Detector signal characterization with a Bayesian network in XENONnT

Autor: XENON Collaboration, Aprile, E., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Angevaare, J. R., Antochi, V. C., Martin, D. Antón, Arneodo, F., Baudis, L., Baxter, A. L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Brookes, E. J., Brown, A., Bruenner, S., Bruno, G., Budnik, R., Bui, T. K., Cai, C., Cardoso, J. M. R., Cichon, D., Chavez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., Cussonneau, J. P., D'Andrea, V., Decowski, M. P., Di Gangi, P., Di Pede, S., Diglio, S., Eitel, K., Elykov, A., Farrell, S., Ferella, A. D., Ferrari, C., Fischer, H., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Rosso, A. Gallo, Galloway, M., Gao, F., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Howlett, J., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Joy, A., Kato, N., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koltman, G., Kopec, A., Kuger, F., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, D., Masson, E., Mastroianni, S., Messina, M., Miuchi, K., Mizukoshi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Palacio, J., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Pizzella, V., Plante, G., Pollmann, T. R., Qi, J., Qin, J., García, D. Ramírez, Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, D., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shockley, E., Silva, M., Simgen, H., Takeda, A., Tan, P. -L., Terliuk, A., Thers, D., Toschi, F., Trinchero, G., Tunnell, C., Tönnies, F., Valerius, K., Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wolf, T., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., Zhong, M., Zhu, T.

Publikováno v: Phys. Rev. D 108, 012016 (2023)

We developed a detector signal characterization model based on a Bayesian network trained on the waveform attributes generated by a dual-phase xenon time projection chamber. By performing inference on the model, we produced a quantitative metric of s

Externí odkaz: http://arxiv.org/abs/2304.05428

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Externí odkaz: https://hdl.handle.net/10216/162665

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