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Title: The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.
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Publication Date:
Report Number(s):
FERMILAB-PUB-17-306-ND; arXiv:1708.03135; BNL-203308-2018-JAAM
Journal ID: ISSN 1434-6044; 1615469
Grant/Contract Number:
AC02-07CH11359; SC0012704; 654168
Type:
Published Article
Journal Name:
European Physical Journal. C, Particles and Fields
Additional Journal Information:
Journal Volume: 78; Journal Issue: 1; Journal ID: ISSN 1434-6044
Publisher:
Springer
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25); USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26)
Contributing Orgs:
MicroBooNE Collaboration
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; pattern recognition; event reconstruction; neutrino detectors
OSTI Identifier:
1418407
Alternate Identifier(s):
OSTI ID: 1398805; OSTI ID: 1424970