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The MicroBooNE Search For Anomalous ...

Genty, Victor.

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The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The MicroBooNE Search For Anomalous Electron Neutrino Appearance Using Image Based Data Reconstruction./
Author:	Genty, Victor.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	249 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:	Dissertations Abstracts International80-10B.
Subject:	Particle physics. -
Online resource:	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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300 $a 249 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Shaevitz, Michael.
502 $a Thesis (Ph.D.)--Columbia University, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a 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.
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650 4 $a Particle physics. $3 3433269
653 $a Computer vision
653 $a Image
653 $a LARTPC
653 $a Liquid argon
653 $a Low energy excess
653 $a Microboone
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773 0 $t Dissertations Abstracts International $g 80-10B.
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13860818