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Self-Organised Polylinear Regression Maps As a Method of Resolving HPGe Detector Responses

2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)(2024)

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Abstract
Within the field of Nuclear Instrumentation, the technique of Pulse Shape Analysis (PSA) is used to apply bespoke timing and energy corrections for detectors by interrogating the signal profiles corresponding to their spatial response. Parametric PSA methods are suitable for high-rate applications but rely on human-interpretable corrections and are often limited in their accuracy and application to multi-interaction signals. Non-parametric PSA methods such as the gamma-ray localisation used in the Advanced Gamma Tracking Array (AGATA) provide excellent prediction accuracy but are rate-limited and can only operate at a few kHz. In this work we propose a pseudo-parametric method using Self-Organising Maps (SOMs) for generating a human-interpretable approximation of the underlying detector response. These SOMs can be experimentally trained for accurate analytical regression of a variety of parameters from radial and cartesian position to timing. This method provides an efficient and tuneable way for the prediction of signal characteristics when a detector exhibits complex non-linear behaviour whilst capable of being implemented real-time on conventional digitiser hardware.
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要点】:本研究提出了一种伪参数方法,使用自组织映射(SOMs)生成探测器响应的近似,解决高纯锗(HPGe)探测器响应问题,兼具参数方法的实时处理能力和非参数方法的预测精度。

方法】:通过自组织映射(SOMs)进行信号特征的准确分析回归,该方法可以实验性地训练以预测各种参数,如径向和笛卡尔位置及时序。

实验】:文中未具体描述实验细节,但提出的方法能够应用于传统的数字化硬件,实现实时信号特征预测,且未提及使用的数据集名称和具体实验结果。