Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.778304
Title: Constraint of systematic uncertainties in an electron neutrino search using muon neutrinos at MicroBooNE
Author: Lister, Adam
ISNI:       0000 0004 7964 0384
Awarding Body: Lancaster University
Current Institution: Lancaster University
Date of Award: 2019
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Abstract:
MicroBooNE is a liquid argon time projection chamber which has been running in the Booster Neutrino Beam at Fermilab since 2015. The primary goal of MicroBooNE is investigation of the excess of electromagnetic events observed by the MiniBooNE collaboration. Due to limitations of the Cherenkov-based particle identification of MiniBooNE, this excess could be interpreted as either photon-like or electron-like. A photon-like excess would indicate that there are processes which are not well understood which could act as a background in neutrino oscillation measurements, while an electron-like excess could indicate the presence of sterile neutrinos, the existence of which is one of the most hotly debated questions in the field. This work will outline the MicroBooNE strategy for investigation of this low-energy excess, with particular attention given to the role of the muon neutrino sideband which is used as an important constraint on systematic uncertainties. A procedure has been developed in order to apply this constraint to an electron neutrino dataset, and it has been shown that the constraint results in an improvement to the sensitivity. In order to perform this constraint, an exclusive-state νμ CC selection has been developed, which results in 804 selected events from on-beam data. The ratio of the data with respect to simulation is R=0.78 ± 0.04 (stat.) ± 0.12 (syst.). In addition, this thesis presents a first measurement of the longitudinal ionisation electron diffusion coefficient from the MicroBooNE data, which is determined to be 3.73 (+0.70, -0.68) cm2/s.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.778304  DOI:
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