학술논문
Novel Approach for Evaluating Detector-Related Uncertainties in a LArTPC Using MicroBooNE Data
Document Type
Working Paper
Author
MicroBooNE collaboration; 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.; Rodrigues, O. Benevides; Berkman, S.; Bhanderi, A.; Bhat, A.; Bishai, M.; Blake, A.; Bolton, T.; Book, J. Y.; Camilleri, L.; Caratelli, D.; Terrazas, I. Caro; 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.; Aguirre, G. A. Fiorentini; 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, C.; Marsden, D.; Marshall, J.; Caicedo, D. A. Martinez; 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.; Lepin, L. Mora; Mousseau, J.; Murphy, M.; 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.; Rondon, J. Rodriguez; 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.; John, J. St.; 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.
Source
Eur. Phys. J. C 82, 454 (2022)
Subject
Language
Abstract
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.
Comment: 14 pages, 12 figures, version accepted by EPJ C
Comment: 14 pages, 12 figures, version accepted by EPJ C