使用主成分分析在丘比特中的脉冲形状歧视

论文标题

使用主成分分析在丘比特中的脉冲形状歧视

Pulse Shape Discrimination in CUPID-Mo using Principal Component Analysis

论文作者

Huang, R., Armengaud, E., Augier, C., Barabash, A. S., Bellini, F., Benato, G., Benoît, A., Beretta, M., Bergé, L., Billard, J., Borovlev, Yu. A., Bourgeois, Ch., Brudanin, V. B., Camus, P., Cardani, L., Casali, N., Cazes, A., Chapellier, M., Charlieux, F., de Combarieu, M., Dafinei, I., Danevich, F. A., De Jesus, M., Dixon, T., Dumoulin, L., Eitel, K., Ferri, F., Fujikawa, B. K., Gascon, J., Gironi, L., Giuliani, A., Grigorieva, V. D., Gros, M., Guerard, E., Helis, D. L., Huang, H. Z., Johnston, J., Juillard, A., Khalife, H., Kleifges, M., Kobychev, V. V., Kolomensky, Yu. G., Konovalov, S. I., Loaiza, P., Ma, L., Makarov, E. P., de Marcillac, P., Mariam, R., Marini, L., Marnieros, S., Misiak, D., Navick, X. -F., Nones, C., Olivieri, E., Ouellet, J. L., Pagnanini, L., Pari, P., Pattavina, L., Paul, B., Pavan, M., Peng, H., Pessina, G., Pirro, S., Poda, D. V., Polischuk, O. G., Previtali, E., Redon, Th., Rozov, S., Rusconi, C., Sanglard, V., Scarpaci, J. A., Schäffner, K., Schmidt, B., Shen, Y., Shlegel, V. N., Siebenborn, B., Singh, V., Tomei, C., Tretyak, V. I., Umatov, V. I., Vagneron, L., Velázquez, M., Weber, M., Welliver, B., Winslow, L., Xue, M., Yakushev, E., Zarytskyy, M. M., Zolotarova, A. S.

论文摘要

Cupid-Mo是一种低温检测器阵列，旨在寻找$^{100} $ MO的中微子双β衰减（$0νββ$）。它使用20个闪烁的$^{100} $ mo-mo-endriched li $ _2 $ _4 $ _4 $ bolometers带有GE灯检测器的仪表仪，以执行$α$背景的主动抑制，从而大大降低了$0νβ$信号区域的预期背景。结果，模仿正常信号的堆积事件和小探测器不稳定性成为不可忽略的潜在背景。这些类型的事件原则上可以根据其信号形状来消除，这与常规侧杆脉冲不同。我们表明，基于数据驱动的主成分分析方法能够在没有探测器响应模拟的情况下过滤这些异常事件。

CUPID-Mo is a cryogenic detector array designed to search for neutrinoless double-beta decay ($0νββ$) of $^{100}$Mo. It uses 20 scintillating $^{100}$Mo-enriched Li$_2$MoO$_4$ bolometers instrumented with Ge light detectors to perform active suppression of $α$ backgrounds, drastically reducing the expected background in the $0νββ$ signal region. As a result, pileup events and small detector instabilities that mimic normal signals become non-negligible potential backgrounds. These types of events can in principle be eliminated based on their signal shapes, which are different from those of regular bolometric pulses. We show that a purely data-driven principal component analysis based approach is able to filter out these anomalous events, without the aid of detector response simulations.

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