Journal article
Electromagnetic shower reconstruction and energy validation with Michel electrons and π0 samples for the deep-learning-based analyses in MicroBooNE
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 1.9MB, Terms of use)
-
- Publisher copy:
- 10.1088/1748-0221/16/12/T12017
- Publisher:
- IOP Publishing
- Journal:
- Journal of Instrumentation More from this journal
- Volume:
- 16
- Article number:
- T12017
- Publication date:
- 2021-12-22
- Acceptance date:
- 2021-12-08
- DOI:
- EISSN:
-
1748-0221
- ISSN:
-
1748-0221
- Language:
-
English
- Keywords:
- Pubs id:
-
1231502
- Local pid:
-
pubs:1231502
- Deposit date:
-
2022-01-11
Terms of use
- Copyright holder:
- IOP Publishing Ltd and Sissa Medialab
- Copyright date:
- 2021
- Rights statement:
- © 2021 IOP Publishing Ltd and Sissa Medialab.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from IOP Publishing at: https://doi.org/10.1088/1748-0221/16/12/T12017
If you are the owner of this record, you can report an update to it here: Report update to this record