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arXiv 2302.05641physics.ins-detastro-ph.IMcond-mat.mtrl-sciphysics.comp-phphysics.data-an
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基于仿真器的非比例闪烁模型贝叶斯推断:康普顿边缘探测方法

Emulator-based Bayesian Inference on Non-Proportional Scintillation Models by Compton-Edge Probing

David Breitenmoser, Francesco Cerutti, Gernot Butterweck, Malgorzata Magdalena Kasprzak, Sabine Mayer

AI总结:

本文提出利用康普顿边缘探测结合贝叶斯推断和机器学习仿真器,在无需额外电子响应测量的条件下约束无机闪烁体的非比例闪烁模型并量化固有分辨率。

摘要:

闪烁体探测器响应建模已成为粒子与核物理、天文学或地球物理学等多个研究领域的重要工具。然而,由于系统复杂性以及对精确电子响应测量的要求,模型推断与校准仍然是一项挑战。本文提出利用康普顿边缘探测对无机闪烁体进行非比例闪烁模型(NPSM)推断。我们使用基于 NaI(Tl) 闪烁体的实验室伽马射线辐射测量,对 NPSM 执行贝叶斯推断。此外,我们应用机器学习来仿真由蒙特卡罗模拟获得的探测器响应。我们表明,所提出的方法能够成功约束 NPSM,并由此量化固有分辨率。此外,利用训练好的仿真器,我们可以预测光谱康普顿边缘动力学随参数化闪烁机制的变化。所提出的框架为任意无机闪烁体推断 NPSM 提供了一种新途径,而无需额外的电子响应测量。

英文摘要:

Scintillator detector response modelling 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 novel way to infer NPSMs for any inorganic scintillator without the need for additional electron response measurements.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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