Development of an optimised event reconstruction for the Deep Underground Neutrino Experiment using machine learning and a multi-algorithm approach
Lead Research Organisation:
University of Warwick
Department Name: Physics
Abstract
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People |
ORCID iD |
John Marshall (Primary Supervisor) | |
Mousam Rai (Student) |
Publications

Abi B
(2020)
Long-baseline neutrino oscillation physics potential of the DUNE experiment DUNE Collaboration
in The European Physical Journal C

Abi B
(2020)
Volume IV. The DUNE far detector single-phase technology
in Journal of Instrumentation

Abi B
(2021)
Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment: DUNE Collaboration.
in The European physical journal. C, Particles and fields

Abi B
(2020)
Neutrino interaction classification with a convolutional neural network in the DUNE far detector
in Physical Review D

Abi B
(2020)
First results on ProtoDUNE-SP liquid argon time projection chamber performance from a beam test at the CERN Neutrino Platform
in Journal of Instrumentation

Abi B
(2020)
Volume III. DUNE far detector technical coordination
in Journal of Instrumentation

Abi B
(2020)
Volume I. Introduction to DUNE
in Journal of Instrumentation

Abi B
(2021)
Supernova neutrino burst detection with the Deep Underground Neutrino Experiment DUNE Collaboration
in The European Physical Journal C
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/S505857/1 | 30/09/2018 | 21/03/2023 | |||
2108560 | Studentship | ST/S505857/1 | 30/09/2018 | 21/03/2023 | Mousam Rai |