Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

R. Acciarri; C. Adams; R. An; J. Asaadi; M. Auger; L. Bagby; B. Baller; G. Barr; M. Bass; F. Bay; M. Bishai; A. Blake; T. Bolton; L. Bugel; L. Camilleri; D. Caratelli; B. Carls; R. Castillo Fernandez; F. Cavanna; H. Chen; E. Church; D. Cianci; G. H. Collin; J. M. Conrad; M. Convery; J. I. Crespo-Anadón; M. Del Tutto; D. Devitt; S. Dytman; B. Eberly; A. Ereditato; L. Escudero Sanchez; J. Esquivel; B. T. Fleming; W. Foreman; A. P. Furmanski; G. T. Garvey; V. Genty; D. Goeldi; S. Gollapinni; N. Graf; E. Gramellini; H. Greenlee; R. Grosso; R. Guenette; A. Hackenburg; P. Hamilton; O. Hen; J. Hewes; C. Hill; J. Ho; G. Horton-Smith; C. James; J. Jan De Vries; C. M. Jen; L. Jiang; R. A. Johnson; B. J.P. Jones; J. Joshi; H. Jostlein; D. Kaleko; G. Karagiorgi; W. Ketchum; B. Kirby; M. Kirby; T. Kobilarcik; I. Kreslo; A. Laube; Y. Li; A. Lister; B. R. Littlejohn; S. Lockwitz; D. Lorca; W. C. Louis; M. Luethi; B. Lundberg; X. Luo; A. Marchionni; C. Mariani; J. Marshall; D. A.Martinez Caicedo; V. Meddage; T. Miceli; G. B. Mills; J. Moon; M. Mooney; C. D. Moore; J. Mousseau; R. Murrells; D. Naples; P. Nienaber; J. Nowak; O. Palamara; V. Paolone; V. Papavassiliou; S. F. Pate; Z. Pavlovic; D. Porzio; G. Pulliam; X. Qian; J. L. Raaf; A. Rafique; L. Rochester; C. Rudolf Von Rohr; B. Russell; D. W. Schmitz; A. Schukraft; W. Seligman; M. H. Shaevitz; J. Sinclair; E. L. Snider; M. Soderberg; S. Söldner-Rembold; S. R. Soleti; P. Spentzouris; J. Spitz; J. John; T. Strauss; A. M. Szelc; N. Tagg; K. Terao; M. Thomson; M. Toups; Y. T. Tsai; S. Tufanli; T. Usher; R. G. Van De Water; B. Viren; M. Weber; J. Weston; D. A. Wickremasinghe; S. Wolbers; T. Wongjirad; K. Woodruff; T. Yang; G. P. Zeller; J. Zennamo; C. Zhang

doi:10.1088/1748-0221/12/03/P03011

Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

R. Acciarri, C. Adams, R. An, J. Asaadi, M. Auger, L. Bagby, B. Baller, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. ChenE. Church, D. Cianci, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadón, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, C. James, J. Jan De Vries, C. M. Jen, L. Jiang, R. A. Johnson, B. J.P. Jones, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A.Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf Von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Söldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. T. Tsai, S. Tufanli, T. Usher, R. G. Van De Water, B. Viren, M. Weber, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, G. P. Zeller, J. Zennamo, C. Zhang

Department of Physics

Research output: Contribution to journal › Article › peer-review

79 Scopus citations

Abstract

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.

Original language	English (US)
Article number	P03011
Journal	Journal of Instrumentation
Volume	12
Issue number	3
DOIs	https://doi.org/10.1088/1748-0221/12/03/P03011
State	Published - Mar 14 2017

Keywords

Analysis and statistical methods
Image filtering
Particle identification methods
Time projection chambers

ASJC Scopus subject areas

Instrumentation
Mathematical Physics

Access to Document

10.1088/1748-0221/12/03/P03011

Cite this

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, L., Caratelli, D., Carls, B., Fernandez, R. C., Cavanna, F., ... Zhang, C. (2017). Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber. Journal of Instrumentation, 12(3), Article P03011. https://doi.org/10.1088/1748-0221/12/03/P03011

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, L, Caratelli, D, Carls, B, Fernandez, RC, Cavanna, F, Chen, H, Church, E, Cianci, D, Collin, GH, Conrad, JM, Convery, M, Crespo-Anadón, JI, Del Tutto, M, Devitt, D, Dytman, S, Eberly, B, Ereditato, A, Sanchez, LE, Esquivel, J, Fleming, BT, Foreman, W, Furmanski, AP, Garvey, GT, Genty, V, Goeldi, D, Gollapinni, 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, G, James, C, De Vries, JJ, Jen, CM, Jiang, L, Johnson, RA, Jones, BJP, Joshi, J, Jostlein, H, Kaleko, D, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Laube, A, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Mariani, C, Marshall, J, Caicedo, DAM, Meddage, V, Miceli, T, Mills, GB, Moon, J, Mooney, M, Moore, CD, Mousseau, J, Murrells, R, Naples, D, Nienaber, P, Nowak, J, Palamara, O, Paolone, V, Papavassiliou, V, Pate, SF, Pavlovic, Z, Porzio, D, Pulliam, G, Qian, X, Raaf, JL, Rafique, A, Rochester, L, Von Rohr, CR, Russell, B, Schmitz, DW, Schukraft, A, Seligman, W, Shaevitz, MH, Sinclair, J, Snider, EL, Soderberg, M, Söldner-Rembold, S, Soleti, SR, Spentzouris, P, Spitz, J, John, J, Strauss, T, Szelc, AM, Tagg, N, Terao, K, Thomson, M, Toups, M, Tsai, YT, Tufanli, S, Usher, T, Van De Water, RG, Viren, B, Weber, M, Weston, J, Wickremasinghe, DA, Wolbers, S, Wongjirad, T, Woodruff, K, Yang, T, Zeller, GP, Zennamo, J & Zhang, C 2017, 'Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber', Journal of Instrumentation, vol. 12, no. 3, P03011. https://doi.org/10.1088/1748-0221/12/03/P03011

@article{3400e995f2fd48e7a027d3b8d2423e51,

title = "Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber",

abstract = "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.",

keywords = "Analysis and statistical methods, Image filtering, Particle identification methods, Time projection chambers",

author = "R. Acciarri and C. Adams and R. An and J. Asaadi and M. Auger and L. Bagby and B. Baller and G. Barr and M. Bass and F. Bay and M. Bishai and A. Blake and T. Bolton and L. Bugel and L. Camilleri and D. Caratelli and B. Carls and Fernandez, {R. Castillo} and F. Cavanna and H. Chen and E. Church and D. Cianci and Collin, {G. H.} and Conrad, {J. M.} and M. Convery and Crespo-Anad{\'o}n, {J. I.} and {Del Tutto}, M. and D. Devitt and S. Dytman and B. Eberly and A. Ereditato and Sanchez, {L. Escudero} and J. Esquivel and Fleming, {B. T.} and W. Foreman and Furmanski, {A. P.} and Garvey, {G. T.} and V. Genty and D. Goeldi and S. Gollapinni and N. Graf and E. Gramellini and H. Greenlee and R. Grosso and R. Guenette and A. Hackenburg and P. Hamilton and O. Hen and J. Hewes and C. Hill and J. Ho and G. Horton-Smith and C. James and {De Vries}, {J. Jan} and Jen, {C. M.} and L. Jiang and Johnson, {R. A.} and Jones, {B. J.P.} and J. Joshi and H. Jostlein and D. Kaleko and G. Karagiorgi and W. Ketchum and B. Kirby and M. Kirby and T. Kobilarcik and I. Kreslo and A. Laube and Y. Li and A. Lister and Littlejohn, {B. R.} and S. Lockwitz and D. Lorca and Louis, {W. C.} and M. Luethi and B. Lundberg and X. Luo and A. Marchionni and C. Mariani and J. Marshall and Caicedo, {D. A.Martinez} and V. Meddage and T. Miceli and Mills, {G. B.} and J. Moon and M. Mooney and Moore, {C. D.} and J. Mousseau and R. Murrells and D. Naples and P. Nienaber and J. Nowak and O. Palamara and V. Paolone and V. Papavassiliou and Pate, {S. F.} and Z. Pavlovic and D. Porzio and G. Pulliam and X. Qian and Raaf, {J. L.} and A. Rafique and L. Rochester and {Von Rohr}, {C. Rudolf} and B. Russell and Schmitz, {D. W.} and A. Schukraft and W. Seligman and Shaevitz, {M. H.} and J. Sinclair and Snider, {E. L.} and M. Soderberg and S. S{\"o}ldner-Rembold and Soleti, {S. R.} and P. Spentzouris and J. Spitz and J. John and T. Strauss and Szelc, {A. M.} and N. Tagg and K. Terao and M. Thomson and M. Toups and Tsai, {Y. T.} and S. Tufanli and T. Usher and {Van De Water}, {R. G.} and B. Viren and M. Weber and J. Weston and Wickremasinghe, {D. A.} and S. Wolbers and T. Wongjirad and K. Woodruff and T. Yang and Zeller, {G. P.} and J. Zennamo and C. Zhang",

note = "Publisher Copyright: {\textcopyright} 2017 IOP Publishing Ltd and Sissa Medialab srl.",

year = "2017",

month = mar,

day = "14",

doi = "10.1088/1748-0221/12/03/P03011",

language = "English (US)",

volume = "12",

journal = "Journal of Instrumentation",

issn = "1748-0221",

publisher = "IOP Publishing Ltd.",

number = "3",

}

TY - JOUR

T1 - Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

AU - Acciarri, R.

AU - Adams, C.

AU - An, R.

AU - Asaadi, J.

AU - Auger, M.

AU - Bagby, L.

AU - Baller, B.

AU - Barr, G.

AU - Bass, M.

AU - Bay, F.

AU - Bishai, M.

AU - Blake, A.

AU - Bolton, T.

AU - Bugel, L.

AU - Camilleri, L.

AU - Caratelli, D.

AU - Carls, B.

AU - Fernandez, R. Castillo

AU - Cavanna, F.

AU - Chen, H.

AU - Church, E.

AU - Cianci, D.

AU - Collin, G. H.

AU - Conrad, J. M.

AU - Convery, M.

AU - Crespo-Anadón, J. I.

AU - Del Tutto, M.

AU - Devitt, D.

AU - Dytman, S.

AU - Eberly, B.

AU - Ereditato, A.

AU - Sanchez, L. Escudero

AU - Esquivel, J.

AU - Fleming, B. T.

AU - Foreman, W.

AU - Furmanski, A. P.

AU - Garvey, G. T.

AU - Genty, V.

AU - Goeldi, D.

AU - Gollapinni, S.

AU - Graf, N.

AU - Gramellini, E.

AU - Greenlee, H.

AU - Grosso, R.

AU - Guenette, R.

AU - Hackenburg, A.

AU - Hamilton, P.

AU - Hen, O.

AU - Hewes, J.

AU - Hill, C.

AU - Ho, J.

AU - Horton-Smith, G.

AU - James, C.

AU - De Vries, J. Jan

AU - Jen, C. M.

AU - Jiang, L.

AU - Johnson, R. A.

AU - Jones, B. J.P.

AU - Joshi, J.

AU - Jostlein, H.

AU - Kaleko, D.

AU - Karagiorgi, G.

AU - Ketchum, W.

AU - Kirby, B.

AU - Kirby, M.

AU - Kobilarcik, T.

AU - Kreslo, I.

AU - Laube, A.

AU - Li, Y.

AU - Lister, A.

AU - Littlejohn, B. R.

AU - Lockwitz, S.

AU - Lorca, D.

AU - Louis, W. C.

AU - Luethi, M.

AU - Lundberg, B.

AU - Luo, X.

AU - Marchionni, A.

AU - Mariani, C.

AU - Marshall, J.

AU - Caicedo, D. A.Martinez

AU - Meddage, V.

AU - Miceli, T.

AU - Mills, G. B.

AU - Moon, J.

AU - Mooney, M.

AU - Moore, C. D.

AU - Mousseau, J.

AU - Murrells, R.

AU - Naples, D.

AU - Nienaber, P.

AU - Nowak, J.

AU - Palamara, O.

AU - Paolone, V.

AU - Papavassiliou, V.

AU - Pate, S. F.

AU - Pavlovic, Z.

AU - Porzio, D.

AU - Pulliam, G.

AU - Qian, X.

AU - Raaf, J. L.

AU - Rafique, A.

AU - Rochester, L.

AU - Von Rohr, C. Rudolf

AU - Russell, B.

AU - Schmitz, D. W.

AU - Schukraft, A.

AU - Seligman, W.

AU - Shaevitz, M. H.

AU - Sinclair, J.

AU - Snider, E. L.

AU - Soderberg, M.

AU - Söldner-Rembold, S.

AU - Soleti, S. R.

AU - Spentzouris, P.

AU - Spitz, J.

AU - John, J.

AU - Strauss, T.

AU - Szelc, A. M.

AU - Tagg, N.

AU - Terao, K.

AU - Thomson, M.

AU - Toups, M.

AU - Tsai, Y. T.

AU - Tufanli, S.

AU - Usher, T.

AU - Van De Water, R. G.

AU - Viren, B.

AU - Weber, M.

AU - Weston, J.

AU - Wickremasinghe, D. A.

AU - Wolbers, S.

AU - Wongjirad, T.

AU - Woodruff, K.

AU - Yang, T.

AU - Zeller, G. P.

AU - Zennamo, J.

AU - Zhang, C.

PY - 2017/3/14

Y1 - 2017/3/14

N2 - 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.

AB - 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.

KW - Analysis and statistical methods

KW - Image filtering

KW - Particle identification methods

KW - Time projection chambers

UR - http://www.scopus.com/inward/record.url?scp=85017400383&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85017400383&partnerID=8YFLogxK

U2 - 10.1088/1748-0221/12/03/P03011

DO - 10.1088/1748-0221/12/03/P03011

M3 - Article

AN - SCOPUS:85017400383

SN - 1748-0221

VL - 12

JO - Journal of Instrumentation

JF - Journal of Instrumentation

IS - 3

M1 - P03011

ER -

Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this