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Muon Neutrino Disappearance In Nova With A Deep Convolutional Neural Network Classifier
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Book Synopsis Muon Neutrino Disappearance in NOvA with a Deep Convolutional Neural Network Classifier by :
Download or read book Muon Neutrino Disappearance in NOvA with a Deep Convolutional Neural Network Classifier written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The NuMI Off-axis Neutrino Appearance Experiment (NOvA) is designed to study neutrino oscillation in the NuMI (Neutrinos at the Main Injector) beam. NOvA observes neutrino oscillation using two detectors separated by a baseline of 810 km; a 14 kt Far Detector in Ash River, MN and a functionally identical 0.3 kt Near Detector at Fermilab. The experiment aims to provide new measurements of [Delta]m2 and [theta]23 and has potential to determine the neutrino mass hierarchy as well as observe CP violation in the neutrino sector. Essential to these analyses is the classification of neutrino interaction events in NOvA detectors. Raw detector output from NOvA is interpretable as a pair of images which provide orthogonal views of particle interactions. A recent advance in the field of computer vision is the advent of convolutional neural networks, which have delivered top results in the latest image recognition contests. This work presents an approach novel to particle physics analysis in which a convolutional neural network is used for classification of particle interactions. The approach has been demonstrated to improve the signal efficiency and purity of the event selection, and thus physics sensitivity. Early NOvA data has been analyzed (2.74×1020 POT, 14 kt equivalent) to provide new best- fit measurements of sin2([theta]23) = 0.43 (with a statistically-degenerate compliment near 0.60) and.
Book Synopsis Measurement of Atmospheric Muon Neutrino Disappearance with IceCube Using Convolutional Neural Network Reconstructions by : Jessie Micallef
Download or read book Measurement of Atmospheric Muon Neutrino Disappearance with IceCube Using Convolutional Neural Network Reconstructions written by Jessie Micallef and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neutrinos are neutral, fundamental particles that oscillate, or change flavor, while they travel. This phenomenon means that neutrinos deviate from the Standard Model prediction that they are massless, creating an exciting window into physics exploration beyond the Standard Model. Understanding neutrino oscillation and constraining their behavior is crucial to furthering the understanding of these particles and how they fit, or do not fit, into the Standard Model. The IceCube Neutrino Observatory has been detecting neutrinos for more than 10 years, leading to a large sample of atmospheric neutrino data available for studying neutrino oscillations. Reconstructing the neutrino interactions, such as the neutrino's energy and direction, are key to constraining neutrino oscillation. A fast and robust reconstruction method was developed using convolutional neural networks (CNNs) and optimized to reconstruct parameters necessary to both reconstruct and isolate a pure atmospheric neutrino sample using the IceCube detector. This work compares the performance of this reconstruction to the current likelihood-based reconstruction currently used in IceCube. An analysis of the muon neutrino disappearance is then pursued using 9.28 years of neutrino data. The analysis shows competitive projected sensitivity, the ability to account for numerous systematics, and robust recovery of the physics parameters under statistical and systematic variations. While the 9.28 year sample is still under collaboration review, one year of the total data is used to perform a confirmatory study on the CNN reconstruction and sample. The oscillation parameter constraints from this one year analysis are in alignment with past IceCube analyses and other neutrino experiments within one sigma. This opens the pathway to use the CNN reconstruction for future analyses studying low energy neutrinos on IceCube.
Book Synopsis Measurement of Muon Neutrino Disappearance with a NOvA Experiment by : Luke Vinton
Download or read book Measurement of Muon Neutrino Disappearance with a NOvA Experiment written by Luke Vinton and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Domain Generalization with Machine Learning in the NOvA Experiment by : Andrew T.C. Sutton
Download or read book Domain Generalization with Machine Learning in the NOvA Experiment written by Andrew T.C. Sutton and published by Springer Nature. This book was released on 2023-12-10 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents significant advances in the use of neural networks to study the properties of neutrinos. Machine learning tools like neural networks (NN) can be used to identify the particle types or determine their energies in detectors such as those used in the NOvA neutrino experiment, which studies changes in a beam of neutrinos as it propagates approximately 800 km through the earth. NOvA relies heavily on simulations of the physics processes and the detector response; these simulations work well, but do not match the real experiment perfectly. Thus, neural networks trained on simulated datasets must include systematic uncertainties that account for possible imperfections in the simulation. This thesis presents the first application in HEP of adversarial domain generalization to a regression neural network. Applying domain generalization to problems with large systematic variations will reduce the impact of uncertainties while avoiding the risk of falsely constraining the phase space. Reducing the impact of systematic uncertainties makes NOvA analysis more robust, and improves the significance of experimental results.
Book Synopsis First Measurement of Muon-Neutrino Disappearance in NOvA. by :
Download or read book First Measurement of Muon-Neutrino Disappearance in NOvA. written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper reports the first measurement using the NOvA detectors of $\nu_\mu$ disappearance in a $\nu_\mu$ beam. The analysis uses a 14 kton-equivalent exposure of $2.74 \times 10^{20}$ protons-on-target from the Fermilab NuMI beam. Assuming the normal neutrino mass hierarchy, we measure $\Delta m^{2}_{32}=(2.52^{+0.20}_{-0.18})\times 10^{-3}$ eV$^{2}$ and $\sin^2\theta_{23}$ in the range 0.38-0.65, both at the 68% confidence level, with two statistically-degenerate best fit points at $\sin^2\theta_{23} = $ 0.43 and 0.60. Results for the inverted mass hierarchy are also presented.
Book Synopsis Muon Neutrino Contained Disappearance in NOvA. by :
Download or read book Muon Neutrino Contained Disappearance in NOvA. written by and published by . This book was released on 2015 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NO$\nu$ A experiment studies neutrino oscillations in the NuMI neutrino beam from Fermilab. NO$\nu$ A consists of two liquid scintillator tracking calorimeters placed 14 milliradians off-axis from the beam and 810 km apart. The NO$\nu$ A experiment started taking data in 2014. This thesis establishes the neutrino energy estimation procedures used to determine the oscillation parameters sin2[theta]23 and [Delta]m232.
Book Synopsis Study of Muon Neutrino and Muon Antineutrino Disappearance with the NOvA Neutrino Oscillation Experiment by :
Download or read book Study of Muon Neutrino and Muon Antineutrino Disappearance with the NOvA Neutrino Oscillation Experiment written by and published by . This book was released on 2014 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary goal of this working group is to study the disappearance rate of [nu][mu] charged current events in order to measure the mixing angle [theta]23 and the magnitude of the neutrino mass square splitting [Delta]m 232.
Book Synopsis A Deep-Learning-Based Muon Neutrino CCQE Selection for Searches Beyond the Standard Model with MicroBooNE by : Davio Cianci
Download or read book A Deep-Learning-Based Muon Neutrino CCQE Selection for Searches Beyond the Standard Model with MicroBooNE written by Davio Cianci and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The anomalous Low Energy Excess (LEE) of electron neutrinos and antineutrinos in MiniBooNE has inspired both theories and entire experiments to probe the heart of its mystery. One such experiment is MicroBooNE. This dissertation presents an important facet of its LEE investigation: how a powerful systematic can be levied on this signal through parallel study of a highly correlated channel in muon neutrinos. This constraint serves to strengthen MicroBooNE's ability to confirm or validate the cause of the LEE and will lay the groundwork for future oscillation experiments in Liquid Argon Time Projection Chamber (LArTPC) detector experiments like SBN and DUNE. In addition, this muon channel can be used to test oscillations directly, demonstrated through the world's first muon neutrino disappearance search with LArTPC data.
Book Synopsis An Atmospheric Muon Neutrino Disappearance Measurement with the MINOS Far Detector by : Jeremy Peter Gogos
Download or read book An Atmospheric Muon Neutrino Disappearance Measurement with the MINOS Far Detector written by Jeremy Peter Gogos and published by . This book was released on 2007 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Analysis of Muon Neutrino Disappearance from the NuMI Beam Using an Optimal Track Fitter by :
Download or read book An Analysis of Muon Neutrino Disappearance from the NuMI Beam Using an Optimal Track Fitter written by and published by . This book was released on 2015 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NOvA experiment is a long-baseline neutrino oscillation experiment based out of Fermilab National Accelerator Laboratory that uses two liquid scintillator detectors, one at Fermilab (the \near" detector) and a second 14 kton detector in northern Minnesota (the \far" detector.) The primary physics goals of the NOvA experiment are to measure neutrino mixing parameters through both the v[mu] disappearance and ve appearance channels using neutrinos from the newly upgraded NuMI beam line. The NOvA v[mu] disappearance analysis can significantly improve the world's best measurement of sin2 [theta] 23. This analysis proceeds by using the measured v[mu] charged-current energy spectrum in the near detector to predict the spectrum in the far detector, and comparing this to the measured spectrum to obtain a best fit for the oscillation parameters sin2 [theta] 23 and [Delta]m2 32. Since this fit is governed by the shape of the energy spectrum, the best fit will be maximized by obtaining the best possible energy resolution for the individual neutrino events. This dissertation describes an alternate v[mu] disappearance analysis technique for the NOvA experiment, based on the idea that estimating the energy resolution of the individual events will allow them to be separated into different energy resolution samples in order to improve the final fit.
Book Synopsis Muon Neutrino Disappearance at T2K. by : Alexander Hyndman
Download or read book Muon Neutrino Disappearance at T2K. written by Alexander Hyndman and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis First Results of $\nu_e$ Appearance Analysis and Electron Neutrino Identification at NOvA. by :
Download or read book First Results of $\nu_e$ Appearance Analysis and Electron Neutrino Identification at NOvA. written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: NOvA is a long-baseline accelerator-based neutrino oscillation experiment that is optimized for $\nu_\mu\to\nu_e$ measurements. It uses the upgraded NuMI beam from Fermilab and measures electron-neutrino appearance and muon-neutrino disappearance at its Far Detector in Ash River, Minnesota. The $\nu_e$ appearance analysis at NOvA aims to resolve the neutrino mass hierarchy problem and to constrain the CP-violating phase. The first data set of $2.74\times10^{20}$ protons on target (POT) equivalent exposure taken by NOvA has been analyzed. The first measurement of electron-neutrino appearance in NOvA provides solid evidence of $\nu_\mu\to\nu_e$ oscillation with the NuMI beam line. Electron-neutrino identification is the key ingredient for the $\nu_e$ appearance analysis. The electron-identification algorithm used to produce the primary results presented here compares 3-D shower-energy profiles with Monte Carlo prototypes to construct likelihoods for each particle hypothesis. Particle likelihoods, among other event-topology variables, are used as inputs to an Artificial Neural Network for the final electron-neutrino identification. The design and implementation of this algorithm is also presented.
Book Synopsis Muon Neutrino Disappearance at T2K. by :
Download or read book Muon Neutrino Disappearance at T2K. written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Study of Muon Neutrino Disappearance in the MINOS Detectors and the NuMI Beam by :
Download or read book A Study of Muon Neutrino Disappearance in the MINOS Detectors and the NuMI Beam written by and published by . This book was released on 2010 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is now substantial evidence that the proper description of neutrino involves two representations related by the 3 x 3 PMNS matrix characterized by either distinct mass or flavor. The parameters of this mixing matrix, three angles and a phase, as well as the mass differences between the three mass eigenstates must be determined experimentally. The Main Injector Neutrino Oscillation Search experiment is designed to study the flavor composition of a beam of muon neutrinos as it travels between the Near Detector at Fermi National Accelerator Laboratory at 1 km from the target, and the Far Detector in the Soudan iron mine in Minnesota at 735 km from the target. From the comparison of reconstructed neutrino energy spectra at the near and far location, precise measurements of neutrino oscillation parameters from muon neutrino disappearance and electron neutrino appearance are expected. It is very important to know the neutrino flux coming from the source in order to achieve the main goal of the MINOS experiment: precise measurements of the atmospheric mass splitting.
Book Synopsis A Study of Muon Neutrino Disappearance with the MINOS Detectors and the NuMI Neutrino Beam by : John Stuart Marshall
Download or read book A Study of Muon Neutrino Disappearance with the MINOS Detectors and the NuMI Neutrino Beam written by John Stuart Marshall and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Measurement of Atmospheric Muon Neutrino Disappearance with IceCube-DeepCore by : Matthew Dunkman
Download or read book Measurement of Atmospheric Muon Neutrino Disappearance with IceCube-DeepCore written by Matthew Dunkman and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The measurement of muon neutrino disappearance presentedhere was designed to make use of neutrinos of all flavors,exploiting $\nu_e$ events and more poorly reconstructedcascade-like neutrino events to better constrain systematicuncertainties associated with neutrino fluxes and interactions. Inaccordance with IceCube Collaboration policy, the analysis was developed "blind,'' with reference to Monte Carlo simulations and down-going events where no oscillation signal could be visible. Discrepancies observed in the data when they were examined after theanalysis was finalized led to the conclusion that the cascade-like and intermediate data samples were affected by unexpected systematiceffects, so that their inclusion in the analysis produced substantialbias. This analysis thus relied exclusively on the track-like data sample, while investigations into the nature of these systematic effects continue in preparation for an IceCubejournal article.The best fit and 68% confidence interval from this analysison the two oscillation parameters which drive muon neutrino disappearance are\begin{align*} \sin^2 \theta_{23} &= 0.53_{-0.11}^{+0.07}, \\ \Delta m_{32}^2 / 10^{-3}\mathrm{eV}^2 &= 2.35_{-0.17}^{+0.14},\end{align*}which are compatible and competitive with measurements madeby dedicated beam-line neutrino experiments.
Book Synopsis Dual Baseline Search for Muon Neutrino Disappearance at $0.5 {\rm EV}^2 [\Delta M^2 [40 {\rm EV}^2$ by :
Download or read book Dual Baseline Search for Muon Neutrino Disappearance at $0.5 {\rm EV}^2 [\Delta M^2 [40 {\rm EV}^2$ written by and published by . This book was released on 2011 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: The SciBooNE and MiniBooNE collaborations report the results of a [nu]{sub {mu}} disappearance search in the [Delta]m2 region of 0.5-40 eV2. The neutrino rate as measured by the SciBooNE tracking detectors is used to constrain the rate at the MiniBooNE Cherenkov detector in the first joint analysis of data from both collaborations. Two separate analyses of the combined data samples set 90% confidence level (CL) limits on [nu]{sub {mu}} disappearance in the 0.5-40 eV2 [Delta]m2 region, with an improvement over previous experimental constraints between 10 and 30 eV2.
