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  1. Massive Wolf-Rayet (WR) stars in binary systems may produce supernovae capable of emitting long duration gamma ray bursts. Characterizing the structure of the colliding winds in these systems may help constrain the mass loss and transfer properties and help predict their future evolution. I will present new spectropolarimetric data for the possible WR+O binary system WR 71, collected using RSS at the Southern African Large Telescope. WR 71 is a WN6 whose binary status is unknown, but it displays similar spectropolarimetric variations to the known WR+O binary system V444 Cygni. I investigate the orbital and rotational velocity of WR 71'smore »winds by analyzing its polarized emission line profiles as a function of phase, the first analysis of its kind. I compare the line polarization behavior with predictive models of both colliding wind binaries and single stars with co-rotating interaction regions. Describing the wind structure of WR 71 will help determine the rate of mass loss from the system, an important indicator for LGRB progenitors, and shed light on its binary status.« less
  2. 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.more »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.« less
    Free, publicly-accessible full text available January 1, 2023
  3. Abstract 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 ν μ -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 ismore »shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.« less
    Free, publicly-accessible full text available December 1, 2022
  4. Abstract Accurate knowledge of electron transport properties is vital to understanding the information provided by liquid argon time projection chambers (LArTPCs). Ionization electron drift-lifetime, local electric field distortions caused by positive ion accumulation, and electron diffusion can all significantly impact the measured signal waveforms. This paper presents a measurement of the effective longitudinal electron diffusion coefficient, D L , in MicroBooNE at the nominal electric field strength of 273.9 V/cm. Historically, this measurement has been made in LArTPC prototype detectors. This represents the first measurement in a large-scale (85 tonne active volume) LArTPC operating in a neutrino beam. This ismore »the largest dataset ever used for this measurement. Using a sample of ∼70,000 through-going cosmic ray muon tracks tagged with MicroBooNE's cosmic ray tagger system, we measure D L = 3.74 +0.28 -0.29 cm 2 /s.« less
    Free, publicly-accessible full text available September 1, 2022