We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector ...beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×1020 protons on target running in neutrino mode, and 4.9×1020 protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE’s detection thresholds, we obtain a flux averaged cross section of 2.0-1.7+2.2×10-40 cm2/Ar , where statistical and systematic uncertainties are combined.
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We report on a flux-integrated multi-differential measurement of charged-current muon neutrino scattering on argon with one muon and one proton in the final state using the Booster Neutrino Beam and ...MicroBooNE detector at Fermi National Accelerator Laboratory. The data are studied as a function of various kinematic imbalance variables and of a neutrino energy estimator, and are compared to a number of event generator predictions. We find that the measured cross sections in different phase-space regions are sensitive to nuclear effects. Our results provide precision data to test and improve the neutrino-nucleus interaction models needed to perform high-accuracy oscillation analyses. Specific regions of phase-space are identified where further model refinements are most needed.
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We present results of searches for vector and pseudoscalar bosonic super-weakly interacting massive particles (WIMPs), which are dark matter candidates with masses at the keV-scale, with the XENON100 ...experiment. XENON100 is a dual-phase xenon time projection chamber operated at the Laboratori Nazionali del Gran Sasso. A profile likelihood analysis of data with an exposure of 224.6 live days ×34 kg showed no evidence for a signal above the expected background. We thus obtain new and stringent upper limits in the (8–125) keV/c2 mass range, excluding couplings to electrons with coupling constants of gae>3×10−13 for pseudo-scalar and α′/α>2×10−28 for vector super-WIMPs, respectively. These limits are derived under the assumption that super-WIMPs constitute all of the dark matter in our galaxy.
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We present the first constraints on the spin-dependent, inelastic scattering cross section of weakly interacting massive particles (WIMPs) on nucleons from XENON100 data with an exposure of 7.64×103 ...kg·days. XENON100 is a dual-phase xenon time projection chamber with 62 kg of active mass, operated at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy and designed to search for nuclear recoils from WIMP-nucleus interactions. Here we explore inelastic scattering, where a transition to a low-lying excited nuclear state of Xe129 is induced. The experimental signature is a nuclear recoil observed together with the prompt deexcitation photon. We see no evidence for such inelastic WIMP-Xe129 interactions. A profile likelihood analysis allows us to set a 90% C.L. upper limit on the inelastic, spin-dependent WIMP-nucleon cross section of 3.3×10−38 cm2 at 100 GeV/c2. This is the most constraining result to date, and sets the pathway for an analysis of this interaction channel in upcoming, larger dual-phase xenon detectors.
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Abstract
An accurate and efficient event reconstruction is required
to realize the full scientific capability of liquid argon time
projection chambers (LArTPCs). The current and future neutrino
...experiments that rely on massive LArTPCs create a need for new ideas
and reconstruction approaches. Wire-Cell, proposed in recent years,
is a novel tomographic event reconstruction method for LArTPCs. The
Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time,
and geometry information to reconstruct a topology-agnostic 3D image
of the ionization electrons prior to pattern recognition. A second
novel method, the many-to-many charge-light matching, then pairs the
TPC charge activity to the detected scintillation light signal, thus
enabling a powerful rejection of cosmic-ray muons in the MicroBooNE
detector. A robust processing of the scintillation light signal and
an appropriate clustering of the reconstructed 3D image are
fundamental to this technique. In this paper, we describe the
principles and algorithms of these techniques and their successful
application in the MicroBooNE experiment. A quantitative evaluation
of the performance of these techniques is presented. Using these
techniques, a 95% efficient pre-selection of neutrino
charged-current events is achieved with a 30-fold reduction of
non-beam-coincident cosmic-ray muons, and about 80% of the selected
neutrino charged-current events are reconstructed with at least 70%
completeness and 80% purity.
Abstract
Wire-Cell is a 3D event reconstruction package for liquid
argon time projection chambers. Through geometry, time, and drifted
charge from multiple readout wire planes, 3D space points with
...associated charge are reconstructed prior to the pattern recognition
stage. Pattern recognition techniques, including track trajectory
and d
Q
/d
x
(ionization charge per unit length) fitting, 3D neutrino
vertex fitting, track and shower separation, particle-level
clustering, and particle identification are then applied on these 3D
space points as well as the original 2D projection measurements. A
deep neural network is developed to enhance the reconstruction of
the neutrino interaction vertex. Compared to traditional
algorithms, the deep neural network boosts the vertex efficiency by
a relative 30% for charged-current ν
e
interactions. This
pattern recognition achieves 80–90% reconstruction efficiencies
for primary leptons, after a 65.8% (72.9%) vertex efficiency for
charged-current ν
e
(ν
μ
) interactions. Based on the
resulting reconstructed particles and their kinematics, we also
achieve 15-20% energy reconstruction resolutions for
charged-current neutrino interactions.
For a large liquid-argon time-projection chamber (LArTPC) operating on or near the Earth’s surface to detect neutrino interactions, the rejection of cosmogenic background is a critical and ...challenging task because of the large cosmic-ray flux and the long drift time of the time-projection chamber. We introduce a superior cosmic background rejection procedure based on the Wire-Cell three-dimensional (3D) event reconstruction for LArTPCs. From an initial 1:20 000 neutrino to cosmic-ray background ratio, we demonstrate these tools on data from the MicroBooNE experiment and create a high-performance generic neutrino event selection with a cosmic contamination of 14.9% (9.7%) for a visible energy region greater than O(200) MeV. The neutrino interaction selection efficiency is 80.4% and 87.6% for inclusive νμ charged-current and νe charged-current interactions, respectively. Here, this significantly improved performance compared with existing reconstruction algorithms marks a major milestone toward reaching the scientific goals of LArTPC neutrino oscillation experiments operating near the Earth’s surface.
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We present the performance of a semantic segmentation network, SparseSSNet, that provides pixel-level classification of MicroBooNE data. The MicroBooNE experiment employs a liquid argon time ...projection chamber for the study of neutrino properties and interactions. SparseSSNet is a submanifold sparse convolutional neural network, which provides the initial machine learning based algorithm utilized in one of MicroBooNE's ν_e-appearance oscillation analyses. The network is trained to categorize pixels into five classes, which are re-classified into two classes more relevant to the current analysis. The output of SparseSSNet is a key input in further analysis steps. This technique, used for the first time in liquid argon time projection chambers data and is an improvement compared to a previously used convolutional neural network, both in accuracy and computing resource utilization. The accuracy achieved on the test sample is ≥99%. For full neutrino interaction simulations, the time for processing one image is ≈ 0.5 sec, the memory usage is at 1 GB level, which allows utilization of most typical CPU worker machine.
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We describe the purification of xenon from traces of the radioactive noble gas radon using a cryogenic distillation column. The distillation column was integrated into the gas purification loop of ...the XENON100 detector for online radon removal. This enabled us to significantly reduce the constant Rn-222 background originating from radon emanation. After inserting an auxiliary 222Rn emanation source in the gas loop, we determined a radon reduction factor of R > 27 (95% C.L.) for the distillation column by monitoring the Rn-222 activity concentration inside the XENON100 detector.
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