389 research outputs found
Measurement of Muon Neutrino Quasi-Elastic Scattering on Carbon
The observation of neutrino oscillations is clear evidence for physics beyond
the standard model. To make precise measurements of this phenomenon, neutrino
oscillation experiments, including MiniBooNE, require an accurate description
of neutrino charged current quasi-elastic (CCQE) cross sections to predict
signal samples. Using a high-statistics sample of muon neutrino CCQE events,
MiniBooNE finds that a simple Fermi gas model, with appropriate adjustments,
accurately characterizes the CCQE events observed in a carbon-based detector.
The extracted parameters include an effective axial mass, M_A^eff = 1.23+/-0.20
GeV, that describes the four-momentum dependence of the axial-vector form
factor of the nucleon; and a Pauli-suppression parameter, kappa =
1.019+/-0.011. Such a modified Fermi gas model may also be used by future
accelerator-based experiments measuring neutrino oscillations on nuclear
targets.Comment: 5 pages, 3 figure
Constraints from muon g-2 and LFV processes in the Higgs Triplet Model
Constraints from the muon anomalous magnetic dipole moment and lepton flavor
violating processes are translated into lower bounds on v_Delta*m_H++ in the
Higgs Triplet Model by considering correlations through the neutrino mass
matrix. The discrepancy of the sign of the contribution to the muon anomalous
magnetic dipole moment between the measurement and the prediction in the model
is clarified. It is shown that mu to e gamma, tau decays (especially, tau to mu
e e), and the muonium conversion can give a more stringent bound on
v_Delta*m_H++ than the bound from mu to eee which is expected naively to give
the most stringent one.Comment: 18 pages, 16 figure
Measurement of the \nu_\mu charged current \pi^+ to quasi-elastic cross section ratio on mineral oil in a 0.8 GeV neutrino beam
Using high statistics samples of charged current interactions,
MiniBooNE reports a measurement of the single charged pion production to
quasi-elastic cross section ratio on mineral oil (CH), both with and
without corrections for hadron re-interactions in the target nucleus. The
result is provided as a function of neutrino energy in the range 0.4 GeV 2.4 GeV with 11% precision in the region of highest statistics. The
results are consistent with previous measurements and the prediction from
historical neutrino calculations.Comment: 4 pages, 2 figure
A Proposal for a Three Detector Short-Baseline Neutrino Oscillation Program in the Fermilab Booster Neutrino Beam
A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors
located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This
new SBN Program will deliver a rich and compelling physics opportunity,
including the ability to resolve a class of experimental anomalies in neutrino
physics and to perform the most sensitive search to date for sterile neutrinos
at the eV mass-scale through both appearance and disappearance oscillation
channels. Using data sets of 6.6e20 protons on target (P.O.T.) in the LAr1-ND
and ICARUS T600 detectors plus 13.2e20 P.O.T. in the MicroBooNE detector, we
estimate that a search for muon neutrino to electron neutrino appearance can be
performed with ~5 sigma sensitivity for the LSND allowed (99% C.L.) parameter
region. In this proposal for the SBN Program, we describe the physics analysis,
the conceptual design of the LAr1-ND detector, the design and refurbishment of
the T600 detector, the necessary infrastructure required to execute the
program, and a possible reconfiguration of the BNB target and horn system to
improve its performance for oscillation searches.Comment: 209 pages, 129 figure
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
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
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
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