[en] 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 800 MeV, using an exposure corresponding to 5.0 $\times <!--\; ??\; -->$ 10${}^{19}$ 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. (orig.)

[en] Muon tomography is a technique based on the observation of the absorption of muons in matter, as the ordinary radiography does using X-rays. The interaction of cosmic rays with the atmosphere produce Extensive Air Showers, which provide an abundant source of muons. These particles can be used for multiple applications on muon tomography, in particular, to study the internal structure of different volcanoes edifices. It is necessary in any muon tomography experiment a particle detector that has the capability to be sensitive to muon interactions. Here we report a brief description of the first steps towards a complete design of a prototype particle detector to perform muon tomography in harsh conditions encountered in the surroundings of the Galeras Volcano. The mechanical design and fabrication processes of the supporting structure of the muon detector prototype, and first steps towards a future detector simulations on GEANT4 are described in this work. (paper)

[en] The MINERvA experiment is designed to perform precision studies of neutrino-nucleus scattering using ν_μ and ν^¯_μ neutrinos incident at 1–20 GeV in the NuMI beam at Fermilab. This article presents a detailed description of the MINERvA detector and describes the ex situ and in situ techniques employed to characterize the detector and monitor its performance. The detector is composed of a finely segmented scintillator-based inner tracking region surrounded by electromagnetic and hadronic sampling calorimetry. The upstream portion of the detector includes planes of graphite, iron and lead interleaved between tracking planes to facilitate the study of nuclear effects in neutrino interactions. Observations concerning the detector response over sustained periods of running are reported. The detector design and methods of operation have relevance to future neutrino experiments in which segmented scintillator tracking is utilized

[en] The MINERvA collaboration operated a scaled-down replica of thesolid scintillator tracking and sampling calorimeter regions of the MINERvA detector in a hadron test beam at the Fermilab Test Beam Facility. This paper reports measurements with samples of protons, pions, and electrons from 0.35 to 2.0 GeV/c momentum. The calorimetric response to protons, pions, and electrons is obtained from these data. A measurement of the parameter in Birks' law and an estimate of the tracking efficiency are extracted from the proton sample. Overall the data are well described by a Geant4-based Monte Carlo simulation of the detector and particle interactions with agreements better than 4% for the calorimetric response, though some features of the data are not precisely modeled. These measurements are used to tune the MINERvA detector simulation and evaluate systematic uncertainties in support of the MINERvA neutrino cross-section measurement program

[en] 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. (orig.)