9 research outputs found
Searching for solar KDAR with DUNE
The observation of 236 MeV muon neutrinos from kaon-decay-at-rest (KDAR)
originating in the core of the Sun would provide a unique signature of
dark matter annihilation. Since excellent angle and energy
reconstruction are necessary to detect this monoenergetic, directional
neutrino flux, DUNE with its vast volume and reconstruction
capabilities, is a promising candidate for a KDAR neutrino search. In
this work, we evaluate the proposed KDAR neutrino search strategies by
realistically modeling both neutrino-nucleus interactions and the
response of DUNE. We find that, although reconstruction of the neutrino
energy and direction is difficult with current techniques in the
relevant energy range, the superb energy resolution, angular resolution,
and particle identification offered by DUNE can still permit great
signal/background discrimination. Moreover, there are non-standard
scenarios in which searches at DUNE for KDAR in the Sun can probe dark
matter interactions
Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment DUNE Collaboration
The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool
for a variety of physics topics. The high-intensity proton beams provide
a large neutrino flux, sampled by a near detector system consisting of a
combination of capable precision detectors, and by the massive far
detector system located deep underground. This configuration sets up
DUNE as a machine for discovery, as it enables opportunities not only to
perform precision neutrino measurements that may uncover deviations from
the present three-flavor mixing paradigm, but also to discover new
particles and unveil new interactions and symmetries beyond those
predicted in the Standard Model (SM). Of the many potential beyond the
Standard Model (BSM) topics DUNE will probe, this paper presents a
selection of studies quantifying DUNE's sensitivities to sterile
neutrino mixing, heavy neutral leptons, non-standard interactions, CPT
symmetry violation, Lorentz invariance violation, neutrino trident
production, dark matter from both beam induced and cosmogenic sources,
baryon number violation, and other new physics topics that complement
those at high-energy colliders and significantly extend the present
reach
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 energies above 2 GeV. When considering all
electron neutrino and antineutrino interactions as signal, a selection
purity of 90% is achieved. These event selections are critical to
maximize the sensitivity of the experiment to CP-violating effects
Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC
The ProtoDUNE-SP detector is a single-phase liquid argon time projection
chamber (LArTPC) that was constructed and operated in the CERN North
Area at the end of the H4 beamline. This detector is a prototype for the
first far detector module of the Deep Underground Neutrino Experiment
(DUNE), which will be constructed at the Sandford Underground Research
Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector
incorporates full-size components as designed for DUNE and has an active
volume of 7 x 6 x 7.2 m3. The H4 beam delivers incident particles with
well-measured momenta and high-purity particle identification.
ProtoDUNE-SP's successful operation between 2018 and 2020 demonstrates
the effectiveness of the single-phase far detector design. This paper
describes the design, construction, assembly and operation of the
detector components
Delayed colorectal cancer care during covid-19 pandemic (decor-19). Global perspective from an international survey
Background
The widespread nature of coronavirus disease 2019 (COVID-19) has been unprecedented. We sought to analyze its global impact with a survey on colorectal cancer (CRC) care during the pandemic.
Methods
The impact of COVID-19 on preoperative assessment, elective surgery, and postoperative management of CRC patients was explored by a 35-item survey, which was distributed worldwide to members of surgical societies with an interest in CRC care. Respondents were divided into two comparator groups: 1) ‘delay’ group: CRC care affected by the pandemic; 2) ‘no delay’ group: unaltered CRC practice.
Results
A total of 1,051 respondents from 84 countries completed the survey. No substantial differences in demographics were found between the ‘delay’ (745, 70.9%) and ‘no delay’ (306, 29.1%) groups. Suspension of multidisciplinary team meetings, staff members quarantined or relocated to COVID-19 units, units fully dedicated to COVID-19 care, personal protective equipment not readily available were factors significantly associated to delays in endoscopy, radiology, surgery, histopathology and prolonged chemoradiation therapy-to-surgery intervals. In the ‘delay’ group, 48.9% of respondents reported a change in the initial surgical plan and 26.3% reported a shift from elective to urgent operations. Recovery of CRC care was associated with the status of the outbreak. Practicing in COVID-free units, no change in operative slots and staff members not relocated to COVID-19 units were statistically associated with unaltered CRC care in the ‘no delay’ group, while the geographical distribution was not.
Conclusions
Global changes in diagnostic and therapeutic CRC practices were evident. Changes were associated with differences in health-care delivery systems, hospital’s preparedness, resources availability, and local COVID-19 prevalence rather than geographical factors. Strategic planning is required to optimize CRC care