تقرير
Suppression of Neutron Background using Deep Neural Network and Fourier Frequency Analysis at the KOTO Experiment
| العنوان: | Suppression of Neutron Background using Deep Neural Network and Fourier Frequency Analysis at the KOTO Experiment |
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| المؤلفون: | Tung, Y. -C., Li, J., Hsiung, Y. B., Lin, C., Nanjo, H., Nomura, T., Redeker, J. C., Shimizu, N., Shinohara, S., Shiomi, K., Wah, Y. W., Yamanaka, T. |
| سنة النشر: | 2023 |
| المجموعة: | High Energy Physics - Experiment Physics (Other) |
| مصطلحات موضوعية: | High Energy Physics - Experiment, Physics - Instrumentation and Detectors |
| الوصف: | We present two analysis techniques for distinguishing background events induced by neutrons from photon signal events in the search for the rare $K^0_L\rightarrow\pi^0\nu\bar{\nu}$ 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 $5.6\times10^5$, while maintaining the efficiency of $K^0_L\rightarrow\pi^0\nu\bar{\nu}$ at $70\%$. Comment: 7 pages, 10 figures |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2309.12063Test |
| رقم الانضمام: | edsarx.2309.12063 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |