为超级卡米康德开发数据溢出保护系统,最大限度地利用近邻超新星数据

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-08-23 DOI:10.1093/ptep/ptae128
M Mori, K Abe, Y Hayato, K Hiraide, K Hosokawa, K Ieki, M Ikeda, J Kameda, Y Kanemura, R Kaneshima, Y Kashiwagi, Y Kataoka, S Miki, S Mine, M Miura, S Moriyama, Y Nakano, M Nakahata, S Nakayama, Y Noguchi, K Okamoto, K Sato, H Sekiya, H Shiba, K Shimizu, M Shiozawa, Y Sonoda, Y Suzuki, A Takeda, Y Takemoto, A Takenaka, H Tanaka, S Watanabe, T Yano, S Han, T Kajita, K Okumura, T Tashiro, T Tomiya, X Wang, S Yoshida, G D Megias, P Fernandez, L Labarga, N Ospina, B Zaldivar, B W Pointon, E Kearns, J L Raaf, L Wan, T Wester, J Bian, N J Griskevich, S Locke, M B Smy, H W Sobel, V Takhistov, A Yankelevich, J Hill, M C Jang, S H Lee, D H Moon, R G Park, B Bodur, K Scholberg, C W Walter, A Beauchêne, O Drapier, A Giampaolo, Th A Mueller, A D Santos, P Paganini, B Quilain, R Rogly, T Ishizuka, T Nakamura, J S Jang, J G Learned, K Choi, N Iovine, S Cao, L H V Anthony, D Martin, M Scott, A A Sztuc, Y Uchida, V Berardi, M G Catanesi, E Radicioni, N F Calabria, A Langella, L N Machado, G De Rosa, G Collazuol, F Iacob, M Lamoureux, M Mattiazzi, L Ludovici, M Gonin, L Perisse, G Pronost, C Fujisawa, Y Maekawa, Y Nishimura, R Okazaki, R Akutsu, M Friend, T Hasegawa, T Ishida, T Kobayashi, M Jakkapu, T Matsubara, T Nakadaira, K Nakamura, Y Oyama, K Sakashita, T Sekiguchi, T Tsukamoto, N Bhuiyan, G T Burton, R Edwards, F Di Lodovico, J Gao, A Goldsack, T Katori, J Migenda, R M Ramsden, Z Xie, S Zsoldos, Y Kotsar, H Ozaki, A T Suzuki, Y Takagi, Y Takeuchi, H Zhong, C Bronner, J Feng, J R Hu, Z Hu, M Kawaune, T Kikawa, F LiCheng, T Nakaya, R A Wendell, K Yasutome, S J Jenkins, N McCauley, P Mehta, A Tarant, Y Fukuda, Y Itow, H Menjo, K Ninomiya, Y Yoshioka, J Lagoda, S M Lakshmi, M Mandal, P Mijakowski, Y S Prabhu, J Zalipska, M Jia, J Jiang, C K Jung, W Shi, M J Wilking, C Yanagisawa, M Harada, Y Hino, H Ishino, H Kitagawa, Y Koshio, F Nakanishi, S Sakai, T Tada, T Tano, G Barr, D Barrow, L Cook, S Samani, D Wark, A Holin, F Nova, S Jung, B S Yang, J Y Yang, J Yoo, J E P Fannon, L Kneale, M Malek, J M McElwee, M D Thiesse, L F Thompson, S Wilson, H Okazawa, S B Kim, E Kwon, J W Seo, I Yu, A K Ichikawa, K D Nakamura, S Tairafune, K Nishijima, A Eguchi, K Nakagiri, Y Nakajima, S Shima, N Taniuchi, E Watanabe, M Yokoyama, P de Perio, S Fujita, K Martens, K M Tsui, M R Vagins, C J Valls, J Xia, M Kuze, S Izumiyama, M Ishitsuka, H Ito, T Kinoshita, R Matsumoto, Y Ommura, N Shigeta, M Shinoki, T Suganuma, K Yamauchi, T Yoshida, J F Martin, H A Tanaka, T Towstego, R Gaur, V Gousy-Leblanc, M Hartz, A Konaka, X Li, N W Prouse, S Chen, B D Xu, B Zhang, M Posiadala-Zezula, S B Boyd, D Hadley, M Nicholson, M O’Flaherty, B Richards, A Ali, B Jamieson, S Amanai, Ll Marti, A Minamino, G Pintaudi, S Sano, S Suzuki, K Wada
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We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead time less than 1 ms, and does not influence ordinary operations. 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引用次数: 0

摘要

来自非常近的超新星(如参宿四)的中微子预计会在超级卡莫坎德(SK)的 10 秒钟内产生超过 1 千万个事件。在如此大的事件发生率下,SK 模数转换板(QBEE)的缓冲器将溢出,导致数据随机丢失,而这些数据对于了解超新星爆炸机制的动态至关重要。为了解决这个问题,我们开发了两个新的 DAQ 模块,以帮助观测非常邻近的超新星。其中第一个模块,即 SN 模块,旨在仅保存超新星爆发期间被击中的 PMT 的数量;第二个模块,即 Veto 模块,根据 SN 模块提供的信息,对高频率中微子事件进行预缩放,以防止 QBEE 溢出。在发生非常邻近的超新星时,这些模块允许 SK 利用 QBEE 和 SN 模块数据重建中微子事件率从开始到结束的时间演变。本文介绍了这些模块的开发和测试情况,以及对使用闪烁激光二极管生成的类似超新星数据的分析。我们证明了Veto模块成功地防止了类贝特宙超新星的DAQ溢出以及新模块的长期稳定性。在正常运行过程中,我们发现 "Veto "模块每月会发出几次 DAQ vetos,总死机时间小于 1 毫秒,不会影响正常运行。此外,利用模拟数据,我们发现距离 800 pc 以上的超新星会触发 Veto 模块,导致观测到的中微子数据预缩放。
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Development of a Data Overflow Protection System for Super-Kamiokande to Maximize Data from Nearby Supernovae
Neutrinos from very nearby supernovae, such as Betelgeuse, are expected to generate more than ten million events over 10 s in Super-Kamokande (SK). At such large event rates, the buffers of the SK analog-to-digital conversion board (QBEE) will overflow, causing random loss of data that is critical for understanding the dynamics of the supernova explosion mechanism. In order to solve this problem, two new DAQ modules were developed to aid in the observation of very nearby supernovae. The first of these, the SN module, is designed to save only the number of hit PMTs during a supernova burst and the second, the Veto module, prescales the high rate neutrino events to prevent the QBEE from overflowing based on information from the SN module. In the event of a very nearby supernova, these modules allow SK to reconstruct the time evolution of the neutrino event rate from beginning to end using both QBEE and SN module data. This paper presents the development and testing of these modules together with an analysis of supernova-like data generated with a flashing laser diode. We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead time less than 1 ms, and does not influence ordinary operations. Additionally, using simulation data we find that supernovae closer than 800 pc will trigger Veto module resulting in a prescaling of the observed neutrino data.
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