Hlavná stránka > Cosmic Ray Background Removal With Deep Neural Networks in SBND |
Article | |
Report number | arXiv:2012.01301 ; FERMILAB-PUB-20-641-ND |
Title | Cosmic Ray Background Removal With Deep Neural Networks in SBND |
Related title | Cosmic Background Removal with Deep Neural Networks in SBND |
Author(s) |
Acciarri, R. (Fermilab) ; Adams, C. (Argonne) ; Andreopoulos, C. (Liverpool U. ; Rutherford) ; Asaadi, J. (Texas U., Arlington) ; Babicz, M. (CERN) ; Backhouse, C. (University Coll. London) ; Badgett, W. (Fermilab) ; Bagby, L. (Fermilab) ; Barker, D. (Sheffield U.) ; Basque, V. (Manchester U.) ; Bazetto, M.C. Q. (Campinas State U.) ; Betancourt, M. (Fermilab) ; Bhanderi, A. (Manchester U.) ; Bhat, A. (Syracuse U.) ; Bonifazi, C. (UFRJ, Rio de Janeiro) ; Brailsford, D. (Lancaster U.) ; Brandt, A.G. (Texas U., Arlington) ; Brooks, T. (Sheffield U.) ; Carneiro, M.F. (Brookhaven Natl. Lab.) ; Chen, Y. (Bern U.) ; Chen, H. (Brookhaven Natl. Lab.) ; Chisnall, G. (Sussex U.) ; Crespo-Anadón, J.I. (Madrid, CIEMAT) ; Cristaldo, E. (Asuncion Natl. U.) ; Cuesta, C. (Madrid, CIEMAT) ; de Icaza Astiz, I.L. (Sussex U.) ; De Roeck, A. (CERN) ; de Sa Pereira, G. (Liverpool U. ; Rutherford) ; Del Tutto, M. (Fermilab) ; Di Benedetto, V. (Fermilab) ; Ereditato, A. (Bern U.) ; Evans, J.J. (Manchester U.) ; Ezeribe, A.C. (Sheffield U.) ; Fitzpatrick, R.S. (Michigan U.) ; Fleming, B.T. (Yale U.) ; Foreman, W. (IIT, Chicago) ; Franco, D. (Yale U.) ; Furic, I. (Florida U.) ; Furmanski, A.P. (Minnesota U.) ; Gao, S. (Brookhaven Natl. Lab.) ; Garcia-Gamez, D. (CAFPE, Granada) ; Frandini, H. (Campinas State U.) ; Ge, G. (Columbia U.) ; Gil-Botella, I. (Madrid, CIEMAT) ; Gollapinni, S. (Los Alamos) ; Goodwin, O. (Manchester U.) ; Green, P. (Manchester U.) ; Griffith, W.C. (Sussex U.) ; Guenette, R. (Harvard U.) ; Guzowski, P. (Manchester U.) ; Ham, T. (Liverpool U.) ; Henzerling, J. (Liverpool U.) ; Holin, A. (University Coll. London) ; Howard, B. (Fermilab) ; Jones, R. S. (Liverpool U.) ; Kalra, D. (Columbia U.) ; Karagiorgi, G. (Columbia U.) ; Kashur, L. (Colorado State U.) ; Ketchum, W. (Fermilab) ; Kim, M.J. (Fermilab) ; Kudryavtsev, V.A. (Sheffield U.) ; Larkin, J. (Brookhaven Natl. Lab.) ; Lay, H. (Lancaster U.) ; Lepetic, I. (Rutgers U., Piscataway) ; Littlejohn, B.R. (IIT, Chicago) ; Louis, W.C. (Los Alamos) ; Machado, A. A. (U. Campinas) ; Malek, M. (Sheffield U.) ; Mardsen, D. (Manchester U.) ; Mariani, C. (Virginia Tech.) ; Marinho, F. (Sao Carlos Federal U.) ; Mastbaum, A. (Rutgers U., Piscataway) ; Mavrokoridis, K. (Liverpool U.) ; McConkey, N. (Manchester U.) ; Meddage, V. (Florida U.) ; Méndez, D.P. (Brookhaven Natl. Lab.) ; Mettler, T. (Bern U.) ; Mistry, K. (Manchester U.) ; Mogan, A. (U. Tennessee, Knoxville) ; Molina, J. (Asuncion Natl. U.) ; Mooney, M. (Colorado State U.) ; Mora, L. (Manchester U.) ; Moura, C.A. (ABC Federal U.) ; Mousseau, J. (U. Michigan, Ann Arbor) ; Navrer-Agasson, A. (Manchester U.) ; Nicolas-Arnaldos, F. J. (Granada U.) ; Nowak, J.A. (Lancaster U.) ; Palamara, O. (Fermilab) ; Pandey, V. (Florida U.) ; Pater, J. (Manchester U.) ; Paulucci, L. (ABC Federal U.) ; Pimentel, V.L. (Campinas State U.) ; Psihas, F. (Fermilab) ; Putnam, G. (Chicago U., EFI) ; Qian, X. (Brookhaven Natl. Lab.) ; Raguzin, E. (Brookhaven Natl. Lab.) ; Ray, H. (Florida U.) ; Reggiani-Guzzo, M. (Manchester U.) ; Rivera, D. (Pennsylvania U.) ; Roda, M. (Liverpool U.) ; Ross-Lonergan, M. (Columbia U.) ; Scanavini, G. (Yale U.) ; Scarff, A. (Sheffield U.) ; Schmitz, D.W. (Chicago U., EFI) ; Schukraft, A. (Fermilab) ; Segreto, E. (U. Campinas) ; Soares Nunes, M. (Syracuse U.) ; Soderberg, M. (Syracuse U.) ; Söldner-Rembold, S. (Manchester U.) ; Spitz, J. (Michigan U.) ; Spooner, N.J. C. (Sheffield U.) ; Stancari, M. (Fermilab) ; Stenico, G.V. (Campinas State U.) ; Szelc, A. (Manchester U.) ; Tang, W. (Tennessee U.) ; Tena Vidal, J. (Liverpool U.) ; Torretta, D. (Fermilab) ; Toups, M. (Fermilab) ; Touramanis, C. (Liverpool U.) ; Tripathi, M. (Florida U.) ; Tufanli, S. (CERN) ; Tyley, E. (Sheffield U.) ; Valdiviesso, G.A. (Alfenas Fed. U., Pocos de Caldas) ; Worcester, E. (Brookhaven Natl. Lab.) ; Worcester, M. (Brookhaven Natl. Lab.) ; Yarbrough, G. (U. Tennessee, Knoxville) ; Yu, J. (Texas U., Arlington) ; Zamorano, B. (Granada U.) ; Zennamo, J. (Fermilab) ; Zglam, A. (Sheffield U.) |
Publication | 2021-08-24 |
Imprint | 2020-12-02 |
Number of pages | 17 |
In: | Front. Artif. Intell. 4 (2021) 649917 |
DOI | 10.3389/frai.2021.649917 |
Subject category | physics.data-an ; Other Fields of Physics |
Abstract | In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons and other cosmic particles are incident on the detectors while a single neutrino-induced event is being recorded. In practice, this means that data from surface liquid argon time projection chambers will be dominated by cosmic particles, both as a source of event triggers and as the majority of the particle count in true neutrino-triggered events. In this work, we demonstrate a novel application of deep learning techniques to remove these background particles by applying semantic segmentation on full detector images from the SBND detector, the near detector in the Fermilab Short-Baseline Neutrino Program. We use this technique to identify, at single image-pixel level, whether recorded activity originated from cosmic particles or neutrino interactions. |
Copyright/License | preprint: (License: arXiv nonexclusive-distrib 1.0) publication: © 2021-2024 The authors (License: CC-BY-4.0) |