514 research outputs found
Development of a novel, windowless, amorphous selenium based photodetector for use in liquid noble detectors
Detection of the vacuum ultraviolet (VUV) scintillation light produced by
liquid noble elements is a central challenge in order to fully exploit the
available timing, topological, and calorimetric information in detectors
leveraging these media. In this paper, we characterize a novel, windowless
amorphous selenium based photodetector with direct sensitivity to VUV light. We
present here the manufacturing and experimental setup used to operate this
detector at low transport electric fields (2.7-5.2 V/m) and across a wide
range of temperatures (77K-290K). This work shows that the first
proof-of-principle device windowless amorphous selenium is robust under
cryogenic conditions, responsive to VUV light at cryogenic temperatures, and
preserves argon purity. These findings motivate a continued exploration of
amorphous selenium devices for simultaneous detection of scintillation light
and ionization charge in noble element detectors
Down syndrome and aberrant right subclavian artery
Down syndrome (DS) may be associated with various organ system disorders. Feeding problems are frequent in children with DS and may be caused by associated defects, including congenital heart defects, gastrointestinal defects, or endocrine disorders. In the absence of these associated conditions, feeding problems are often attributed to general hypotonia. However, an aberrant right subclavian artery (ARSA), a rare vascular anomaly and an unusual cause of problems with the passage of solid food through the esophagus, has recently been suggested to occur more frequently in patients with DS. This knowledge is of importance when evaluating feeding difficulties in patients with DS. Additional investigation for identifying an ARSA may be indicated in selected patients. Diagnostic techniques, such as transthoracic echocardiography, barium contrast esophagram, angiography, or computed tomography–angiography (CT) can be used in a diagnostic flow chart. The presence of ARSA is not synonymous to the cause of feeding problems in patients with DS and corrective surgery of this vascular anomaly should be restricted to selected cases
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The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.
The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies
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Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons
We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration
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Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC
We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics
Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber
We present several studies of convolutional neural networks applied to data
coming from the MicroBooNE detector, a liquid argon time projection chamber
(LArTPC). The algorithms studied include the classification of single particle
images, the localization of single particle and neutrino interactions in an
image, and the detection of a simulated neutrino event overlaid with cosmic ray
backgrounds taken from real detector data. These studies demonstrate the
potential of convolutional neural networks for particle identification or event
detection on simulated neutrino interactions. We also address technical issues
that arise when applying this technique to data from a large LArTPC at or near
ground level
The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector
The development and operation of Liquid-Argon Time-Projection Chambers for
neutrino physics has created a need for new approaches to pattern recognition
in order to fully exploit the imaging capabilities offered by this technology.
Whereas the human brain can excel at identifying features in the recorded
events, it is a significant challenge to develop an automated, algorithmic
solution. The Pandora Software Development Kit provides functionality to aid
the design and implementation of pattern-recognition algorithms. It promotes
the use of a multi-algorithm approach to pattern recognition, in which
individual algorithms each address a specific task in a particular topology.
Many tens of algorithms then carefully build up a picture of the event and,
together, provide a robust automated pattern-recognition solution. This paper
describes details of the chain of over one hundred Pandora algorithms and tools
used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE
detector. Metrics that assess the current pattern-recognition performance are
presented for simulated MicroBooNE events, using a selection of final-state
event topologies.Comment: Preprint to be submitted to The European Physical Journal
Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering
We discuss a technique for measuring a charged particle's momentum by means
of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time
projection chamber (LArTPC). This method does not require the full particle
ionization track to be contained inside of the detector volume as other track
momentum reconstruction methods do (range-based momentum reconstruction and
calorimetric momentum reconstruction). We motivate use of this technique,
describe a tuning of the underlying phenomenological formula, quantify its
performance on fully contained beam-neutrino-induced muon tracks both in
simulation and in data, and quantify its performance on exiting muon tracks in
simulation. Using simulation, we have shown that the standard Highland formula
should be re-tuned specifically for scattering in liquid argon, which
significantly improves the bias and resolution of the momentum measurement.
With the tuned formula, we find agreement between data and simulation for
contained tracks, with a small bias in the momentum reconstruction and with
resolutions that vary as a function of track length, improving from about 10%
for the shortest (one meter long) tracks to 5% for longer (several meter)
tracks. For simulated exiting muons with at least one meter of track contained,
we find a similarly small bias, and a resolution which is less than 15% for
muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first
estimate of the MCS momentum measurement capabilities of MicroBooNE for high
momentum exiting tracks
Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC
The low-noise operation of readout electronics in a liquid argon time
projection chamber (LArTPC) is critical to properly extract the distribution of
ionization charge deposited on the wire planes of the TPC, especially for the
induction planes. This paper describes the characteristics and mitigation of
the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase
LArTPC comprises two induction planes and one collection sense wire plane with
a total of 8256 wires. Current induced on each TPC wire is amplified and shaped
by custom low-power, low-noise ASICs immersed in the liquid argon. The
digitization of the signal waveform occurs outside the cryostat. Using data
from the first year of MicroBooNE operations, several excess noise sources in
the TPC were identified and mitigated. The residual equivalent noise charge
(ENC) after noise filtering varies with wire length and is found to be below
400 electrons for the longest wires (4.7 m). The response is consistent with
the cold electronics design expectations and is found to be stable with time
and uniform over the functioning channels. This noise level is significantly
lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure
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