Volume IV The DUNE far detector single-phase technology

2020

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

2020

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

2020

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…

Multiband variability studies and novel broadband SED modeling of Mrk 501 in 2009

2017

Astronomy and astrophysics 603, A31 (2017). doi:10.1051/0004-6361/201629540

Volume I. Introduction to DUNE

2020

Journal of Instrumentation 15(08), T08008 (1-228) (2020). doi:10.1088/1748-0221/15/08/T08008

SANS Investigations of Adsorption Mechanisms in Model Porous Silicas

2002

Colloidal zeolites and zeolite membranes

2002

The synthesis of zeolite membranes and thin films using the secondary growth process is briefly described. In this process colloidal zeolite particles (sols) are prepared hydrothermally and then subsequently deposited on substrates to produce uniform layers of controlled thickness. In order to optimise this process, an understanding of the nature of the sols and an insight into the structure of the consolidated layer so formed, is required. Such studies are illustrated here with silicalite and zeolite A. The formation and growth of silicalite sols has been investigated in situ by small angle neutron scattering (SANS). SANS measurements on sols at progressively higher concentrations have pro…

Volume III. DUNE far detector technical coordination

2020

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…

Sensitivity of the Cherenkov Telescope Array to a dark matter signal from the Galactic centre

2021

Full list of authors: Acharyya, A.; Adam, R.; Adams, C.; Agudo, I.; Aguirre-Santaella, A.; Alfaro, R.; Alfaro, J.; Alispach, C.; Aloisio, R.; Alves Batista, R.; Amati, L.; Ambrosi, G.; Angüner, E. O.; Antonelli, L. A.; Aramo, C.; Araudo, A.; Armstrong, T.; Arqueros, F.; Asano, K.; Ascasíbar, Y. Ashley, M.; Balazs, C.; Ballester, O.; Baquero Larriva, A.; Barbosa Martins, V.; Barkov, M.; Barres de Almeida, U.; Barrio, J. A.; Bastieri, D.; Becerra, J.; Beck, G.; Becker Tjus, J.; Benbow, W.; Benito, M.; Berge, D.; Bernardini, E.; Bernlöhr, K.; Berti, A.; Bertucci, B.; Beshley, V.; Biasuzzi, B.; Biland, A.; Bissaldi, E.; Biteau, J.; Blanch, O.; Blazek, J.; Bocchino, F.; Boisson, C.; Bonneau Arbe…