Search for Neutrinos in Coincidence with Gravitational Wave Events from the LIGO–Virgo O3a Observing Run with the Super-Kamiokande Detector
The Astrophysical Journal American Astronomical Society 918:2 (2021) 78
Authors:
K Abe, C Bronner, Y Hayato, M Ikeda, S Imaizumi, J Kameda, Y Kanemura, Y Kataoka, S Miki, M Miura, S Moriyama, Y Nagao, M Nakahata, S Nakayama, T Okada, K Okamoto, A Orii, G Pronost, H Sekiya, 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, R Wang, J Xia, GD Megias, D Bravo-Berguño, L Labarga, Ll Marti, B Zaldivar, BW Pointon, FDM Blaszczyk, E Kearns, JL Raaf, JL Stone, L Wan, T Wester, J Bian, NJ Griskevich, WR Kropp, S Locke, S Mine, MB Smy, HW Sobel, V Takhistov, P Weatherly, J Hill, JY Kim, IT Lim, RG Park, B Bodur, K Scholberg, CW Walter, L Bernard, A Coffani, O Drapier, S El Hedri, A Giampaolo, M Gonin, Th A Mueller, P Paganini, B Quilain, T Ishizuka, T Nakamura, JS Jang, JG Learned, LHV Anthony, DGR Martin, AA Sztuc, Y Uchida, V Berardi, MG Catanesi, E Radicioni, NF Calabria, LN Machado, G De Rosa, G Collazuol, F Iacob, M Lamoureux, N Ospina, L Ludovici, Y Maekawa, Y Nishimura, S Cao, M Friend, T Hasegawa, T Ishida, M Jakkapu, T Kobayashi, T Matsubara, T Nakadaira, K Nakamura, Y Oyama, K Sakashita, T Sekiguchi, T Tsukamoto, Y Kotsar, Y Nakano, H Ozaki, T Shiozawa, AT Suzuki, Y Takeuchi, S Yamamoto, A Ali, Y Ashida, J Feng, S Hirota, T Kikawa, M Mori, T Nakaya, RA Wendell, K Yasutome, P Fernandez, N McCauley, P Mehta, A Pritchard, KM Tsui, Y Fukuda, Y Itow, H Menjo, T Niwa, K Sato, M Tsukada, P Mijakowski, J Jiang, CK Jung, C Vilela, MJ Wilking, C Yanagisawa, K Hagiwara, M Harada, T Horai, H Ishino, S Ito, Y Koshio, H Kitagawa, W Ma, N Piplani, S Sakai, Y Kuno, G Barr, D Barrow, L Cook, A Goldsack, S Samani, C Simpson, D Wark, F Nova, T Boschi, F Di Lodovico, J Migenda, S Molina Sedgwick, M Taani, S Zsoldos, JY Yang, SJ Jenkins, M Malek, JM McElwee, O Stone, MD Thiesse, LF Thompson, H Okazawa, SB Kim, I Yu, K Nishijima, M Koshiba, K Iwamoto, Y Nakajima, N Ogawa, M Yokoyama, K Martens, MR Vagins, S Izumiyama, M Kuze, M Tanaka, T Yoshida, M Inomoto, M Ishitsuka, H Ito, R Matsumoto, K Ohta, M Shinoki, JF Martin, HA Tanaka, T Towstego, R Akutsu, M Hartz, A Konaka, P de Perio, NW Prouse, S Chen, BD Xu, M Posiadala-Zezula, D Hadley, B Richards, B Jamieson, J Walker, A Minamino, K Okamoto, G Pintaudi, S Sano, R Sasaki, AK Ichikawa, K NakamuraCalorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data
(2021)
Authors:
MicroBooNE collaboration, P Abratenko, R An, J Anthony, J Asaadi, A Ashkenazi, S Balasubramanian, B Baller, C Barnes, G Barr, V Basque, L Bathe-Peters, O Benevides Rodrigues, S Berkman, A Bhanderi, A Bhat, M Bishai, A Blake, T Bolton, L Camilleri, D Caratelli, I Caro Terrazas, R Castillo Fernandez, F Cavanna, G Cerati, Y Chen, E Church, D Cianci, JM Conrad, M Convery, L Cooper-Troendle, JI Crespo-Anadon, M Del Tutto, SR Dennis, D Devitt, R Diurba, R Dorrill, K Duffy, S Dytman, B Eberly, A Ereditato, JJ Evans, R Fine, GA Fiorentini Aguirre, RS Fitzpatrick, BT Fleming, N Foppiani, D Franco, AP Furmanski, D Garcia-Gamez, S Gardiner, G Ge, S Gollapinni, O Goodwin, E Gramellini, P Green, H Greenlee, W Gu, R Guenette, P Guzowski, L Hagaman, E Hall, P Hamilton, O Hen, GA Horton-Smith, A Hourlier, R Itay, C James, X Ji, L Jiang, JH Jo, RA Johnson, YJ Jwa, N Kamp, N Kaneshige, G Karagiorgi, W Ketchum, M Kirby, T Kobilarcik, I Kreslo, R LaZur, I Lepetic, K Li, Y Li, K Lin, BR Littlejohn, WC Louis, X Luo, K Manivannan, C Mariani, D Marsden, J Marshall, DA Martinez Caicedo, K Mason, A Mastbaum, N McConkey, V Meddage, T Mettler, K Miller, J Mills, K Mistry, T Mohayai, A Mogan, J Moon, M Mooney, AF Moor, CD Moore, L Mora Lepin, J Mousseau, M Murphy, D Naples, A Navrer-Agasson, RK Neely, J Nowak, M Nunes, O Palamara, V Paolone, A Papadopoulou, V Papavassiliou, SF Pate, A Paudel, Z Pavlovic, E Piasetzky, I Ponce-Pinto, S Prince, X Qian, JL Raaf, V Radeka, A Rafique, M Reggiani-Guzzo, L Ren, LCJ Rice, L Rochester, J Rodriguez Rondon, HE Rogers, M Rosenberg, M Ross-Lonergan, G Scanavini, DW Schmitz, A Schukraft, W Seligman, MH Shaevitz, R Sharankova, J Sinclair, A Smith, EL Snider, M Soderberg, S Soldner-Rembold, P Spentzouris, J Spitz, M Stancari, J St John, T Strauss, K Sutton, S Sword-Fehlberg, AM Szelc, N Tagg, W Tang, K Terao, C Thorpe, D Totani, M Toups, Y-T Tsai, MA Uchida, T Usher, W Van De Pontseele, B Viren, M Weber, H Wei, Z Williams, S Wolbers, T Wongjirad, M Wospakrik, N Wright, W Wu, E Yandel, T Yang, G Yarbrough, LE Yates, GP Zeller, J Zennamo, C ZhangCosmic Ray Background Removal With Deep Neural Networks in SBND
Frontiers in Artificial Intelligence Frontiers 4 (2021) 649917
Authors:
R Acciarri, C Adams, C Andreopoulos, J Asaadi, M Babicz, C Backhouse, W Badgett, L Bagby, D Barker, V Basque, MCQ Bazetto, M Betancourt, A Bhanderi, A Bhat, C Bonifazi, D Brailsford, AG Brandt, T Brooks, MF Carneiro, Y Chen, H Chen, G Chisnall, JI Crespo-Anadón, E Cristaldo, C Cuesta, IL de Icaza Astiz, A De Roeck, G de Sá Pereira, M Del Tutto, V Di Benedetto, A Ereditato, JJ Evans, AC Ezeribe, RS Fitzpatrick, BT Fleming, W Foreman, D Franco, I Furic, AP Furmanski, S Gao, D Garcia-Gamez, H Frandini, G Ge, I Gil-Botella, S Gollapinni, O Goodwin, P Green, WC Griffith, R Guenette, P Guzowski, T Ham, J Henzerling, A Holin, B Howard, RS Jones, D Kalra, G Karagiorgi, L Kashur, W Ketchum, MJ Kim, VA Kudryavtsev, J Larkin, H Lay, I Lepetic, BR Littlejohn, WC Louis, AA Machado, M Malek, D Mardsen, C Mariani, F Marinho, A Mastbaum, K Mavrokoridis, N McConkey, V Meddage, DP Méndez, T Mettler, K Mistry, A Mogan, J Molina, M Mooney, L Mora, CA Moura, J Mousseau, A Navrer-Agasson, FJ Nicolas-Arnaldos, JA Nowak, O Palamara, V Pandey, J Pater, L Paulucci, VL Pimentel, F Psihas, G Putnam, X Qian, E Raguzin, H Ray, M Reggiani-Guzzo, D Rivera, M Roda, M Ross-Lonergan, G Scanavini, A Scarff, DW Schmitz, A Schukraft, E Segreto, M Soares Nunes, M Soderberg, S Söldner-Rembold, J Spitz, NJC Spooner, M Stancari, GV Stenico, A Szelc, W Tang, J Tena Vidal, D Torretta, M Toups, C Touramanis, M Tripathi, S Tufanli, E Tyley, GA Valdiviesso, E Worcester, M Worcester, G Yarbrough, J Yu, B Zamorano, J Zennamo, A ZglamAn error analysis toolkit for binned counting experiments
EPJ Web of Conferences EDP Sciences 251 (2021)
Authors:
Ben Messerly, Rob Fine, Andrew Olivier, X-G Lu, Kang YangAbstract:
We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC
(2021)