MicroBooNE: The Search For The MiniBooNE Low Energy Excess

This thesis describes work towards the search for a low energy excess of electromagnetic events in the MicroBooNE detector. A background primer on the current state of neutrino physics is provided, including a description of the MiniBooNE detector and its published observation of an excess of electromagnetic events at low energies. A description of the MicroBooNE Liquid Argon Time Projection Chamber (LArTPC) detector is given, along with a description of the event selection and reconstruction algorithms developed to select electron neutrino charge-current interactions. A MiniBooNE-like signal is simulated in MicroBooNE with assumptions about the origin of the excess, and the sensitivity to observe such a signal above backgrounds in MicroBooNE is computed. An additional analysis is presented which constrains a dominant background in the MicroBooNE low energy excess search: the beam-intrinsic electron neutrino interactions which come from kaon decay in the beam-line. An essential step in this analysis is to reconstruct the energy of muon neutrino charge-current interactions in which the muon produced in the interaction escapes the detector. A publication detailing the algorithm which leverages the phenomenon of multiple Coulomb scattering to reconstruct the energy of escaping muons is provided as an appendix

Novel approaches to prevent and treat pertussis

Pertussis remains a significant health problem, killing up to 200,000 infants annually. We are pursuing two complementary approaches to this problem, (1) engineering the adenylate cyclase toxin as an additional antigen for inclusion in the current accellular vaccine and (2) developing a neonatal antibody therapeutic to protect infants during the most vulnerable period before they are fully vaccinated. The current vaccine confers short-term immunity and prevents the symptoms of disease but does not reduce infection or transmission rates. The adenylate cyclase toxin (ACT) is the leading candidate for inclusion in future vaccines, yet there is surprisingly little data detailing the mechanisms by which ACT confers protection or its appropriateness for manufacturing and formulation as a part of a multicomponent vaccine. We have engineered this protein for improved production and stability and have identified a panel of neutralizing and non-neutralizing antibodies to aid in further engineering efforts. We are currently using the original ACT and our engineered variant in mouse immunization experiments to dissect ACT’s role in protection. Notably, addition of our engineered protein to the current acellular vaccine results in 97% increased bacterial clearance during the early stages of disease, likely by protecting macrophages and neutrophils from toxin activites. To provide a therapeutic option before a new vaccine is lisenced, we have developed a humanized antibody, hu1B7, to both treat and prevent pertussis. This has been engineered for high affinity binding, reduced immunogenicity and extended serum half-life. We have shown hu1B7 is protective against disease in mouse and adolescent baboon models of disease. We have also characterized the antibodies’ mechanisms of action, using biochemical, structural and cellular assays. To determine if passive immunization could protect newborns from pertussis infection, hu1B7 was tested in newborn baboons. Two-day-old baboons received hu1B7 (40 mg/kg, IV) and five weeks later were infected with 108 cfu of B. pertussis. Animals were monitored for clinical signs of disease including leukocytosis, coughing, and bacterial colonization. Thu far, 7 hu1B7-treated and 6 control animals have completed the study. Antibody prophylaxis mitigated the clinical signs of pertussis, including leukocytosis (p = 0.004) and coughing, but as expected, did not prevent bacterial colonization (p = 0.15). As a step toward lowering the cost for developing world applications, we have generated and completed in vitro testing of an extended half-life version of hu1B7. Data from baboons treated with this variant will be reporte

Oral Metallo-Beta-Lactamase Protects the Gut Microbiome From Carbapenem-Mediated Damage and Reduces Propagation of Antibiotic Resistance in Pigs

Antibiotics can damage the gut microbiome, leading to serious adventitious infections and emergence of antibiotic resistant pathogens. Antibiotic inactivation in the GI tract represents a strategy to protect colonic microbiota integrity and reduce antibiotic resistance. Clinical utility of this approach was established when SYN-004 (ribaxamase), an orally-administered beta-lactamase, was demonstrated to degrade ceftriaxone in the GI tract and preserve the gut microbiome. Ribaxamase degrades penicillins and cephalosporin beta-lactams, but not carbapenems. To expand this prophylactic approach to include all classes of beta-lactam antibiotics, a novel carbapenemase, formulated for oral administration, SYN-006, was evaluated in a porcine model of antibiotic-mediated gut dysbiosis. Pigs (20 kg, n = 16) were treated with the carbapenem, ertapenem (ERT), (IV, 30 mg/kg, SID) for 4 days and a cohort (n = 8) also received SYN-006 (PO, 50 mg, QID), beginning the day before antibiotic administration. ERT serum levels were not statistically different in ERT and ERT + SYN-006 groups, indicating that SYN-006 did not alter systemic antibiotic levels. Microbiomes were evaluated using whole genome shotgun metagenomics analyses of fecal DNA collected prior to and after antibiotic treatment. ERT caused significant changes to the gut microbiome that were mitigated in the presence of SYN-006. In addition, SYN-006 attenuated emergence of antibiotic resistance, including encoded beta-lactamases and genes conferring resistance to a broad range of antibiotics such as aminoglycosides and macrolides. SYN-006 has the potential to become the first therapy designed to protect the gut microbiome from all classes of beta-lactam antibiotics and reduce emergence of carbapenem-resistant pathogens

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

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

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

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.Comment: Preprint to be submitted to The European Physical Journal

Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE

The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of induction plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.Comment: 54 pages, 36 figures; the first part of this work can be found at arXiv:1802.0870