Pulse shape discrimination for event rejection in BEGe-type high-purity germanium detectors
- 1Jagiellonian University
- 2INFN Laboratori Nazionali del Gran Sasso
- 3Henryk Niewodniczański Institute of Nuclear Physics, Polish Academy of Sciences
Abstract
High-purity germanium detectors are widely used in rare-event searches due to their excellent energy resolution and extremely high intrinsic (radio)purity. In experiments searching for neutrinoless double beta decay in 76 76 Ge such as Legend , pulse shape discrimination is required to suppress multi-site γ γ events. In this work, we investigate whether pulse shape discrimination classifiers trained exclusively on γ γ ray data can be used to identify and reject α α events, without the need for dedicated α α training. In detectors such as Legend , the total number of registered α α events over the experiment lifetime is expected to be insufficient to train dedicated classifiers, while still contributing to the background. Two approaches based on machine learning are studied: a multilayer perceptron and a projective likelihood classifier. The p+ surface of a point-contact semi-planar germanium detector was exposed to 209 209 Po and 210 210 Po sources deposited on a thin gold foil. Two measurement campaigns were performed, yielding 1.36× 105 1.36 × 10 5 and 1.87× 106 1.87 × 10 6 α α events, respectively. Both classification methods achieve efficient separation of single-site and multi-site γ γ events while strongly reducing the α α component. The multilayer perceptron provides the best overall performance, with a signal-like event survival greater than 80%, a background-like event survival below 20%, and an α α -rejection factor exceeding 2.71× 104 2.71 × 10 4 . These results demonstrate that robust pulse shape discrimination for high-purity germanium detectors can be achieved using training information derived solely from γ γ events, providing a promising strategy for next-generation neutrinoless double beta decay searches.
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BibTeX
@article{biondi2026pulse,
title = {{Pulse shape discrimination for event rejection in BEGe-type high-purity germanium detectors}},
author = {A. Biondi and K. Szczepaniec and T. Mróz and M. Misiaszek and G. Zuzel},
journal = {The European Physical Journal C},
year = {2026},
month = oct,
doi = {10.1140/epjc/s10052-026-16463-9},
url = {https://link.springer.com/article/10.1140/epjc/s10052-026-16463-9},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Pulse shape discrimination for event rejection in BEGe-type high-purity germanium detectors
AU - A. Biondi
AU - K. Szczepaniec
AU - T. Mróz
AU - M. Misiaszek
AU - G. Zuzel
PY - 2026
DA - 2026/10/23
JO - The European Physical Journal C
DO - 10.1140/epjc/s10052-026-16463-9
UR - https://link.springer.com/article/10.1140/epjc/s10052-026-16463-9
AB - High-purity germanium detectors are widely used in rare-event searches due to their excellent energy resolution and extremely high intrinsic (radio)purity. In experiments searching for neutrinoless double beta decay in ^76 76 Ge such as Legend , pulse shape discrimination is required to suppress multi-site γ γ events. In this work, we investigate whether pulse shape discrimination classifiers trained exclusively on γ γ ray data can be used to identify and reject α α events, without the need for dedicated α α training. In detectors such as Legend , the total number of registered α α events over the experiment lifetime is expected to be insufficient to train dedicated classifiers, while still contributing to the background. Two approaches based on machine learning are studied: a multilayer perceptron and a projective likelihood classifier. The p+ surface of a point-contact semi-planar germanium detector was exposed to ^209 209 Po and ^210 210 Po sources deposited on a thin gold foil. Two measurement campaigns were performed, yielding 1.36× 10^5 1.36 × 10 5 and 1.87× 10^6 1.87 × 10 6 α α events, respectively. Both classification methods achieve efficient separation of single-site and multi-site γ γ events while strongly reducing the α α component. The multilayer perceptron provides the best overall performance, with a signal-like event survival greater than 80%, a background-like event survival below 20%, and an α α -rejection factor exceeding 2.71× 10^4 2.71 × 10 4 . These results demonstrate that robust pulse shape discrimination for high-purity germanium detectors can be achieved using training information derived solely from γ γ events, providing a promising strategy for next-generation neutrinoless double beta decay searches.
SN - 1434-6044
SN - 1434-6052
ER -