Semantic segmentation for neutrino event reconstruction in NOvA
Lead Research Organisation:
University College London
Department Name: Physics and Astronomy
Abstract
The NOvA experiment studies the changes ("oscillations") of neutrinos as they travel 810km from an accelerator at Fermilab, outside Chicago, to a huge detector in northern Minnesota. By studying these oscillations we hope to learn which of the three neutrinos is the heaviest, and if there is any difference between the oscillations of neutrinos and their antiparticles. Such a difference could provide an explanation for the mystery that the universe is dominated by matter, rather than consisting of equal parts matter and antimatter. In 2018/2019 NOvA will operate a small replica detector that we will expose to beams of particles with well-controlled properties. This project is to apply modern deep-learning techniques to the large collected data sample to develop a new, more-powerful, neutrino interaction classifier, and potentially a new technique for efficiently simulating neutrino interactions.
People |
ORCID iD |
Christopher Backhouse (Primary Supervisor) | |
Kevin Mulder (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/P006736/1 | 30/09/2017 | 29/09/2024 | |||
2425058 | Studentship | ST/P006736/1 | 30/09/2020 | 29/09/2021 | Kevin Mulder |