Novel approach for evaluating detector-related uncertainties in a LArTPC using MicroBooNE data
Novel approach for evaluating detector-related uncertainties in a LArTPC using MicroBooNE data
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DOI：
10.1140/epjc/s10052-022-10270-8
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发表时间：
2021-11
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影响因子：
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通讯作者：
M. C. P. Abratenko;Rui An;J. Anthony;L. Arellano;J. Asaadi;A. Ashkenazi;S. Balasubramanian;B. Baller;C. Barnes;G. Barr;V. Basque;L. Bathe-Peters;O. Rodrigues;S. Berkman;A. Bhanderi;A. Bhat;M. Bishai;A. Blake;T. Bolton;J. Book;L. Camilleri;D. Caratelli;I. C. Terrazas;F. Cavanna;G. Cerati;Y. Chen;D. Cianci;J. Conrad;M. Convery;L. Cooper-Troendle;J. I. Crespo-Anad'on;M. Tutto;S. Dennis;P. Detje;A. Devitt;R. Diurba;R. Dorrill;K. Duffy;S. Dytman;B. Eberly;A. Ereditato;J. Evans;R. Fine;G. A. F. Aguirre;R. Fitzpatrick;B. Fleming;N. Foppiani;D. Franco;A. Furmanski;D. Garcia-Gamez;S. Gardiner;G. Ge;S. Gollapinni;O. Goodwin;E. Gramellini;P. Green;H. Greenlee;W. Gu;R. Guenette;P. Guzowski;L. Hagaman;O. Hen;C. Hilgenberg;G. Horton-Smith;A. Hourlier;R. Itay;C. James;X. Ji;L. Jiang;J. Jo;R. Johnson;Y. Jwa;D. Kalra;N. Kamp;N. Kaneshige;G. Karagiorgi;W. Ketchum;M. Kirby;T. Kobilarcik;I. Kreslo;I. Lepetic;K. Li;Y. Li;K. Lin;B. Littlejohn;W. Louis;X. Luo;K. Manivannan;C. Mariani;D. Marsden;J. Marshall;D. A. Caicedo;K. Mason;A. Mastbaum;N. McConkey;V. Meddage;T. Mettler;K. Miller;J. Mills;K. Mistry;A. Mogan;T. Mohayai;J. Moon;M. Mooney;A. Moor;C. Moore;L. Lepin;J. Mousseau;M. Murphy;D. Naples;A. Navrer-Agasson;M. Nebot-Guinot;R. Neely;D. Newmark;J. Nowak;M. Nunes;O. Palamara;V. Paolone;A. Papadopoulou;Vicky Papavassiliou;S. Pate;N. Patel;A. Paudel;Z. Pavlovic;E. Piasetzky;I. Ponce-Pinto;S. Prince;X. Qian;J. Raaf;V. Radeka;A. Rafique;M. Reggiani-Guzzo;L. Ren;L. Rice;L. Rochester;J. Rondon;M. Rosenberg;M. Ross-Lonergan;G. Scanavini;D. Schmitz;A. Schukraft;W. Seligman;M. Shaevitz;R. Sharankova;J. Shi;J. Sinclair;A. Smith;E. Snider;M. Soderberg;S. Soldner-Rembold;P. Spentzouris;J. Spitz;M. Stancari;J. John;T. Strauss;K. Sutton;S. Sword-Fehlberg;A. Szelc;W. Tang;K. Terao;C. Thorpe;D. Totani;M. Toups;Y. Tsai;M. Uchida;T. Usher;W. V. D. Pontseele;B. Viren;M. Weber;H. Wei;Z. Williams;S. Wolbers;T. Wongjirad;M. Wospakrik;K. Wresilo;N. Wright;W. Wu;E. Yandel;T. Yang;G. Yarbrough;L. Yates;H. Yu;G. Zeller;J. Zennamo;C. Zhang
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文献类型：
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作者：
M. C. P. Abratenko;Rui An;J. Anthony;L. Arellano;J. Asaadi;A. Ashkenazi;S. Balasubramanian;B. Baller;C. Barnes;G. Barr;V. Basque;L. Bathe-Peters;O. Rodrigues;S. Berkman;A. Bhanderi;A. Bhat;M. Bishai;A. Blake;T. Bolton;J. Book;L. Camilleri;D. Caratelli;I. C. Terrazas;F. Cavanna;G. Cerati;Y. Chen;D. Cianci;J. Conrad;M. Convery;L. Cooper-Troendle;J. I. Crespo-Anad'on;M. Tutto;S. Dennis;P. Detje;A. Devitt;R. Diurba;R. Dorrill;K. Duffy;S. Dytman;B. Eberly;A. Ereditato;J. Evans;R. Fine;G. A. F. Aguirre;R. Fitzpatrick;B. Fleming;N. Foppiani;D. Franco;A. Furmanski;D. Garcia-Gamez;S. Gardiner;G. Ge;S. Gollapinni;O. Goodwin;E. Gramellini;P. Green;H. Greenlee;W. Gu;R. Guenette;P. Guzowski;L. Hagaman;O. Hen;C. Hilgenberg;G. Horton-Smith;A. Hourlier;R. Itay;C. James;X. Ji;L. Jiang;J. Jo;R. Johnson;Y. Jwa;D. Kalra;N. Kamp;N. Kaneshige;G. Karagiorgi;W. Ketchum;M. Kirby;T. Kobilarcik;I. Kreslo;I. Lepetic;K. Li;Y. Li;K. Lin;B. Littlejohn;W. Louis;X. Luo;K. Manivannan;C. Mariani;D. Marsden;J. Marshall;D. A. Caicedo;K. Mason;A. Mastbaum;N. McConkey;V. Meddage;T. Mettler;K. Miller;J. Mills;K. Mistry;A. Mogan;T. Mohayai;J. Moon;M. Mooney;A. Moor;C. Moore;L. Lepin;J. Mousseau;M. Murphy;D. Naples;A. Navrer-Agasson;M. Nebot-Guinot;R. Neely;D. Newmark;J. Nowak;M. Nunes;O. Palamara;V. Paolone;A. Papadopoulou;Vicky Papavassiliou;S. Pate;N. Patel;A. Paudel;Z. Pavlovic;E. Piasetzky;I. Ponce-Pinto;S. Prince;X. Qian;J. Raaf;V. Radeka;A. Rafique;M. Reggiani-Guzzo;L. Ren;L. Rice;L. Rochester;J. Rondon;M. Rosenberg;M. Ross-Lonergan;G. Scanavini;D. Schmitz;A. Schukraft;W. Seligman;M. Shaevitz;R. Sharankova;J. Shi;J. Sinclair;A. Smith;E. Snider;M. Soderberg;S. Soldner-Rembold;P. Spentzouris;J. Spitz;M. Stancari;J. John;T. Strauss;K. Sutton;S. Sword-Fehlberg;A. Szelc;W. Tang;K. Terao;C. Thorpe;D. Totani;M. Toups;Y. Tsai;M. Uchida;T. Usher;W. V. D. Pontseele;B. Viren;M. Weber;H. Wei;Z. Williams;S. Wolbers;T. Wongjirad;M. Wospakrik;K. Wresilo;N. Wright;W. Wu;E. Yandel;T. Yang;G. Yarbrough;L. Yates;H. Yu;G. Zeller;J. Zennamo;C. Zhang
当前和未来使用液氩时间投影室 (LArTPC) 进行精密中微子实验的主要挑战包括了解探测器效应和量化相关的系统不确定性。本文提出了一种评估和传播 LArTPC 探测器相关系统不确定性的新技术。该技术根据从 TPC 观察到的数据和模拟之间电离信号差异的参数化对模拟波形进行修改，同时对探测器模型的细节保持不敏感。然后使用修改来量化低级和高级重建量的系统差异。这种方法可以应用于未来的 LArTPC 探测器，例如 SBN 和 DUNE 中使用的探测器。
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.