{"paper":{"title":"A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"hep-ex","authors_text":"A. Ashkenazi, A. Bhanderi, A. Bhat, A. Blake, A. Ereditato, A.F. Moor, A. Hourlier, A. Marchionni, A. Mastbaum, A. Mogan, A.M. Szelc, A. Navrer-Agasson, A. Papadopoulou, A. Paudel, A.P. Furmanski, A. Rafique, A. Schukraft, A. Smith, B. Baller, B. Eberly, B. Kirby, B.R. Littlejohn, B. Russell, B.T. Fleming, B. Viren, C. Barnes, C.D. Moore, C. James, C. Mariani, C.Thorpe, C. Zhang, D.A. Martinez Caicedo, D. Caratelli, D. Cianci, D. Devitt, D. Franco, D. Garcia-Gamez, D. Lorca, D. Marsden, D. Naples, D. Porzio, D.W. Schmitz, E. Church, E. Gramellini, E. Hall, E.L. Snider, E. Piasetzky, E. Yandel, F. Cavanna, G.A. Fiorentini Aguirre, G.A. Horton-Smith, G. Barr, G. Cerati, G. Ge, G. Karagiorgi, G.P. Zeller, G. Scanavini, G. Yarbrough, H.E. Rogers, H. Greenlee, H. Wei, I. Caro Terrazas, I. Kreslo, I. Lepetic, I. Ponce-Pinto, J. Anthony, J. Asaadi, J.H. Jo, J.I. Crespo-Anadon, J. Jan de Vries, J.J. Evans, J.L. Raaf, J. Marshall, J. Martin-Albo, J.M. Conrad, J. Mills, J. Moon, J. Mousseau, J. Nowak, J. Rodriguez Rondon, J. Sinclair, J. Spitz, J. St. John, J. Zennamo, K. Duffy, K. Li, K. Mason, K. Miller, K. Mistry, K. Sutton, K. Terao, L. Bathe-Peters, L. Camilleri, L. Cooper-Troendle, L. Domine, L. Escudero Sanchez, L.E. Yates, L. Hagaman, L. Jiang, L. Mora Lepin, L. Ren, L. Rochester, M. Alrashed, M.A. Uchida, M. Bishai, M. Convery, M. Del Tutto, M.H. Shaevitz, MicroBooNE collaboration: P. Abratenko, M. Kirby, M. Mooney, M. Murphy, M. Reggiani-Guzzo, M. Rosenberg, M. Ross-Lonergan, M. Soderberg, M. Stancari, M. Toups, M. Weber, M. Wospakrik, N. Foppiani, N. Kamp, N. Kaneshige, N. McConkey, N. Tagg, O. Benevides Rodrigues, O. Goodwin, O. Hen, O. Palamara, P. Green, P. Guzowski, P. Hamilton, P. Nienaber, P. Spentzouris, R.A. Johnson, R. An, R. Castillo Fernandez, R. Diurba, R. Dorrill, R. Guenette, R. Itay, R.K. Neely, R. LaZur, R.S. Fitzpatrick, R. Sharankova, S. Balasubramanian, S. Berkman, S. Dennis, S. Dytman, S.F. Pate, S. Gardiner, S. Gollapinni, S. Prince, S.R. Soleti, S. Soldner-Rembold, S. Sword-Fehlberg, S. Wolbers, T. Bolton, T. Kobilarcik, T. Mettler, T. Mohayai, T. Strauss, T. Usher, T. Wongjirad, T. Yang, V. Basque, V. Meddage, V. Paolone, V. Papavassiliou, V. Radeka, W.C. Louis, W. Gu, W. Ketchum, W. Seligman, W. Tang, W. Van De Pontseele, W. Wu, X. Ji, X. Luo, X. Qian, Y. Chen, Y.J. Jwa, Y. Li, Y.-T. Tsai, Z. Pavlovic, Z. Williams","submitted_at":"2020-10-16T22:27:12Z","abstract_excerpt":"We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the probabilities of $e^-$, $\\gamma$, $\\mu^-$, $\\pi^\\pm$, and protons in a single liquid argon time projection chamber (LArTPC) readout plane. The network extends the single particle identification network previously developed by MicroBooNE. MPID takes as input an image either cropped around a reconstructed interaction vertex or containing only activity connected to a reconstructed vertex, therefore relieving the tool fr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.08653","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2010.08653/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}