Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber

We have developed a convolutional neural network that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. Th...

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Autores principales: Adams, C, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Auger, M, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Bass, M, Bay, F, Bhat, A, Bhattacharya, K, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Terrazas, IC, Carr, R, Fernandez, RC, Cavanna, F, Cerati, G, Chen, Y, Church, E, Cianci, D, Cohen, EO, Collin, GH, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadon, JI, Del Tutto, M, Devitt, D, Diaz, A, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Sanchez, LE, Esquivel, J, Evans, JJ, Fadeeva, AA, Fitzpatrick, RS, Fleming, BT, Franco, D, Furmanski, AP, Garcia-Gamez, D, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Greenlee, H, Grosso, R, Guenette, R, Guzowski, P, Hackenburg, A, Hamilton, P, Hen, O, Hewes, J, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, E-C, James, C, De Vries, JJ, Ji, X, Jiang, L, Johnson, RA, Joshi, J, Jostlein, H, Jwa, Y-J, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Caicedo, DAM, Mastbaum, A, Meddage, V, Mettler, T, Mistry, K, Mogan, A, Moon, J, Mooney, M, Moore, CD, Mousseau, J, Murphy, M, Murrells, R, Naples, D, Nienaber, P, Nowak, J, Palamara, O, Pandey, V, Paolone, V, Papadopoulou, A, Papavassiliou, V, Pate, SF, Pavlovic, Z, Piasetzky, E, Porzio, D, Pulliam, G, Qian, X, Raaf, JL, Rafique, A, Ren, L, Rochester, L, Ross-Lonergan, M, Von Rohr, CR, Russell, B, Scanavini, G, Schmitz, DW, Schukraft, A, Seligman, W, Shaevitz, MH, Sharankova, R, Sinclair, J, Smith, A, Snider, EL, Soderberg, M, Soldner-Rembold, S, Soleti, SR, Spentzouris, P, Spitz, J, St John, J, Strauss, T, Sutton, K, Sword-Fehlberg, S, Szelc, AM, Tagg, N, Tang, W, Terao, K, Thomson, M, Thornton, RT, Toups, M, Tsai, Y-T, Tufanli, S, Usher, T, Van De Pontseele, W, Van De Water, RG, Viren, B, Weber, M, Wei, H, Wickremasinghe, DA, Wierman, K, Williams, Z, Wolbers, S, Wongjirad, T, Woodruff, K, Yang, T, Yarbrough, G, Yates, LE, Zeller, GP, Zennamo, J, Zhang, C, Collaboration, M
Formato: Journal article
Publicado: American Physical Society 2019