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  4. Electromagnetic shower reconstruction and energy validation with Michel electrons and π 0 samples for the deep-learning-based analyses in MicroBooNE

Electromagnetic shower reconstruction and energy validation with Michel electrons and π 0 samples for the deep-learning-based analyses in MicroBooNE

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sword-2022-04-21T15:01:41.original.xml (130 B)
Original SWORD entry document
Author(s)
Hen, Or
•
Conrad, Janet
Date Issued
2021
Journal
Journal of Instrumentation
Publisher
IOP Publishing
Citation
Hen, Or and Conrad, Janet. 2021. "Electromagnetic shower reconstruction and energy validation with Michel electrons and π 0 samples for the deep-learning-based analyses in MicroBooNE." Journal of Instrumentation, 16 (12).
Version
Original manuscript
Abstract
Abstract
This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two νμ-sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Further, the absolute shower energy scale is shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/142006
DOI of Published Version
https://doi.org/10.1088/1748-0221/16/12/T12017
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