We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino ...oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41} cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.
We present the results of a search for dark matter weakly interacting massive particles (WIMPs) in the mass range below 20 GeV/c^{2} using a target of low-radioactivity argon with a 6786.0 kg d ...exposure. The data were obtained using the DarkSide-50 apparatus at Laboratori Nazionali del Gran Sasso. The analysis is based on the ionization signal, for which the DarkSide-50 time projection chamber is fully efficient at 0.1 keVee. The observed rate in the detector at 0.5 keVee is about 1.5 event/keVee/kg/d and is almost entirely accounted for by known background sources. We obtain a 90% C.L. exclusion limit above 1.8 GeV/c^{2} for the spin-independent cross section of dark matter WIMPs on nucleons, extending the exclusion region for dark matter below previous limits in the range 1.8-6 GeV/c^{2}.
We report on the first measurement of flux-integrated single differential cross sections for charged-current (CC) muon neutrino (νμ) scattering on argon with a muon and a proton in the final state, ...Ar40 (νμ,μp)X. The measurement was carried out using the Booster Neutrino Beam at Fermi National Accelerator Laboratory and the MicroBooNE liquid argon time projection chamber detector with an exposure of 4.59×1019 protons on target. Events are selected to enhance the contribution of CC quasielastic (CCQE) interactions. The data are reported in terms of a total cross section as well as single differential cross sections in final state muon and proton kinematics. We measure the integrated per-nucleus CCQE-like cross section (i.e., for interactions leading to a muon, one proton, and no pions above detection threshold) of (4.93±0.76stat±1.29sys)×10−38 cm2, in good agreement with theoretical calculations. The single differential cross sections are also in overall good agreement with theoretical predictions, except at very forward muon scattering angles that correspond to low-momentum-transfer events.
We present an analysis of MicroBooNE data with a signature of one muon, no pions, and at least one proton above a momentum threshold of 300 MeV/c(CC0πNp). This is the first differential cross-section ...measurement of this topology in neutrino-argon interactions. We achieve a significantly lower proton momentum threshold than previous carbon and scintillator-based experiments. Using data collected from a total of approximately 1.6 × 1020 protons on target, we measure the muon neutrino cross section for the CC0πNp interaction channel in argon at MicroBooNE in the Booster Neutrino Beam which has a mean energy of around 800 MeV. We present the results from a data sample with estimated efficiency of 29% and purity of 76% as differential cross sections in five reconstructed variables: the muon momentum and polar angle, the leading proton momentum and polar angle, and the muon-proton opening angle. We include smearing matrices that can be used to "forward fold" theoretical predictions for comparison with these data. We compare the measured differential cross sections to a number of recent theory predictions demonstrating largely good agreement with this first-ever dataset on argon.
A liquid argon time projection chamber, constructed for the Argon Response to Ionization and Scintillation (ARIS) experiment, is exposed to the highly collimated and quasimonoenergetic LICORNE ...neutron beam at the Institut de Physique Nucléaire d’Orsay (IPNO) in order to study the scintillation response to nuclear and electronic recoils. An array of liquid scintillator detectors, arranged around the apparatus, tag scattered neutrons and select nuclear recoil energies in the 7, 120 keV energy range. The relative scintillation efficiency of nuclear recoils is measured to high precision at null field, and the ion-electron recombination probability is extracted for a range of applied electric fields. Single-scattered Compton electrons, produced by gammas emitted from the deexcitation of Li*7 in coincidence with the beam pulse, along with calibration gamma sources, are used to extract the recombination probability as a function of energy and electron drift field. The ARIS results are compared with three recombination probability parametrizations (Thomas-Imel, Doke-Birks, and PARIS), allowing for the definition of a fully comprehensive model of the liquid argon response to nuclear and electronic recoils down to the few-keV range. The constraints provided by ARIS to the liquid argon response at low energy allow the reduction of systematics affecting the sensitivity of dark matter search experiments based on liquid argon.
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 MicroBooNEs νe-appearance oscillation analyses. The network is trained to categorize pixels into five classes, which are reclassified 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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