DUNE UK Production Project

Lead Research Organisation: University of Bristol
Department Name: Physics

Abstract

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Planned Impact

Please refer to the lead submission of this joint proposal.

Publications

10 25 50
publication icon
Abed Abud A (2022) Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network in The European Physical Journal C

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

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

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

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

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

publication icon
Abud A (2022) Low exposure long-baseline neutrino oscillation sensitivity of the DUNE experiment in Physical Review D

publication icon
Abud AA (2022) Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC. in The European physical journal. C, Particles and fields

publication icon
Barcock A (2023) Timing and synchronization of the DUNE neutrino detector in Journal of Instrumentation

publication icon
Cussans D (2020) Timing and synchronization of the DUNE neutrino detector in Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

 
Description Machine Learning Acceleration for Fast Triggers
Amount £24,639 (GBP)
Funding ID ST/W005565/1 
Organisation Science and Technologies Facilities Council (STFC) 
Sector Public
Country United Kingdom
Start 12/2021 
End 06/2022
 
Description Deep Underground Neutrino Experiment (DUNE) 
Organisation Fermilab - Fermi National Accelerator Laboratory
Department DUNE
Country United States 
Sector Public 
PI Contribution The Bristol team is contributing the detector synchronisation system for the DUNE far detector. Prototype hardware, firmware and software is currently under production and will be delivered to the collaboration for testing at CERN (NP04) this year. In addition, the Bristol team is developing firmware and software for trigger primitive generation in the far detector data acquisition system, as well as performing integration tests.
Collaborator Contribution The collaboration as a whole will construct and operate the DUNE near and far detectors.
Impact The publications listed under publications have all resulted from this collaboration.
Start Year 2018