Signal Separation from Thermal Neutrons in Electron–Neutron Detectors Using Convolutional Neural Nets in the ENDA Experiment
- 作者: Kurinov K.1, Kuleshov D.1, Lagutkina A.2, Sten'kin Y.1,2, Shchegolev O.1,2
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隶属关系:
- Institute for Nuclear Research, Russian Academy of Sciences
- Moscow Institute of Physics and Technology
- 期: 卷 163, 编号 4 (2023)
- 页面: 524-530
- 栏目: Articles
- URL: https://journals.rcsi.science/0044-4510/article/view/145390
- DOI: https://doi.org/10.31857/S0044451023040090
- EDN: https://elibrary.ru/LVJOHJ
- ID: 145390
如何引用文章
详细
The electron–neutron detector array (ENDA) is being created in China within the large high-altitude air shower observatory (LHAASO) project. The concept of the array is to simultaneously record the electromagnetic and hadronic components of extensive air showers (EAS) with EN detectors. To estimate the number of hadrons in an EAS, the array detectors record secondary thermal neutrons delayed relative to the shower front. Some of the delayed pulses are created by the simultaneous passage of several charged particles through the scintillator (the signal from one particle lies below the detection threshold) and by the photomultiplier noise. We propose a neutron pulse separation method for EN detectors using convolutional neural networks and make a comparison with the baseline method being currently applied at the installation.
作者简介
K. Kurinov
Institute for Nuclear Research, Russian Academy of Sciences
Email: kyrinov.ko@gmail.com
D. Kuleshov
Institute for Nuclear Research, Russian Academy of Sciences
Email: kyrinov.ko@gmail.com
117312, Moscow, Russia
A. Lagutkina
Moscow Institute of Physics and Technology
Email: kyrinov.ko@gmail.com
141701, Dolgoprudnyi, Moscow oblast, Russia
Yu. Sten'kin
Institute for Nuclear Research, Russian Academy of Sciences; Moscow Institute of Physics and Technology
Email: kyrinov.ko@gmail.com
117312, Moscow, Russia; 141701, Dolgoprudnyi, Moscow oblast, Russia
O. Shchegolev
Institute for Nuclear Research, Russian Academy of Sciences; Moscow Institute of Physics and Technology
编辑信件的主要联系方式.
Email: kyrinov.ko@gmail.com
117312, Moscow, Russia; 141701, Dolgoprudnyi, Moscow oblast, Russia
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