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9 September 2019 Consistent principles for particle identification by pulse shape discriminating systems
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Abstract
Identifying particles that interact in materials that exhibit pulse-shape discrimination (PSD) is a statistical classifier problem. The field of statistical classifiers provides a toolkit of elements and principles that PSD can employ and re-use regardless of the detector material and read-out. Journals have published a myriad of PSD papers over the decades featuring useful components and concepts for implementing and/or improving particle identification. This paper categorizes and assembles PSD methods into one consistent taxonomy. Among the essential elements to consider when building a classifier, one encounters features, pre-processed and reduced features, labels, contamination, coverage, the model, the classifier, optimization and performance metrics, training, testing, scoring, performance trade curves, and thresholding.
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Ronald E. Wurtz "Consistent principles for particle identification by pulse shape discriminating systems", Proc. SPIE 11114, Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XXI, 111140X (9 September 2019); https://doi.org/10.1117/12.2528898
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