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Measurement of neutrino-induced neutral-current coherent production in the NOvA near detector
No full text© 2020 authors. Open access. Published by the American Physical Society under the terms of the "https://creativecommons.org/licenses/by/4.0/"Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by SCOAP3..
WSU authors: Meyer, Holger; Muether, Mathew; Solomey, Nickolas. The complete list includes: Acero, M.A.; Adamson, P.; Aliaga, L.; Alion, T.; Allakhverdian, V.; Anfimov, N.; Antoshkin, A.; Arrieta-Diaz, E.; Aurisano, A.; Back, A.; Backhouse, C.; Baird, M.; Balashov, N.; Baldi, P.; Bambah, B.A.; Basher, S.; Bays, K.; Behera, B.; Bending, S.; Bernstein, R.; Bhatnagar, V.; Bhuyan, B.; Bian, J.; Blair, J.; Booth, A.C.; Bolshakova, A.; Bour, P.; Bromberg, C.; Buchanan, N.; Butkevich, A.; Campbell, M.; Carroll, T.J.; Catano-Mur, E.; Childress, S.; Choudhary, B.C.; Chowdhury, B.; Coan, T.E.; Colo, M.; Corwin, L.; Cremonesi, L.; Cronin-Hennessy, D.; Davies, G.S.; Derwent, P.F.; Ding, P.; Djurcic, Z.; Doyle, D.; Dukes, E.C.; Dung, P.; Duyang, H.; Edayath, S.; Ehrlich, R.; Feldman, G.J.; Flanagan, W.; Frank, M.J.; Gallagher, H.R.; Gandrajula, R.; Gao, F.; Germani, S.; Giri, A.; Gomes, R.A.; Goodman, M.C.; Grichine, V.; Groh, M.; Group, R.; Guo, B.; Habig, A.; Hakl, F.; Hartnell, J.; Hatcher, R.; Hatzikoutelis, A.; Heller, K.; Himmel, A.; Holin, A.; Howard, B.; Huang, J.; Hylen, J.; Jediny, F.; Johnson, C.; Judah, M.; Kakorin, I.; Kalra, D.; Kaplan, D.M.; Keloth, R.; Klimov, O.; Koerner, L.W.; Kolupaeva, L.; Kotelnikov, S.; Kreymer, A.; Kullenberg, C.; Kumar, A.; Kuruppu, C.D.; Kus, V.; Lackey, T.; Lang, K.; Lin, S.; Lokajicek, M.; Lozier, J.; Luchuk, S.; Maan, K.; Magill, S.; Mann, W.A.; Marshak, M.L.; Matveev, V.; Méndez, D.P.; Messier, M.D.; Meyer, H.; Miao, T.; Miller, W.H.; Mishra, S.R.; Mislivec, A.; Mohanta, R.; Moren, A.; Mualem, L.; Muether, M.; Mulder, K.; Mufson, S.; Murphy, R.; Musser, J.; Naples, D.; Nayak, N.; Nelson, J.K.; Nichol, R.; Niner, E.; Norman, A.; Nosek, T.; Oksuzian, Y.; Olshevskiy, A.; Olson, T.; Paley, J.; Patterson, R.B.; Pawloski, G.; Pershey, D.; Petrova, O.; Petti, R.; Plunkett, R.K.; Potukuchi, B.; Principato, C.; Psihas, F.; Raj, V.; Radovic, A.; Rameika, R.A.; Rebel, B.; Rojas, P.; Ryabov, V.; Sachdev, K.; Samoylov, O.; Sanchez, M.C.; Seong, I.S.; Shanahan, P.; Sheshukov, A.; Singh, P.; Singh, V.; Smith, E.; Smolik, J.; Snopok, P.; Solomey, N.; Song, E.; Sousa, A.; Soustruznik, K.; Strait, M.; Suter, L.; Talaga, R.L.; Tas, P.; Thayyullathil, R.B.; Thomas, J.; Tiras, E.; Torbunov, D.; Tripathi, J.; Tsaris, A.; Torun, Y.; Urheim, J.; Vahle, P.; Vasel, J.; Vinton, L.; Vokac, P.; Vrba, T.; Wang, B.; Warburton, T.K.; Wetstein, M.; While, M.; Whittington, D.; Wojcicki, S.G.; Wolcott, J.; Yadav, N.; Yallappa Dombara, A.; Yang, S.; Yonehara, K.; Yu, S.; Zalesak, J.; Zamorano, B.; Zwaska, R.l; NOvA Collaboration.The cross section of neutrino-induced neutral-current coherent production on a carbon-dominated target is measured in the NOvA near detector. This measurement uses a narrow-band neutrino beam with an average neutrino energy of 2.7\,GeV, which is of interest to ongoing and future long-baseline neutrino oscillation experiments. The measured flux-averaged cross section is
, consistent with model prediction. This result is the most precise measurement of neutral-current coherent production in the few-GeV neutrino energy region.Document was prepared by the NOvA Collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP user facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. This work was supported by the U.S. Department of Energy; the U.S. National Science Foundation; the Department of Science and Technology, India; the European Research Council; the MSMT CR, GA UK, Czech Republic; the RAS, RFBR, RMES, RSF, and BASIS Foundation, Russia; CNPq and FAPEG, Brazil; STFC and the Royal Society, United Kingdom; and the state and University of Minnesota
Machine learning in NOA near detector vertexing
Full text linkThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThis work presents an alternative method for a reconstruction machine learning
algorithm in place of the one currently used by the NOA (NuMI Off-axis Appearance)
group for the analysis of neutrino events at the Fermilab near and far detectors. Current
reconstruction methods are flawed because there are many challenges associated with
finding the proper vertex of a neutrino event including background noise, incorrect prong
creation, and secondary vertecies. This work presents a regression-based convolutional
neural network (CNN) that analyzes 2-dimensional pixel maps from NOA ’s catelog of
forward horn current (FHC) and reverse horn current (RHC) h5 files and more accurately
predicts the location of the vertex for each coordinate direction. Additionally, this model
can be implemented into NOA using their primary framework, NOASOFT and applied
to larger data sets to get a better comparison, or even to expand the model to take on
secondary vertexing
Improvement of the nova near detector event reconstruction and primary vertexing through the application of machine learning methods
No full textThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThe purpose of this work is to examine the application of a deep learning model in
event reconstruction of neutrino interactions. The challenges faced in event reconstruction
include the placement of an accurate primary neutrino interaction vertex which is used to
support the particle track and prong algorithms. The result of accurate primary vertex
ensures all particles involved in a neutrino interaction are included. We propose a
regression-based Convolutional Neural Network (CNN) method to predict the primary
vertex of a particle interaction. We show that with raw two-dimensional pixel map views as
input, the regression-based CNN can predict the primary vertex in all three coordinates.
This work is applied as part of the NOvA (NuMI Off-axis Appearance) near detector
reconstruction efforts. The primary vertex predicted by the regression-based CNN model
shows promising results for future applications. This deep learning method can be
extended to secondary vertexing through a Kernel Density Estimate algorithm discussed in
this work
Magnetic field simulation studies in the muon spectrometer
No full textThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThe Deep Underground Neutrino Experiment (DUNE) is focused on addressing important questions in neutrino physics such as matter-antimatter asymmetry and neutrino mass. The experiment utilizes advanced technologies to study muon neutrino disappearance ( ) and electron neutrino ( e) appearance events. An important challenge is distinguishing wrong-sign events, such as antineutrinos, in a neutrino beam. The magnetized TMS is crucial for differentiating muons and antimuons, which allows for accurate oscillation rate predictions.Our study examines the impact of magnetic fields on charge identification in the TMS. Our goal is to determine the optimal field strength for accurate charge determination. We have developed a signed distance metric for charge identification: S.D>0 (for muons) and S.D<0 (for antimuons). We discovered that higher magnetic fields increased the signed distance, which improved the particle’s charge identification. Additionally, as opposed to lower momentum and lower magnetic fields, particle recognition was better at the low momentum range and higher magnetic fields, and even better results were achieved at higher magnetic fields and higher momentum ranges by reducing overlap between the distributions. Plots of Fraction vs. True muon kinetic energy and Fraction vs. momentumTMSStart demonstrate improved charge particle identification with increased magnetic field values
Measurement of a neutral current PI0 cross section in the NOvA near detector
No full textFirst place winner of poster presentations at the 18th Annual Undergraduate Research and Creative Activity Forum (URCAF) held at the Rhatigan Student Center, Wichita State University, April 6, 2018.The NOvA long-baseline neutrino experiment is attempting to measure properties of subatomic particles called neutrinos in order to discover information about the universe. NOvA is a project based out of Fermi National Accelerator Laboratory and funded by the U.S. Department of Energy. The experiment works by firing an extremely high energy beam of neutrinos through the earth at a 14 kiloton detector located hundreds of miles away. This research focused on studying one specific background to the NOvA measurement called neutral current pion production. The goal of the study is to understand how to identify this type of background and consider it when performing measurements for NOvA. Additionally, a cross-section can be calculated to determine the probability of this type of interaction occurring in the detector.
To understand neutral current pion productions, a preliminary cuts-based analysis was performed by hand to separate them from other interactions in the detector. Next, simulated data was fed into a boosted decision tree algorithm, a very powerful tool for separating neutral current pion production interactions from other interactions. After the initial separation, a sideband study was performed to minimize systematic errors. To determine the cross-section, the efficiency and purity of event selection was estimated, and the sideband study was utilized to calculate the cross-section uncertainty. After calculating a single cross-section, a resolution study will be performed to determine if a differential cross-section can be measured. Using this study, NOvA will be able to consider neutral current pion interactions in its final results.Academic AffairsCollege of EducationCollege of Fine ArtsOffice of Research and TechnologyBarton SchoolCohen Honors CollegeCollege of Liberal ArtsUniversity Librarie
The DUNE muon spectrometer: A magnetic systems review
No full textThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThe magnetic system of the Muon Spectrometer in the Near Detector hall of the Deep Underground Neutrino Experiment (DUNE) will enable energy measurements of beam interactions. Confirming the magnetic field within the steel plates of the detector is difficult and providing a measurement of the field to confirm the simulated field provides confidence in its operation. A pickup coil wrapped around individual plate segments would provide enough measurement to confirm computer models of the magnetic field within the plates of the detector
Measurement of charged pion cross section using newly developed reconstruction tool in the NOvA and dune near detector
No full textPresented to the 19th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Rhatigan Student Center, Wichita State University, April 14, 2023.Research completed in the Department of Mathematics, Statistics, and Physics, Fairmount College of Liberal Arts and Sciences.The NOvA and DUNE neutrino experiments are designed to study neutrinos and their interaction properties with matter. Neutrinos, the most abundant massive particle in the universe. They are produced inside the sun, supernovae, galaxies and in nuclear reactors. Neutrinos are electrically neutral particles that come in three types. NOvA and DUNE are both neutrino oscillation experiments which are designed to measure the probability of neutrinos changing types between two detectors that are separated by hundreds of kilometers. Our research group has built a machine learning model to increase the efficiency of determining the point of interaction of particles (Vertex) in the NOvA detector. We plan to use this improved reconstruction to study the likelihood of the production of a charged pion from neutrino interaction. In addition, we are designing a Muon Spectrometer for Phase I of DUNE, which is expected to begin taking data before 2030.Graduate School, Academic Affairs, University Librarie
Understanding the impact of improved hadron production measurements on accelerator neutrino particle beam flux uncertainties
Full text linkThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsOne of the greatest challenges for neutrino experimentation is understanding the
potential uncertainties in the collected data and models that are used for the Monte Carlo
simulations. The neutrino-nucleus hadronic cross sections are a direct input to the
determination of the flux in any accelerator neutrino beam. The high intensity of the
NuMI beamline (Neutrinos at the Main Injector) at Fermilab, in Batavia, IL, allows us to
study neutrino oscillations and neutrino interactions with high statistics. The uncertainties
on the knowledge of the flux is associated with the production and attenuation of hadrons
in the beamline materials and with the beam optics.
The EMPHATIC collaboration is developing a hadron production experiment that
will be used to constrain flux uncertainties in order to reduce them significantly. The group
has taken data impinging 20GeV/c, 30GeV/c and 120GeV/c energy protons into thick (> 1
interaction length) carbon targets during the EMPHATIC beam test in January 2018. The
analysis of the new data provides great details on hadron production cross-section.
This thesis will highlight specific details within the standard model and its
association with neutrino properties. It will also highlight some particle accelerator physics
with applications of Monte Carlo simulations, including the current NuMI beam simulation
and the uncertainty estimates using PPFX software. It also provides an overview of the
EMPHATIC experiment and its engineering test run made in January, 2018. Lastly, by
implementing the improved measurements on the 120 GeV proton impinging on a carbon
target data that was collected by the latest EMPHATIC test run, data will show
verification of a strong improvement for the neutrino flux uncertainty used among several
experiments
Selection optimization of neutral current π⁰ production from an anti-neutrino interaction in the NOvA near detector
No full textThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThe NOvA experiment (NuMI Off-Axis e Appearance) is a particle physics
experiment that is designed to measure neutrino oscillation parameters of muon neutrino
(ν μ) to electron neutrino (ν e), or muon anti-neutrino ( ̅ν μ ) to electron anti-neutrino ( ̅ν e). In
order to get the best results, the signal, which is muon neutrino/anti-neutrino to electron
neutrino/anti-neutrino, detection should be maximized, and the background (other
interactions and factors that may mislead the detection result) should be minimized. One
of the important backgrounds in neutrino oscillation is the neutral current (NC) π⁰
produced by neutrino or anti-neutrino. π⁰ decays and produces to two photons that can
come together to look like an electron, which indicates ̅ν e signal. Also, if one of the photons
escaped the detector the other one will mimic electron shower of the signal. In this thesis,
neutral current π⁰ produced from anti-neutrino interactions and with > 0.5 GeV, will be
the signal. The ultimate goal of this analysis to find the cross section of this interaction.
Knowing the cross section helps in reducing backgrounds from this type of interaction
when looking at ̅ν µ → ̅ν e oscillation, and hence get accurate oscillation parameters. The
background in this analysis are charge current (CC) interactions with and without π⁰ and
NC interactions without π⁰. It is important that in this thesis I found the fractional
uncertainty on the cross section, and not cross section, due to time constraint. However,
the result in this analysis could be used to find the interaction cross section and compare it
with the value from GENIE Monte Carlo (MC) generator. This analysis was performed
based on 6.90×10^20 POT (proton on target) simulated data (MC data), whereas the real
POT in the near detector in is 3.54×10^20. The efficiency and purity of the signal based on
used cuts (Quality, 2 prong, fiducial, containment, MuonID, prong 1 CVN Gamma ID, and
prong 2 CVN Gamma ID) are 0.67% and 64% respectively
Semi-inclusive neutral current neutral pion production selection at the NOvA (numi off-axis electron neutrino appearance) near detector using prong level convolutional neural networks
No full textThesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThe NOνA neutrino experiment based in Fermilab is designed to measure νµ→νe neutrino oscillations. This experiment will give us insight into the properties of massive neutrinos.
Neutral current (NC) νµ,e neutral pion production events can mimic the νµ→νe oscillation
signal and therefore are an important background for NOνA to understand. Neutral pions decay into two photons which can fake a single electron shower (νe appearance signal) in two ways: either the 2 photons can merge together or one of them may escape detection. In order to
constrain this background, NOνA utilizes the Near Detector to measure neutral current neutrino interactions. In this analysis, neutrino-Nucleus (νµ→N) NC π⁰ interactions with total pion energy greater then 0.3 GeV are studied by selecting two prong events with two final state photons as determined by prong based Convolutional Visual Networks (CVN). The analysis is
performed on 3.54x10²¹ Protons On Target (POT) of NOvA Near Detector simulated data and compared to 8.09x10²⁰ POT of data. Optimization of the selection based on fractional
cross-section uncertainty and an initial energy resolution study of the final sample are presented. The final 2 prong selection using prong based CVN gave a purity of 74%, selection efficiency of ∼ 1.8%, and an expected (NC) νµ,e neutral pion cross section of ∼ 15.2%
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