Label-free timing analysis of SiPM-based modularized detectors with physics-constrained deep learning

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成果类型：

期刊论文

作者：

Ai, Pengcheng*;Xiao, Le;Deng, Zhi;Wang, Yi;Sun, Xiangming;...

通讯作者：

Ai, Pengcheng;Xiao, L

作者机构：

[Xiao, Le; Ai, Pengcheng; Sun, Xiangming; Wang, Dong; Ai, PC; Xiao, L; Huang, Guangming] Cent China Normal Univ, Key Lab Quark & Lepton Phys MOE, PLAC, Wuhan 430079, Peoples R China.

[Xiao, Le; Ai, Pengcheng; Sun, Xiangming; Wang, Dong; Ai, PC; Xiao, L; Huang, Guangming] Hubei Prov Engn Res Ctr Silicon Pixel Chip & Detec, Wuhan 430079, Peoples R China.

[Wang, Yi; Li, Yulei; Ran, Xinchi; Deng, Zhi] Tsinghua Univ, Dept Engn Phys, Key Lab Particle & Radiat Imaging MOE, Beijing 100084, Peoples R China.

通讯机构：

[Ai, PC; Xiao, L ] C

Cent China Normal Univ, Key Lab Quark & Lepton Phys MOE, PLAC, Wuhan 430079, Peoples R China.

Hubei Prov Engn Res Ctr Silicon Pixel Chip & Detec, Wuhan 430079, Peoples R China.

语种：

英文

关键词：

Analog to digital conversion;Deep learning;High energy physics;Photomultipliers;Signal processing;Silicon;Silicon detectors;Timing circuits;Toys;Deep learning;Label free;Label-free loss function;Loss functions;Neural-networks;Nuclear detectors;Physical constraints;Pulse timing;Silicon photo multipliers (SiPM);Timing Analysis;Neural network models

期刊：

Machine Learning: Science and Technology

ISSN：

2632-2153

年：

2023

卷：

期：

页码：

045020

DOI：

10.1088/2632-2153/acfd09

基金类别：

This research is supported in part by the National Key Research and Development Program of China (under Grant Nos. 2020YFE0202001, 2022YFA1602103), in part by the National Natural Science Foundation of China (under Grant Nos. 12235006, 12075099, 11875146, U1932143), in part by the Fundamental Research Funds for the Central Universities (under Grant No. CCNU23XJ013) and in part by the China Postdoctoral Science Foundation (under Grant No. 2023M731244).

机构署名：

本校为第一且通讯机构

院系归属：

物理科学与技术学院

摘要：

Abstract Pulse timing is an important topic in nuclear instrumentation, with far-reaching applications from high energy physics to radiation imaging. While high-speed analog-to-digital converters become more and more developed and accessible, their potential uses and merits in nuclear detector signal processing are still uncertain, partially due to associated timing algorithms which are not fully understood and utilized. In this paper, we propose a novel method based on deep learning for timing analysis of modularized detectors without explici...

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Label-free timing analysis of SiPM-based modularized detectors with physics-constrained deep learning

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