0000000000200617
AUTHOR
G.l. Raselli
Volume IV The DUNE far detector single-phase technology
This document was prepared by the DUNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. The DUNE collaboration also acknowledges the international, national, and regional funding agencies supporting the institutions who have contributed to completing this Technical Design Report.
First results on ProtoDUNE-SP liquid argon time projection chamber performance from a beam test at the CERN Neutrino Platform
The ProtoDUNE-SP detector was constructed and operated on the CERN Neutrino Platform. We thank the CERN management for providing the infrastructure for this experiment and gratefully acknowledge the support of the CERN EP, BE, TE, EN, IT and IPT Departments for NP04/ProtoDUNE-SP. This documentwas prepared by theDUNEcollaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. This work was supported by CNPq, FAPERJ, FAPEG and FAPESP, Brazil; CFI, IPP and NSERC, Canada; CERN; MSMT, Czech Republi…
Neutrino interaction classification with a convolutional neural network in the DUNE far detector
The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino…
Non-destructive diagnostics of thin fissile layers
We have developed a non-destructive nuclear technique useful for the diagnostic of thin layers of fissile element. The method is based on the correlation between the fission fragment energy losses and the distortion of the energy spectrum of the alpha-particles emerging from the layer itself. We have also measured the sputtering rate of atoms from a fission layer which can be the cause of an important degradation in a working apparatus.
Volume I. Introduction to DUNE
Journal of Instrumentation 15(08), T08008 (1-228) (2020). doi:10.1088/1748-0221/15/08/T08008
Measurement of fission fragments energy loss
Abstract The mean energy of 252 Cf fission fragments emerging from an absorber and the determination of the capture rate in the absorber itself have been measured using two independent and complementary nuclear techniques. The results can be applied to the measurement of the energy self-absorption in a non-zero thickness source and can be used to validate simulation programs.
Volume III. DUNE far detector technical coordination
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay-these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the st…