NOvA Reconstruction using Deep Learning [Slides]
- Indiana University, Bloomington, IN (United States)
The NOvA experiment has made measurements of the disappearance of νμ and the appearance of νe in the NuMI beam at Fermilab. Key to these measurements is the identification of the neutrino flavor and measurement of the neutrino energy, for which NOvA has implemented deep learning algorithms utilizing tools from the field of computer vision. These algorithms, first applied to NOvA's 2016 results, showed significant improvement over previous reconstruction methods. I will present NOvA's implementation of deep learning algorithms using convolutional neural networks for identification of event neutrino flavor and single particles used in the 2018 analysis.
- Research Organization:
- Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Contributing Organization:
- NOvA
- DOE Contract Number:
- AC02-07CH11359
- OSTI ID:
- 1462092
- Report Number(s):
- FERMILAB-SLIDES-18-075-ND; oai:inspirehep.net:1683078
- Resource Relation:
- Conference: New Perspectives 2018, Batavia, IL (United States), 18-19 Jun 2018
- Country of Publication:
- United States
- Language:
- English
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