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The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% formore » the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$$\pm 0.6$$% and 84.1$$\pm 0.6$$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.« less

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagneticmore » cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.« less

The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance.more » The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents.« less

The goal of the Mu2e experiment at Fermilab is to search for charged-lepton flavor violation by looking for neutrino-less muon to electron conversion in the field of the nucleus. The Mu2e experimental apparatus utilizes a complex magnetic field in the muon generation and momentum and charge selection process. Precise knowledge of the magnetic field is crucial. It is planned to map the solenoid field with calibrated 3D Hall probes up to 10^-5 accuracy. Here, this article describes a new design of a Hall probe calibration system that will be used to calibrate 3D Hall probes to better than 10^-5 accuracymore » for the Mu2e Solenoid Field Mapping System.« less

The Mu2e experiment at Fermilab plans to search for charged-lepton flavor violation by looking for neutrino-less muon to electron conversion in the field of the nucleus. A complex solenoid system and precise knowledge of its magnetic field play a major role in the experimental approach Mu2e has chosen. It is essential to map the solenoid field up to 10^-4 accuracy. This article describes the design of the Field Mapping System Mu2e will use to measure the magnetic field. Two different mechanical mapper systems, a survey based position determination of the in-house calibrated 3D Hall probes, a motion control system, andmore » a data acquisition and readout system are presented.« less

The NOvA Neutrino Experiment has built a one of a kind self-supporting plastic structure, potentially the largest ever built. The PVC structure serves as a neutrino detector and is composed of 28 individual blocks that measure 15.5 m (51 feet) high by 15.5 m (51 feet) wide by 2.1 m (7 feet) deep. The primary parts in the detector construction are 15.5m (51 foot), 15-cell PVC extrusions. These extrusions from the basis of the detector modules which are laminated together in a crossed pattern to form the individual blocks and then filled with mineral oil based liquid scintillator. The self-supportingmore » nature of the detector places important structural requirements on both the PVC formulation and the extrusions. Block assembly requirements impose narrow geometric tolerances. Due to the method of detecting neutrinos, the extrusions must possess exceptionally high reflectivity over a particular wavelength range. The requirement places additional restrictions on the components of the PVC formulation. Altogether, the PVC extrusions have to maintain important reflectivity characteristics, provide structural support to the detector, and meet relatively tight geometric requirements for assembly. In order to meet these constraints, a custom PVC formulation had to be created and extruded. Here, we describe the purpose and requirements of the NOvA detector leading to the production of our unique PVC extrusion, summarize the R&D process, and discuss the lessons learned.« less