Using data collected with the D0 detector at the Fermilab Tevatron Collider, corresponding to 5.3 fb(-1) of integrated luminosity, we search for violation of Lorentz invariance by examining the ...ttover ¯ production cross section in lepton+jets final states. We quantify this violation using the standard-model extension framework, which predicts a dependence of the ttover ¯ production cross section on sidereal time as the orientation of the detector changes with the rotation of the Earth. Within this framework, we measure components of the matrices (c(Q))(μν33) and (c(U))(μν33) containing coefficients used to parametrize violation of Lorentz invariance in the top quark sector. Within uncertainties, these coefficients are found to be consistent with zero.
Abstract
In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to ...MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. This event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.
Abstract
is a near-surface liquid argon (LAr) time projection
chamber (TPC) located at Fermilab. We measure muons originating from
cosmic interactions in the atmosphere using both the charge
...collection and light readout detectors. The data is compared with
the cosmic-ray simulation. Agreement is found between the
observation, simulation and previous results. Furthermore, the
angular resolution of the reconstructed muons inside the TPC is
studied in simulation.
We measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab. We evaluate three ...neutrino interaction models based on the widely used GENIE event generator using these observables. The measurement uses a data set consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2016 with the Fermilab Booster Neutrino Beam, which has an average neutrino energy of 800MeV, using an exposure corresponding to 5.0×1019 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to separate neutrino interactions from cosmic ray background events. We find that GENIE models consistently describe the shapes of a large number of kinematic distributions for fixed observed multiplicity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab. We evaluate three ...neutrino interaction models based on the widely used GENIE event generator using these observables. The measurement uses a data set consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2016 with the Fermilab Booster Neutrino Beam, which has an average neutrino energy of Formula omitted, using an exposure corresponding to Formula omitted protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to separate neutrino interactions from cosmic ray background events. We find that GENIE models consistently describe the shapes of a large number of kinematic distributions for fixed observed multiplicity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The MicroBooNE liquid argon time projection chamber (LArTPC) has been taking data at Fermilab since 2015 collecting, in addition to neutrino beam, cosmic-ray muons. Results are presented on the ...reconstruction of Michel electrons produced by the decay at rest of cosmic-ray muons. Michel electrons are abundantly produced in the TPC, and given their well known energy spectrum can be used to study MicroBooNE's detector response to low-energy electrons (electrons with energies up to ~ 50 MeV). We describe the fully-automated algorithm developed to reconstruct Michel electrons, with which a sample of ~ 14,000 Michel electron candidates is obtained. Most of this article is dedicated to studying the impact of radiative photons produced by Michel electrons on the accuracy and resolution of their energy measurement. In this energy range, ionization and bremsstrahlung photon production contribute similarly to electron energy loss in argon, leading to a complex electron topology in the TPC. By profiling the performance of the reconstruction algorithm on simulation we show that the ability to identify and include energy deposited by radiative photons leads to a significant improvement in the energy measurement of low-energy electrons. The fractional energy resolution we measure improves from over 30% to ~ 20% when we attempt to include radiative photons in the reconstruction. These studies are relevant to a large number of analyses which aim to study neutrinos by measuring electrons produced by νe interactions over a broad energy range.
We present the results of the combination of searches for the standard model Higgs boson produced in association with a W or Z boson and decaying into bb using the data sample collected with the D0 ...detector in pp collisions at √s = 1.96 TeV at the Fermilab Tevatron Collider. We derive 95% C.L. upper limits on the Higgs boson cross section relative to the standard model prediction in the mass range 100 GeV ≤ M(H) ≤ 150 GeV, and we exclude Higgs bosons with masses smaller than 102 GeV at the 95% C.L. In the mass range 120 GeV ≤ M(H) ≤145 GeV, the data exhibit an excess above the background prediction with a global significance of 1.5 standard deviations, consistent with the expectation in the presence of a standard model Higgs boson.
This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction ...algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two νμ-sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Further, the absolute shower energy scale is shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.
In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons, and other cosmic particles are incident on the detectors while a single ...neutrino-induced event is being recorded. In practice, this means that data from surface liquid argon time projection chambers will be dominated by cosmic particles, both as a source of event triggers and as the majority of the particle count in true neutrino-triggered events. In this work, we demonstrate a novel application of deep learning techniques to remove these background particles by applying deep learning on full detector images from the SBND detector, the near detector in the Fermilab Short-Baseline Neutrino Program. We use this technique to identify, on a pixel-by-pixel level, whether recorded activity originated from cosmic particles or neutrino interactions.
We report the observation of a narrow structure, $X(5568)$, in the decay sequence $X(5568) \rightarrow B_s^0 \pi^{\pm}$, $B_s^0 \rightarrow J/\psi \phi$, $J/\psi\rightarrow \mu^+ \mu^-$, $\phi ...\rightarrow K^+K^-$. This is the first observation of a hadronic state with valence quarks of four different flavors. The mass and natural width of the new state are measured to be $m = 5567.8 \pm 2.9 {\rm \thinspace (stat)} ^{+0.9}_{-1.9} {\rm \thinspace (syst)}$ MeV/$c^2$ and $\Gamma = 21.9 \pm 6.4 {\rm \thinspace (stat)} ^{+5.0}_{-2.5} {\rm \thinspace (syst)} $ MeV/$c^2$, and the significance including look-elsewhere effect and systematic uncertainties is 5.1$\sigma$. The observation is based on$10.4~\rm{fb^{-1}}$ of $p \overline p $ collision data at $\sqrt{s}$ = 1.96 TeV collected by the D0 experiment at the Fermilab Tevatron collider.
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