skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

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

Journal Article · · Journal of Instrumentation
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; « less

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.

Research Organization:
Brookhaven National Lab. (BNL), Upton, NY (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Organization:
The MicroBooNE Collaboration; MicroBooNE
Grant/Contract Number:
SC0012704; AC02-07CH11359; AC02-76SF00515
OSTI ID:
1351727
Alternate ID(s):
OSTI ID: 1362054; OSTI ID: 1390716
Report Number(s):
BNL-113707-2017-JA; MICROBOONE-NOTE-1019-PUB; FERMILAB-PUB-16-538-ND; arXiv:1611.05531; R&D Project: PO-022; KA2201020; TRN: US1700609
Journal Information:
Journal of Instrumentation, Vol. 12, Issue 03; ISSN 1748-0221
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 49 works
Citation information provided by
Web of Science

References (7)

A convolutional neural network neutrino event classifier journal September 2016
Background rejection in NEXT using deep neural networks journal January 2017
ROOT — An object oriented data analysis framework journal April 1997
Geant4—a simulation toolkit
  • Agostinelli, S.; Allison, J.; Amako, K.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 506, Issue 3 https://doi.org/10.1016/S0168-9002(03)01368-8
journal July 2003
Neutrino flux prediction at MiniBooNE journal April 2009
The GENIE neutrino Monte Carlo generator
  • Andreopoulos, C.; Bell, A.; Bhattacharya, D.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 614, Issue 1 https://doi.org/10.1016/j.nima.2009.12.009
journal February 2010
Mastering the game of Go with deep neural networks and tree search journal January 2016

Cited By (7)

FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing journal October 2019
Machine learning at the energy and intensity frontiers of particle physics journal August 2018
Extensive deep neural networks for transferring small scale learning to large scale systems journal January 2019
Ionization electron signal processing in single phase LArTPCs. Part I. Algorithm Description and quantitative evaluation with MicroBooNE simulation journal July 2018
Timing and characterization of shaped pulses with MHz ADCs in a detector system: a comparative study and deep learning approach journal March 2019
Extensive deep neural networks for transferring small scale learning to large scale systems text January 2017
Ionization Electron Signal Processing in Single Phase LArTPCs I. Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation text January 2018

Similar Records

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber
Journal Article · Tue Mar 14 00:00:00 EDT 2017 · Journal of Instrumentation · OSTI ID:1351727
+135 more
Convolutional neural network for multiple particle identification in the MicroBooNE liquid argon time projection chamber
Journal Article · Fri May 14 00:00:00 EDT 2021 · Physical Review D · OSTI ID:1351727
+180 more
Scalable deep convolutional neural networks for sparse, locally dense liquid argon time projection chamber data
Journal Article · Fri Jul 10 00:00:00 EDT 2020 · Physical Review. D. · OSTI ID:1351727

Related Subjects

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
47 OTHER INSTRUMENTATION
MicroBooNE
detector
chamber
convolutional
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY