Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study
The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the sys...
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| Published in | Journal of instrumentation Vol. 20; no. 4; p. P04025 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Bristol
IOP Publishing
01.04.2025
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| ISSN | 1748-0221 1748-0221 |
| DOI | 10.1088/1748-0221/20/04/P04025 |
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| Abstract | The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle. |
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| AbstractList | The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle. The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation.This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector.The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency.The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers).The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle. |
| Author | Cortesi, M. Di Carlo, S. Harca, I.M. Dziubinski, S. |
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| Cites_doi | 10.1016/j.nima.2011.03.009 10.1088/1748-0221/11/02/T02005 10.1016/j.nima.2015.04.020 10.1016/j.nima.2004.02.015 10.1088/1748-0221/8/05/P05025 10.1063/5.0124846 10.1088/1748-0221/5/09/P09006 10.3390/instruments5010005 10.1088/1748-0221/15/12/P12020 10.1088/1748-0221/7/10/P10005 10.1016/j.nimb.2023.05.039 10.1007/s10967-021-08007-0 10.1063/5.0068180 10.3390/coatings13010122 10.1016/j.engappai.2023.107593 10.1051/epjconf/202329010006 10.1016/j.nima.2004.08.100 10.1088/1748-0221/15/03/P03025 10.1016/j.procs.2020.04.020 10.1016/S0168-9002(03)01368-8 10.1016/j.nima.2012.09.041 10.1016/s0168-9002(98)00960-7 10.1016/s0168-9002(97)00601-3 |
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| References | Santiago (bf4bac0e8be4aa053e20b12277da74c52) 2013; 698 Janardhanan (b03c916996524992c5eb983bd7d499c7f) 2020; 171 Blake (b19077db4ec87702333a223487c029e03) 2015; 791 NEXT Collaboration (b302428f21964e50c6fd57ffabb9df9e8) 2013; 8 Li (bb250a3bbdee25a7fdb7d7243690a65ed) 2016; 11 bad93d924f669694b066b53eb0ec73626 Cortesi (ba213df1b7c99ee1cb2aacf5d5ab9c547) 2020; 15 Hans (bc95635b4a04fa24727cf3089c718beb7) 2020; 15 bc4ad07c8d0e48b46b87bd3ed5cb572b1 Lippmann (be46ed9d0f490e72100df80d6ed343b12) 2012; 666 GEANT4 Collaboration (bee73ff6af1088b4c2f0493d8e6a1d3b9) 2003; 506 Aprile (bbbbda660eb4381159bb90d2663791cf2) 2012; 7 Gudivada (b7841f5cf4d591327f4ff098a301238fc) 2018 Fernandes (ba588f3301358d7842a43c43013fbb0fd) 2010; 5 Stenzel (bfc1a129398aed3eed08d8c145f1e281a) 2023; 13 Kimura (b8fbad9e673cd1c8d6d4cfd8c20072960) 2005; 538 Hijikata (b6612bcea4bd2e19ce231409a45f232ac) 2023; 541 Khriachkov (b45b9526c9deec424b4e7ac28faa9bad0) 1997; 394 Morii (b89c291f0c22214369167b42dfc5c4f3e) 2004; 526 Hitachi (bfbe3598565ab010150a70b41c7fa0ee0) 2021; 5 Anthony (b1cc09d3c2bb0b1e707bd7f68d71973f0) 2022; 93 Yurkon (b9664a22905b3b6e95c446ae0c189f744) 1999; 422 Liu (bdaa9c0cd7e37f24e7a254d29c3672cf7) 2021; 330 Cortesi (b1964f295e3d695328857b3342eebc7c6) 2023; 290 (b0554c789bc1d2bf05c4db032c653c61a) 2022 Cortesi (bbcc00d4dc4ebd83cda367cefdef8d3ee) 2022; 93 Le-Duc (b7a8220306c6a774eeac20c1c3b7b457a) 2024; 129 |
| References_xml | – volume: 666 start-page: 148 year: 2012 ident: be46ed9d0f490e72100df80d6ed343b12 article-title: Particle identification publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2011.03.009 – volume: 11 year: 2016 ident: bb250a3bbdee25a7fdb7d7243690a65ed article-title: Performance of Photosensors in the PandaX-I Experiment publication-title: JINST doi: 10.1088/1748-0221/11/02/T02005 – volume: 791 start-page: 27 year: 2015 ident: b19077db4ec87702333a223487c029e03 article-title: Quenching the scintillation in CF_4 Cherenkov gas radiator publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2015.04.020 – volume: 526 start-page: 399 year: 2004 ident: b89c291f0c22214369167b42dfc5c4f3e article-title: Quenching Effects in Nitrogen Gas Scintillation publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2004.02.015 – ident: bc4ad07c8d0e48b46b87bd3ed5cb572b1 – volume: 8 year: 2013 ident: b302428f21964e50c6fd57ffabb9df9e8 article-title: Ionization and scintillation response of high-pressure xenon gas to alpha particles publication-title: JINST doi: 10.1088/1748-0221/8/05/P05025 – volume: 93 year: 2022 ident: bbcc00d4dc4ebd83cda367cefdef8d3ee article-title: Design and construction of a novel energy-loss optical scintillation system (ELOSS) for heavy-ion particle identification publication-title: Rev. Sci. Instrum. doi: 10.1063/5.0124846 – start-page: 31 year: 2018 ident: b7841f5cf4d591327f4ff098a301238fc article-title: Open-Source Libraries, Application Frameworks, and Workflow Systems for NLP – volume: 5 year: 2010 ident: ba588f3301358d7842a43c43013fbb0fd article-title: Primary and secondary scintillation measurements in a xenon Gas Proportional Scintillation Counter publication-title: JINST doi: 10.1088/1748-0221/5/09/P09006 – volume: 5 start-page: 5 year: 2021 ident: bfbe3598565ab010150a70b41c7fa0ee0 article-title: Luminescence Response and Quenching Models for Heavy Ions of 0.5 keV to 1 GeV/n in Liquid Argon and Xenon publication-title: Instruments doi: 10.3390/instruments5010005 – volume: 15 year: 2020 ident: bc95635b4a04fa24727cf3089c718beb7 article-title: Light Yield Quenching and Quenching Remediation in Liquid Scintillator Detectors publication-title: JINST doi: 10.1088/1748-0221/15/12/P12020 – volume: 7 year: 2012 ident: bbbbda660eb4381159bb90d2663791cf2 article-title: Measurement of the Quantum Efficiency of Hamamatsu R8520 Photomultipliers at Liquid Xenon Temperature publication-title: JINST doi: 10.1088/1748-0221/7/10/P10005 – start-page: xix year: 2022 ident: b0554c789bc1d2bf05c4db032c653c61a – volume: 541 start-page: 333 year: 2023 ident: b6612bcea4bd2e19ce231409a45f232ac article-title: Development of a gaseous Xe scintillator for particle identification of high-intensity and heavy ion beams publication-title: Nucl. Instrum. Meth. B doi: 10.1016/j.nimb.2023.05.039 – volume: 330 start-page: 1091 year: 2021 ident: bdaa9c0cd7e37f24e7a254d29c3672cf7 article-title: Development and testing of a Frisch-Grid Ionization Chamber for the measurement of low activity of alpha-particle emitters publication-title: Journal of Radioanalytical and Nuclear Chemistry doi: 10.1007/s10967-021-08007-0 – volume: 93 year: 2022 ident: b1cc09d3c2bb0b1e707bd7f68d71973f0 article-title: Beam particle identification and tagging of incompletely stripped heavy beams with HEIST publication-title: Rev. Sci. Instrum. doi: 10.1063/5.0068180 – volume: 13 start-page: 122 year: 2023 ident: bfc1a129398aed3eed08d8c145f1e281a article-title: A Model Surface for Calculating the Reflectance of Smooth and Rough Aluminum Layers in the Vacuum Ultraviolet Spectral Range publication-title: Coatings doi: 10.3390/coatings13010122 – volume: 129 year: 2024 ident: b7a8220306c6a774eeac20c1c3b7b457a article-title: Sequential motion optimization with short-term adaptive moment estimation for deep learning problems publication-title: Engineering Applications of Artificial Intelligence doi: 10.1016/j.engappai.2023.107593 – volume: 290 start-page: 10006 year: 2023 ident: b1964f295e3d695328857b3342eebc7c6 article-title: Upgrade to the focal-plane detector system of the S800 spectrograph at FRIB publication-title: EPJ Web Conf. doi: 10.1051/epjconf/202329010006 – volume: 538 start-page: 608 year: 2005 ident: b8fbad9e673cd1c8d6d4cfd8c20072960 article-title: High-rate particle identification of high-energy heavy ions using a tilted electrode gas ionization chamber publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2004.08.100 – volume: 15 year: 2020 ident: ba213df1b7c99ee1cb2aacf5d5ab9c547 article-title: Development of a novel MPGD-based drift chamber for the NSCL/FRIB S800 spectrometer publication-title: JINST doi: 10.1088/1748-0221/15/03/P03025 – volume: 171 start-page: 188 year: 2020 ident: b03c916996524992c5eb983bd7d499c7f article-title: Project repositories for machine learning with TensorFlow publication-title: Procedia Computer Science doi: 10.1016/j.procs.2020.04.020 – volume: 506 start-page: 250 year: 2003 ident: bee73ff6af1088b4c2f0493d8e6a1d3b9 article-title: GEANT4 - A Simulation Toolkit publication-title: Nucl. Instrum. Meth. A doi: 10.1016/S0168-9002(03)01368-8 – ident: bad93d924f669694b066b53eb0ec73626 – volume: 698 start-page: 26 year: 2013 ident: bf4bac0e8be4aa053e20b12277da74c52 article-title: Systematic study of particle quenching in organic scintillators publication-title: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment doi: 10.1016/j.nima.2012.09.041 – volume: 422 start-page: 291 year: 1999 ident: b9664a22905b3b6e95c446ae0c189f744 article-title: Focal plane detector for the S800 high-resolution spectrometer publication-title: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment doi: 10.1016/s0168-9002(98)00960-7 – volume: 394 start-page: 261 year: 1997 ident: b45b9526c9deec424b4e7ac28faa9bad0 article-title: Direct experimental determination of Frisch grid inefficiency in ionization chamber publication-title: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment doi: 10.1016/s0168-9002(97)00601-3 |
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| SubjectTerms | Algorithms Angular resolution Artificial neural networks Charged particles Computer simulation Data processing dE/dx detectors Detectors Efficiency Heavy ions Heavy-ion detectors Instrumentation and methods for heavy-ion reactions and fission studies Light sources Monte Carlo simulation Network analysis Neural networks Photons Scintillation Scintillation counters Tracking |
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| Title | Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study |
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