Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber
Instrumentation and Detectors
2023-02-17 v1 High Energy Physics - Experiment
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
Cite
@article{arxiv.1611.05531,
title = {Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber},
author = {MicroBooNE collaboration and 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 R. Castillo Fernandez and F. Cavanna and H. Chen and E. Church and D. Cianci and G. H. Collin and J. M. Conrad and M. Convery and J. I. Crespo-Anadón and M. Del Tutto and D. Devitt and S. Dytman and B. Eberly and A. Ereditato and L. Escudero Sanchez and J. Esquivel and B. T. Fleming and W. Foreman and A. P. Furmanski and G. T. Garvey 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 V Hewes and C. Hill and J. Ho and G. Horton-Smith and C. James and J. Jan de Vries and C. -M. Jen and L. Jiang and R. A. Johnson and B. J. P. Jones 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 B. R. Littlejohn and S. Lockwitz and D. Lorca and W. C. Louis and M. Luethi and B. Lundberg and X. Luo and A. Marchionni and C. Mariani and J. Marshall and D. A. Martinez Caicedo and V. Meddage and T. Miceli and G. B. Mills and J. Moon and M. Mooney and C. D. Moore 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 S. F. Pate and Z. Pavlovic and D. Porzio and G. Pulliam and X. Qian and J. L. Raaf and A. Rafique and L. Rochester and C. Rudolf von Rohr and B. Russell and D. W. Schmitz and A. Schukraft and W. Seligman and M. H. Shaevitz and J. Sinclair and E. L. Snider and M. Soderberg and S. Söldner-Rembold and S. R. Soleti and P. Spentzouris and J. Spitz and J. St. John and T. Strauss and A. M. Szelc and N. Tagg and K. Terao and M. Thomson and M. Toups and Y. -T. Tsai and S. Tufanli and T. Usher and R. G. Van de Water and B. Viren and M. Weber and J. Weston and D. A. Wickremasinghe and S. Wolbers and T. Wongjirad and K. Woodruff and T. Yang and G. P. Zeller and J. Zennamo and C. Zhang},
journal= {arXiv preprint arXiv:1611.05531},
year = {2023}
}