Three-dimensional position reconstruction of orthogonal-strip planar high-purity germanium detectors using maximum likelihood estimation
Fuente:
arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915408029679616 |
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| author | Zhang, Qiuli Zhang, Peng Dai, Wenhhan Yang, Mingxin Tian, Yang Zeng, Ming Ma, Hao Zeng, Zhi |
| author_facet | Zhang, Qiuli Zhang, Peng Dai, Wenhhan Yang, Mingxin Tian, Yang Zeng, Ming Ma, Hao Zeng, Zhi |
| contents | Orthogonal-strip planar high-purity germanium (HPGe) detectors can reconstruct three-dimensional (3D) positions of photon interactions through analysis of parameters extracted from multiple charge signals. The conventional method independently reconstructs positions in each dimension using amplitude-based parameters, leading to noise sensitivity and systematic biases. In this study, we propose a multi-parameter-joint reconstruction method based on maximum likelihood estimation (MLE) which establishes a mapping between pulse shape parameters and corresponding 3D positions. To mitigate the effects of electronic noise, we employ integral-based parameters. The reconstruction performance was evaluated using pulse shape simulations. For 100 keV photons under 1 keV root-mean-square (RMS) electronic noise, the maximum Z reconstruction bias was reduced from 0.4 mm to 0.02 mm in the central region and from 2 mm to 0.15 mm near the electrodes. The maximum reconstruction bias in the X/Y directions was reduced from 0.4 mm to 0.016 mm. Furthermore, the use of integral-based parameters mitigated the rapid degradation of resolution under high-noise conditions. The achieved position resolution ranged from 0.07 mm to 0.16 mm in the Z directions and from 0.07 mm to 0.44 mm in the X/Y direction. This method offers a promising approach to 3D position reconstruction with HPGe detectors for applications such as medical imaging and gamma-ray astronomy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_18222 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Three-dimensional position reconstruction of orthogonal-strip planar high-purity germanium detectors using maximum likelihood estimation Zhang, Qiuli Zhang, Peng Dai, Wenhhan Yang, Mingxin Tian, Yang Zeng, Ming Ma, Hao Zeng, Zhi Instrumentation and Detectors Nuclear Experiment Orthogonal-strip planar high-purity germanium (HPGe) detectors can reconstruct three-dimensional (3D) positions of photon interactions through analysis of parameters extracted from multiple charge signals. The conventional method independently reconstructs positions in each dimension using amplitude-based parameters, leading to noise sensitivity and systematic biases. In this study, we propose a multi-parameter-joint reconstruction method based on maximum likelihood estimation (MLE) which establishes a mapping between pulse shape parameters and corresponding 3D positions. To mitigate the effects of electronic noise, we employ integral-based parameters. The reconstruction performance was evaluated using pulse shape simulations. For 100 keV photons under 1 keV root-mean-square (RMS) electronic noise, the maximum Z reconstruction bias was reduced from 0.4 mm to 0.02 mm in the central region and from 2 mm to 0.15 mm near the electrodes. The maximum reconstruction bias in the X/Y directions was reduced from 0.4 mm to 0.016 mm. Furthermore, the use of integral-based parameters mitigated the rapid degradation of resolution under high-noise conditions. The achieved position resolution ranged from 0.07 mm to 0.16 mm in the Z directions and from 0.07 mm to 0.44 mm in the X/Y direction. This method offers a promising approach to 3D position reconstruction with HPGe detectors for applications such as medical imaging and gamma-ray astronomy. |
| title | Three-dimensional position reconstruction of orthogonal-strip planar high-purity germanium detectors using maximum likelihood estimation |
| topic | Instrumentation and Detectors Nuclear Experiment |
| url | https://arxiv.org/abs/2507.18222 |