the superior method, as it provides an accurate final dose estimate while correctly propagating measurement uncertainty. A general framework for understanding and partitioning variance in luminescence data is thereby established. Practical recommendations are provided for improving the accuracy of modern luminescence science by selecting appropriate models and using correct statistical protocols, with a strong emphasis on the critical need for model validation.
期刊介绍:
The journal seeks to publish papers that present advances in the following areas: spontaneous and stimulated luminescence (including scintillating materials, thermoluminescence, and optically stimulated luminescence); electron spin resonance of natural and synthetic materials; the physics, design and performance of radiation measurements (including computational modelling such as electronic transport simulations); the novel basic aspects of radiation measurement in medical physics. Studies of energy-transfer phenomena, track physics and microdosimetry are also of interest to the journal.
Applications relevant to the journal, particularly where they present novel detection techniques, novel analytical approaches or novel materials, include: personal dosimetry (including dosimetric quantities, active/electronic and passive monitoring techniques for photon, neutron and charged-particle exposures); environmental dosimetry (including methodological advances and predictive models related to radon, but generally excluding local survey results of radon where the main aim is to establish the radiation risk to populations); cosmic and high-energy radiation measurements (including dosimetry, space radiation effects, and single event upsets); dosimetry-based archaeological and Quaternary dating; dosimetry-based approaches to thermochronometry; accident and retrospective dosimetry (including activation detectors), and dosimetry and measurements related to medical applications.