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The MicroBooNE Search For Anomalous ...
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Genty, Victor.
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The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction./
作者:
Genty, Victor.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
249 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:
Dissertations Abstracts International80-10B.
標題:
Particle physics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13860818
ISBN:
9781392078563
The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction.
Genty, Victor.
The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 249 p.
Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Thesis (Ph.D.)--Columbia University, 2019.
This item must not be sold to any third party vendors.
This thesis presents the MicroBooNE search for the MiniBooNE low energy excess using a fully automated image based data reconstruction scheme. A suite of traditional and deep learning computer vision algorithms are developed for identification of charge current quasi-elastic (CCQE) like muon and electron neutrino interactions using the MicroBooNE detector. Given a model of the MiniBooNE low energy excess as due to an enhancement of electron neutrino type events, this analysis predicts a combined statistical and systematic 3.8σ low energy signal in 13.2 x 1020 POT of MicroBooNE data. When interpreted in the context of νµ → νe 3 + 1 sterile neutrino oscillations a best fit point of (Δm241, sin2 2&thetas; eµ) = (0.063,0.794) is found with a 90% confidence allowed region consistent with > 0.1 eV2 oscillations.
ISBN: 9781392078563Subjects--Topical Terms:
3433269
Particle physics.
Subjects--Index Terms:
Computer vision
The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction.
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