Suppression of neutron background using deep neural network and Fourier frequency analysis at the KOTO experiment

被引：0
作者：
Tung, Y. -c. [1 ,2 ]
Li, J. [1 ,6 ]
Hsiung, Y. B. [2 ]
Lin, C. [2 ,7 ]
Nanjo, H. [3 ]
Nomura, T. [4 ]
Redeker, J. C. [1 ]
Shimizu, N. [3 ,8 ,9 ]
Shinohara, S. [5 ,10 ]
Shiomi, K. [4 ]
Wah, Y. W. [1 ]
Yamanaka, T. [3 ]
机构：
[1] Univ Chicago, Enr Fermi Inst, Chicago, IL 60637 USA
[2] Natl Taiwan Univ, Dept Phys, Taipei 10617, Taiwan
[3] Osaka Univ, Dept Phys, Toyonaka, Osaka 5600043, Japan
[4] High Energy Accelerator Res Org KEK, Inst Particle & Nucl Studies, Tsukuba, Ibaraki 3050801, Japan
[5] Kyoto Univ, Dept Phys, Kyoto 6068502, Japan
[6] Northwestern Univ, Dept Phys & Astron, Evanston, IL 60208 USA
[7] Univ Chicago, Enrico Fermi Inst, Chicago, IL 60637 USA
[8] Chiba Univ, Dept Phys, Chiba 2638522, Japan
[9] Chiba Univ, Int Ctr Hadron Astrophys, Chiba 2638522, Japan
[10] KEK, Tsukuba, Ibaraki 3050801, Japan
来源：
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT | 2024年 / 1059卷
基金：
日本学术振兴会;
关键词：
Rare kaon decay; Convolutional neural network; Deep learning; Cluster shape discrimination; Pulse shape discrimination; Fourier frequency analysis;
D O I：
10.1016/j.nima.2023.169010
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
We present two analysis techniques for distinguishing background events induced by neutrons from photon signal events in the search for the rare K-L(0)-+pi(0)v (v) over bar, decay at the J-PARC KOTO experiment. These techniques employed a deep convolutional neural network and Fourier frequency analysis to discriminate neutrons from photons, based on their variations in cluster shape and pulse shape, in the electromagnetic calorimeter made of undoped CsI. The results effectively suppressed the neutron background by a factor of 5.6 x 10(5), while maintaining the efficiency of K-L(0)-+ pi(0)v (v) over bar, at 70%.
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页数：8
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