Journal article
The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector
- Abstract:
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.4MB, Terms of use)
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- Publisher copy:
- 10.1140/epjc/s10052-017-5481-6
Authors
- Publisher:
- Springer
- Journal:
- European Physical Journal C More from this journal
- Volume:
- 78
- Issue:
- 1
- Pages:
- 82
- Publication date:
- 2018-01-29
- Acceptance date:
- 2017-12-18
- DOI:
- EISSN:
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1434-6052
- ISSN:
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1434-6044
- Keywords:
- Pubs id:
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pubs:713679
- UUID:
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uuid:9b74d3a2-e9c9-4436-8807-f875d3cfbf72
- Local pid:
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pubs:713679
- Source identifiers:
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713679
- Deposit date:
-
2018-05-19
Terms of use
- Copyright holder:
- Barr et al
- Copyright date:
- 2018
- Notes:
- © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Licence:
- CC Attribution (CC BY)
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