Browsing by Author "An, R."

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    Comparison of nu(mu)-Ar multiplicity distributions observed by MicroBooNE to GENIE model predictions: MicroBooNE Collaboration
    Adams, C.; An, R.; Anthony, J.; Asaadi, J.; 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, Leslie; Caratelli, D.; Castillo Fernandez, R.; Cavanna, F.; Cerati, G.; Chen, H.; Chen, Y.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, Janet M.; Convery, M.; Cooper-Troendle, L.; Crespo-Anadon, J. I.; Del Tutto, M.; Devitt, D.; Diaz, A.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Evans, J. J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Golapinni, S.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Guzowski, P.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, Glenn A.; Hourlier, A.; Huang, E-C; James, C.; Jan de Vries, J.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Jwa, Y-J; Kaleko, D.; Karagiorgi, Georgia S.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Marcocci, S.; Mariani, Camillo; Marshall, J.; Martinez Caicedo, D. A.; Mastbaum, A.; Meddage, V.; Mettler, T.; Miceli, T.; Mills, G. B.; Mogan, A.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murphy, M.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Pandey, V.; Paolone, V.; Papadopoulou, A.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Ross-Lonergan, M.; von Rohr, C. Rudolph; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, Marjorie Hansen; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, Joshua; St John, J.; Strauss, T.; Sutton, K.; Sword-Fehlberg, S.; Szelc, A. M.; Tagg, N.; Tang, W.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y. T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wei, H.; Wickremasinghe, D. A.; Wierman, K.; Williams, Z.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yarbrough, G.; Yates, L. E.; Zeller, Geralyn P.; Zennamo, J.; Zhang, C. (2019-03-18)
    We measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab. We evaluate three neutrino interaction models based on the widely used GENIE event generator using these observables. The measurement uses a data set consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2016 with the Fermilab Booster Neutrino Beam, which has an average neutrino energy of MeV, using an exposure corresponding to 5.0x1019 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to separate neutrino interactions from cosmic ray background events. We find that GENIE models consistently describe the shapes of a large number of kinematic distributions for fixed observed multiplicity.
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    Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber
    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.; Bagby, L.; Baller, B.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, Leslie; Caratelli, D.; Carls, B.; Fernandez, R. C.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, Janet M.; Convery, M.; Crespo-Anadon, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garvey, G. T.; Genty, V.; Goeldi, D.; Golapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, Glenn A.; James, C.; de Vries, J. J.; Jen, C. M.; Jiang, L.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, Georgia S.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, Camillo; Marshall, J.; Caicedo, D. A. M.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. R.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, Marjorie Hansen; Sinclair, J.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, Joshua; St John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y. T.; Tufanli, S.; Usher, T.; de Water, R. G. V.; Viren, B.; Weber, M.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Zeller, Geralyn P.; Zennamo, J.; Zhang, C. (IOP, 2017-03-01)
    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.
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    Design and construction of the MicroBooNE Cosmic Ray Tagger system
    Adams, C.; Collaboration, Microboone; 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, Leslie; Caratelli, D.; Terrazas, I. Caro; Carr, Rachel E.; Castillo Fernandez, R.; Cavanna, F.; Cerati, G.; Chen, Y.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, Janet M.; Convery, M.; Cooper-Troendle, L.; Crespo-Anadon, J. I.; Del Tutto, M.; Devitt, D.; Diaz, A.; Duffy, K.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Evans, J. J.; Fadeeva, A. A.; Fitzpatrick, R. S.; Fleming, B. T.; Franco, D.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinniz, 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, Glenn A.; Hourlier, A.; Huang, E-C; James, C.; Jan de Vries, J.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Jwa, Y-J; Karagiorgi, Georgia S.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Marcocci, S.; Mariani, Camillo; Marshall, J.; Martin-Albo, J.; Martinez Caicedo, D. A.; Mastbaum, A.; Meddage, V.; Mettler, T.; Mills, G. B.; Mistry, K.; Mogan, A.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murphy, M.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Pandey, V.; Paolone, V.; Papadopoulou, A.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Ross-Lonergan, M.; von Rohr, C. Rudolph; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, Marjorie Hansen; Sharankova, R.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, Joshua; St John, J.; Strauss, T.; Sutton, K.; Sword-Fehlberg, S.; Szelc, A. M.; Tagg, N.; Tang, W.; Terao, K.; Thomson, M.; Thornton, R. T.; Toups, M.; Tsai, Y. T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wei, H.; Wickremasinghe, D. A.; Wierman, K.; Williams, Z.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yarbrough, G.; Yates, L. E.; Zeller, Geralyn P.; Zennameh, J.; Zhang, C. (2019-04)
    The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking.
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    Design and construction of the MicroBooNE detector
    Acciarri, R.; Adams, C.; An, R.; Aparicio, A.; Aponte, S.; Asaadi, J.; Auger, M.; Ayoub, N.; Bagby, L.; Baller, B.; Barger, R.; Barr, G.; Bass, M.; Bay, F.; Biery, K.; Bishai, M.; Blake, A.; Bocean, V.; Boehnlein, D.; Bogert, V. D.; Bolton, T.; Bugel, L.; Callahan, C.; Camilleri, Leslie; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chappa, S.; Chen, H.; Chen, K.; Chi, C. Y.; Chiu, C. S.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, Janet M.; Convery, M.; Cornele, J.; Cowan, P.; Crespo-Anadon, J. I.; Crutcher, G.; Darve, C.; Davis, R.; Del Tutto, M.; Devitt, D.; Duffin, S.; Dytman, S.; Eberly, B.; Ereditato, A.; Erickson, D.; Escudero Sanchez, L.; Esquivel, J.; Farooq, S.; Farrell, J.; Featherston, D.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Genty, V.; Geynisman, M.; Goeldi, D.; Goff, B.; Golapinni, S.; Graf, N.; Gramellini, E.; Green, J.; Greene, A.; Greenlee, H.; Griffin, T.; Grosso, R.; Guenette, R.; Hackenburg, A.; Haenni, R.; Hamilton, P.; Healey, P.; Hen, O.; Henderson, E.; Hewes, J.; Hill, C.; Hill, K.; Himes, L.; Ho, J.; Horton-Smith, Glenn A.; Huffman, D.; Ignarra, C. M.; James, C.; James, E.; Jan de Vries, J.; Jaskierny, W.; Jen, C. M.; Jiang, L.; Johnson, B.; Johnson, M.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Kalousis, L. N.; Karagiorgi, Georgia S.; Katori, T.; Kellogg, P.; Ketchum, W.; Kilmer, J.; King, B.; Kirby, B.; Kirby, M.; Klein, E.; Kobilarcik, T.; Kreslo, I.; Krull, R.; Kubinski, R.; Lange, G.; Lanni, F.; Lathrop, A.; Laube, A.; Leeg, W. M.; Li, Y.; Lissauer, D.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Lukhanin, G.; Luethi, M.; Lundberg, B.; Luo, X.; Mahler, G.; Majoros, I.; Makowiecki, D.; Marchionni, A.; Mariani, Camillo; Markley, D.; Marshall, J.; Martinez Caicedo, D. A.; McDonald, K. T.; McKee, D.; McLean, A.; Mead, J.; Meddage, V.; Miceli, T.; Mills, G. B.; Miner, W.; Moon, J.; Mooney, M.; Moore, C. D.; Moss, Z.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Norris, B.; Norton, N.; Nowak, J.; O'Boyle, M.; Olszanowski, T.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Pelkey, R.; Phipps, M.; Pordes, S.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Radeka, V.; Rafique, A.; Rameika, R.; Rebel, B.; Rechenmacher, R.; Rescia, S.; Rochester, L.; von Rohr, C. R.; Ruga, A.; Russell, B.; Sanders, R.; Sands, W. R.; Sarychev, M.; Schmitz, D. W.; Schukraft, A.; Scott, R.; Seligman, W.; Shaevitz, Marjorie Hansen; Shoun, M.; Sinclair, J.; Sippach, W.; Smidt, T.; Smith, A.; Snider, E. L.; Soderberg, M.; Solano-Gonzalez, M.; Söldner-Rembold, S.; Soleti, S. R.; Sondericker, J.; Spentzouris, P.; Spitz, Joshua; St John, J.; Strauss, T.; Sutton, K.; Szelc, A. M.; Taheri, K.; Tagg, N.; Tatum, K.; Teng, J.; Terao, K.; Thomson, M.; Thorn, C.; Tiliman, J.; Toups, M.; Tsai, Y. T.; Tufanli, S.; Usher, T.; Utes, M.; Van de Water, R. G.; Vendetta, C.; Vergani, S.; Voirin, E.; Voirin, J.; Viren, B.; Watkins, P.; Weber, M.; Wester, T.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Wu, K. C.; Yang, T.; Yu, B.; Zeller, Geralyn P.; Zennamo, J.; Zhang, C.; Zuckerbrot, M. (IOP, 2017-02-01)
    This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported.
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    Novel approach for evaluating detector-related uncertainties in a LArTPC using MicroBooNE data
    Abratenko, P.; An, R.; Anthony, J.; Arellano, L.; Asaadi, J.; Ashkenazi, A.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Basque, V.; Bathe-Peters, L.; Benevides Rodrigues, O.; Berkman, S.; Bhanderi, A.; Bhat, A.; Bishai, M.; Blake, A.; Bolton, T.; Book, J. Y.; Camilleri, L.; Caratelli, D.; Caro Terrazas, I.; Cavanna, F.; Cerati, G.; Chen, Y.; Cianci, D.; Conrad, J. M.; Convery, M.; Cooper-Troendle, L.; Crespo-Anadón, J. I.; Del Tutto, M.; Dennis, S. R.; Detje, P.; Devitt, A.; Diurba, R.; Dorrill, R.; Duffy, K.; Dytman, S.; Eberly, B.; Ereditato, A.; Evans, J. J.; Fine, R.; Fiorentini Aguirre, G. A.; Fitzpatrick, R. S.; Fleming, B. T.; Foppiani, N.; Franco, D.; Furmanski, A. P.; Garcia-Gamez, D.; Gardiner, S.; Ge, G.; Gollapinni, S.; Goodwin, O.; Gramellini, E.; Green, P.; Greenlee, H.; Gu, W.; Guenette, R.; Guzowski, P.; Hagaman, L.; Hen, O.; Hilgenberg, C.; Horton-Smith, G. A.; Hourlier, A.; Itay, R.; James, C.; Ji, X.; Jiang, L.; Jo, J. H.; Johnson, R. A.; Jwa, Y.-J.; Kalra, D.; Kamp, N.; Kaneshige, N.; Karagiorgi, G.; Ketchum, W.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Lepetic, I.; Li, K.; Li, Y.; Lin, K.; Littlejohn, B. R.; Louis, W. C.; Luo, X.; Manivannan, K.; Mariani, Camillo; Marsden, D.; Marshall, J.; Caicedo, D. A. M.; Mason, K.; Mastbaum, A.; McConkey, N.; Meddage, V.; Mettler, T.; Miller, K.; Mills, J.; Mistry, K.; Mogan, A.; Mohayai, T.; Moon, J.; Mooney, M.; Moor, A. F.; Moore, C. D.; Mora Lepin, L.; Mousseau, J.; Murphy, Matthew Douglas; Naples, D.; Navrer-Agasson, A.; Nebot-Guinot, M.; Neely, R. K.; Newmark, D. A.; Nowak, J.; Nunes, M.; Palamara, O.; Paolone, V.; Papadopoulou, A.; Papavassiliou, V.; Pate, S. F.; Patel, N.; Paudel, A.; Pavlovic, Z.; Piasetzky, E.; Ponce-Pinto, I. D.; Prince, S.; Qian, X.; Raaf, J. L.; Radeka, V.; Rafique, A.; Reggiani-Guzzo, M.; Ren, L.; Rice, L. C. J.; Rochester, L.; Rodriguez Rondon, J.; Rosenberg, M.; Ross-Lonergan, M.; Scanavini, G.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sharankova, R.; Shi, J.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Spentzouris, P.; Spitz, J.; Stancari, M.; St. John, J.; Strauss, T.; Sutton, K.; Sword-Fehlberg, S.; Szelc, A. M.; Tang, W.; Terao, K.; Thorpe, C.; Totani, D.; Toups, M.; Tsai, Y.-T.; Uchida, M. A.; Usher, T.; Van De Pontseele, W.; Viren, B.; Weber, M.; Wei, H.; Williams, Z.; Wolbers, S.; Wongjirad, T.; Wospakrik, M.; Wresilo, K.; Wright, N.; Wu, W.; Yandel, E.; Yang, T.; Yarbrough, G.; Yates, L. E.; Yu, H. W.; Zeller, G. P.; Zennamo, J.; Zhang, C. (2022-05-17)
    Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper presents a novel technique for assessing and propagating LArTPC detector-related systematic uncertainties. The technique makes modifications to simulation waveforms based on a parameterization of observed differences in ionization signals from the TPC between data and simulation, while remaining insensitive to the details of the detector model. The modifications are then used to quantify the systematic differences in low- and high-level reconstructed quantities. This approach could be applied to future LArTPC detectors, such as those used in SBN and DUNE.