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, L.; Caratelli, D.; Fernandez, R.; Cavanna, F.; Cerati, G.; Chen, H.; Chen, Y.; Church, E.; Cianci, D.; Cohen, E.; Collin, G.; Conrad, J.; Convery, M.; Cooper-Troendle, L.; Crespo-Anadon, J.; Del Tutto, M.; Devitt, D.; Diaz, A.; Dytman, S.; Eberly, B.; Ereditato, A.; Sanchez, L.; Esquivel, J.; Evans, J.; Fadeeva, A.; Fleming, B.; Foreman, W.; Furmanski, A.; Garcia-Gamez, D.; Garvey, G.; Genty, V.; Goeldi, D.; Gollapinni, 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, G.; Hourlier, A.; Huang, E.; James, C.; de Vries, J.; Jiang, L.; Johnson, R.; Joshi, J.; Jostlein, H.; Jwa, Y.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Li, Y.; Lister, A.; Littlejohn, B.; Lockwitz, S.; Lorca, D.; Louis, W.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Marcocci, S.; Mariani, C.; Marshall, J.; Martinez Caicedo, D.; Mastbaum, A.; Meddage, V.; Mettler, T.; Miceli, T.; Mills, G.; Mogan, A.; Moon, J.; Mooney, M.; Moore, C.; Mousseau, J.; Murphy, M.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Pandey, V.; Paolone, V.; Papadopoulou, A.; Papavassiliou, V.; Pate, S.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J.; Rafique, A.; Rochester, L.; Ross-Lonergan, M.; von Rohr, C.; Russell, B.; Schmitz, D.; Schukraft, A.; Seligman, W.; Shaevitz, M.; Sinclair, J.; Smith, A.; Snider, E.; Soderberg, M.; Soeldner-Rembold, S.; Soleti, S.; Spentzouris, P.; Spitz, J.; John, J.; Strauss, T.; Sutton, K.; Sword-Fehlberg, S.; Szelc, A.; Tagg, N.; Tang, W.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R.; Viren, B.; Weber, M.; Wei, H.; Wickremasinghe, D.; Wierman, K.; Williams, Z.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yarbrough, G.; Yates, L.; Zeller, G.; Zennamo, J.; Zhang, C.

doi:10.1140/epjc/s10052-019-6742-3

Comparison of nu(mu)-Ar multiplicity distributions observed by MicroBooNE to GENIE model predictions: MicroBooNE Collaboration

Atıf İçin Kopyala

Adams C., An R., Anthony J., Asaadi J., Auger M., Balasubramanian S., ...Daha Fazla

EUROPEAN PHYSICAL JOURNAL C, cilt.79, sa.3, 2019 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 79 Sayı: 3
Basım Tarihi: 2019
Doi Numarası: 10.1140/epjc/s10052-019-6742-3
Dergi Adı: EUROPEAN PHYSICAL JOURNAL C
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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.