Neutrino Scattering in the NOvA Near Detector
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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Results for “Neutrino detector”
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First results from the search of $ν_μ$ disappearance with ICARUS
his work presents a search for muon neutrino disappearance signal using the ICARUS detector. ICARUS is currently working as the far detector of the Short-Baseline Neutrino (SBN) program. Its main goal is to investigate the possible oscillation of a sterile neutrino state ($\Delta m^2 \sim \text{eV}^2$), that would drive short baseline oscillations at the scale of L/E $\sim$ km/GeV. Neutrino interactions from the Booster Neutrino Beam (BNB) are investigated, looking for simple final state topology with a single muon and at least one proton (1$\mu$Np). This analysis tests the 3+1 model using the two flavor neutrino approximation, where careful consideration has been given to the systematic uncertainties arising from flux, neutrino interaction, and detector models. No statistically significant $\nu_\mu$ disappearance is observed, hence 90\% C.L. exclusion contours are reported in the $\Delta m^2_{41} - \sin^22\theta_{\mu\mu}$ parameter space.
Artero Pons, Maria [INFN, Padua; U. Padua (main)]↗
Measurement of Electron Neutrino and Antineutrino Appearance with the NO{$\nu$}A Experiment
As a long-baseline neutrino oscillation experiment, the NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment aims at studying neutrino physics by measuring neutrino oscillation parameters using the neutrino flux from the Main Injector (NuMI) beam. It has two functionally identical detectors. The near detector is onsite at Fermi National Accelerator Laboratory. The far detector is 810 km away from the source of neutrinos and antineutrinos, at Ash River, Minnesota. At the near detector, muon neutrinos or antineutrinos, before significant oscillations take place, are used to correct the Monte Carlo simulation. At the far detector, the neutrino and antineutrino fluxes after significant oscillations have happened are measured and analyzed to study neutrino oscillation. The NOvA experiment is sensitive to the values of $\sin^2{\theta_{23}}$, $\Delta m^2_{32}$, and $\delta_{CP}$. The latest values from the NOvA 2020 analysis are as follows: $\sin^2{\theta_{23}}= 0.57^{+0.03}_{-0.04}$, $\Delta m^2_{32} = (2.41 \pm 0.07)\times 10^{-3}$\,eV$^2/c^4$, and $\delta_{CP}=0.82\pi$ with a wide 1$\sigma$ interval of uncertainty. My study is focused on the neutrino oscillation analysis with NOvA, including detector light model tuning, particle classification with convolutional neural network, electron neutrino and antineutrino energy reconstruction, and oscillation background estimation. Most of my studies have been used in the latest NOvA publication and the NOvA 2020 analysis.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Sterile Neutrino Search using nue Appearance with NOvA Near Detector
This poster reports the current status of a short-baseline sterile-neutrino search using the NOvA ND in a (3+1) framework with combined neutrino-mode and antineutrino-mode data.
Acharya, Bishnu [Mississippi U.]↗
Searches for decays of new particles in the DUNE Multi-Purpose near Detector
One proposed component of the upcoming Deep Underground Neutrino Experiment (DUNE) near detector complex is a multi-purpose, magnetized, gaseous argon time projection chamber: the Multi-Purpose Detector (MPD). We explore the new-physics potential of the MPD, focusing on scenarios in which the MPD is significantly more sensitive to new physics than a liquid argon detector, specifically searches for semi-long-lived particles that are produced in/near the beam target and decay in the MPD. The specific physics possibilities studied are searches for dark vector bosons mixing kinetically with the Standard Model hypercharge group, leptophilic vector bosons, dark scalars mixing with the Standard Model Higgs boson, and heavy neutral leptons that mix with the Standard Model neutrinos. We demonstrate that the MPD can extend existing bounds in most of these scenarios. We illustrate how the ability of the MPD to measure the momentum and charge of the final state particles leads to these bounds.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Passive Low-Energy Nuclear-Recoil Detection with Color Centers
Crystal-damage events such as tracks and point defects have been used to record and detect radiation for a long time and recently they have been proposed as a means for dark-matter detection. Color centers can be read out optically and we propose a scheme based on selective plane illumination microscopy for micrometer-scale imaging of large volumes corresponding to kilogram mass detectors. This class of detectors would be passive and would operate at room temperature and we call this the passive low-energy optical color-center nuclear-recoil (PALEOCCENE) detection method. We apply these concepts to the detection of reactor neutrinos using coherent elastic neutrino nucleus scattering (CE ν NS). Crystal-damage formation energies are intrinsically on the order of 25 eV, resulting in similarly low nuclear-recoil thresholds. Furthermore, this would enable the observation of reactor-neutrino CE ν NS with detectors as small as 10 g. Additionally, a competitive search for spin-dependent dark-matter scattering down to a dark-matter mass of 0.3 GeV could be possible. Passive crystal detectors might also be attractive for nuclear-nonproliferation safeguards if used to monitor reactor power and to put limits on plutonium production. The passive nature and small footprint of the proposed detectors implies that these might fit well within accepted reactor-safeguards operations.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Monitoring the SNS basement neutron background with the MARS detector
Here, we present the analysis and results of the first dataset collected with the MARS neutron detector deployed at the Oak Ridge National Laboratory Spallation Neutron Source (SNS) for the purpose of monitoring and characterizing the beam-related neutron (BRN) background for the COHERENT collaboration. MARS was positioned next to the COH-CsI coherent elastic neutrino-nucleus scattering detector in the SNS basement corridor. This is the basement location of closest proximity to the SNS target and thus, of highest neutrino flux, but it is also well shielded from the BRN flux by infill concrete and gravel. Furthermore, these data show the detector registered roughly one BRN per day. Using MARS' measured detection efficiency, the incoming BRN flux is estimated to be 1.20 ± 0.56 neutrons/m 2 /MWh for neutron energies above ~3.5 MeV and up to a few tens of MeV. We compare our results with previous BRN measurements in the SNS basement corridor reported by other neutron detectors.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Electromagnetic shower reconstruction in the ICARUS liquid argon time projection chamber detector
The ICARUS-T600 liquid argon time projection chamber (LArTPC) detector is taking data at shallow depth as the far detector of the Short Baseline Neutrino (SBN) program at Fermilab, to search for a possible sterile neutrino signal at $\Delta m^{2} \approx 1~\text{eV}^{2}$ with the Booster (BNB) and Main Injector (NuMI) neutrino beams at $\GeV{\sim 0.8}$ and $\GeV{\sim 2}$ average energies respectively. The LArTPC technology, developed by the ICARUS collaboration and now a standard in neutrino physics, offers impressive charged-particle imaging capabilities with $\sim1 \ \text{mm}$ spatial resolution, enabling efficient discrimination between track-like signatures (e.g., from muons, pions, and protons) and electromagnetic showers (from electrons and photons). Moreover, electron and photon signatures can be distinguished both with the calorimetric measurement of local energy depositions at the shower start and with the cm-scale conversion gap signature of photons. This contribution discusses event reconstruction at ICARUS focusing on Pandora, a multi-algorithm pattern recognition software widely used in LArTPC experiments. Over a hundred Pandora algorithms and tools are used to reconstruct cosmic rays and neutrino interactions in the ICARUS detector. Recent developments have focused on the reconstruction of electromagnetic shower signatures, crucial to ensure a robust and efficient reconstruction of charged-current $\nu_e$ interactions, which serve as a key signature of sterile neutrino oscillations at SBN. In this contribution, recent improvements to the reconstruction are discussed, focusing on the discrimination between tracks and electromagnetic showers using neutrino simulations and data.
Triozzi, Riccardo [Padua U.; INFN, Padua] (ORCID:0↗
Latest Three Flavor Neutrino Oscillation Results from the NOvA Experiment.
NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is designed primarily to constrain neutrino oscillation parameters such as the atmospheric mass squared splitting, $\Delta m^2_{32}$, the mixing angle, $\theta_{23}$, neutrino mass hierachy, and the CP-violating phase, $\delta_{CP}$, using $\nu_\mu \ (\bar{\nu}_\mu)$ disappearance and $\nu_e \ (\bar{\nu}_e)$ appearance data. NOvA receives a high purity instense beam of neutrinos and anti-neutrinos from Fermilab's Neutrinos at Main Injector (NuMI) beamline. The NOvA near detector (ND) observes un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and beam $\nu_e \ (\bar{\nu}_e)$ events, while the far detector (FD), which is situated 810 km away from the near detector, records un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and oscillated $\nu_e \ (\bar{\nu}_e)$ events. The best fit values of the oscillation parameters are extracted by performing a joint fit of the far detector predicted events to data from $\nu_\mu \to \nu_\mu$, $\bar{\nu}_\mu \to \bar{\nu}_\mu$, $\nu_\mu \to \nu_e$, and $\bar{\nu}_\mu \to \bar{\nu}_e$ oscillation channels. We present latest joint fit results from NOvA based on a neutrino-beam exposure of $27.24 \times 10^{20}$ POT and an anti-neutrino beam exposure of $12.55\times 10^{20}$ POT and improved simulations.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Latest Three Flavor Neutrino Oscillation Results from the NOvA Experiment.
NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is designed primarily to constrain neutrino oscillation parameters such as the atmospheric mass squared splitting, $\Delta m^2_{32}$, the mixing angle, $\theta_{23}$, neutrino mass hierachy, and the CP-violating phase, $\delta_{CP}$, using $\nu_\mu \ (\bar{\nu}_\mu)$ disappearance and $\nu_e \ (\bar{\nu}_e)$ appearance data. NOvA receives a high purity instense beam of neutrinos and anti-neutrinos from Fermilab's Neutrinos at Main Injector (NuMI) beamline. The NOvA near detector (ND) observes un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and beam $\nu_e \ (\bar{\nu}_e)$ events, while the far detector (FD), which is situated 810 km away from the near detector, records un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and oscillated $\nu_e \ (\bar{\nu}_e)$ events. The best fit values of the oscillation parameters are extracted by performing a joint fit of the far detector predicted events to data from $\nu_\mu \to \nu_\mu$, $\bar{\nu}_\mu \to \bar{\nu}_\mu$, $\nu_\mu \to \nu_e$, and $\bar{\nu}_\mu \to \bar{\nu}_e$ oscillation channels. We present latest joint fit results from NOvA based on a neutrino-beam exposure of $27.24 \times 10^{20}$ POT and an anti-neutrino beam exposure of $12.55\times 10^{20}$ POT and improved simulations.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Status of the muon neutrino charged-current zero mesons cross section measurement in the NOvA near detector
NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement will be made with respect to the kinematics of the final state particles. Our chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and will provide a handle for constraining the cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A D$_2$O detector for flux normalization of a pion decay-at-rest neutrino source
We report on the technical design and expected performance of a 592 kg heavy-water-Cherenkov detector to measure the absolute neutrino flux from the pion-decay-at-rest neutrino source at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL). The detector will be located roughly 20 m from the SNS target and will measure the neutrino flux with better than 5% statistical uncertainty in 2 years. This heavy-water detector will serve as the first module of a two-module detector system to ultimately measure the neutrino flux to 2–3% at both the First Target Station and the planned Second Target Station of the SNS. This detector will significantly reduce a dominant systematic uncertainty for neutrino cross-section measurements at the SNS, increasing the sensitivity of searches for new physics.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
First Measurement of the Electron-Neutrino Charged-Current Pion Production Cross Section on Carbon with the T2K Near Detector
The T2K Collaboration presents the first measurement of electron neutrino-induced charged-current pion production on a predominantly carbon target in a restricted kinematical phase space. This is performed using data from the 2.5° off-axis near detector, ND280. The differential cross sections with respect to the outgoing electron and pion kinematics, in addition to the total flux-integrated cross section, are obtained. Comparisons between the measured and predicted cross-section results using the neut, genie, and nuwro Monte Carlo event generators are presented. The measured total flux-integrated cross section is [2.52 ± 0.52(stat) ± 0.30(syst)] × 10 −39 cm 2 nucleon −1 , which is lower than the event generator predictions.
Neutrinos↗
Understanding neutrinos with accelerator beams and liquid argon time-projection chambers: ICARUS and DUNE
A global program of experiments has worked towards characterizing neutrino oscillation over the past few decades. However, important parameters remain to be measured, and mysteries remain to be elucidated. Current and upcoming experiments are targeting the open questions and probing the consistency of the neutrino oscillation paradigm. Likewise, the liquid argon (LAr) time-projection chamber (TPC) has emerged as a sensitive particle detection technology for neutrino experiments. A current generation of LAr TPC detectors are being used to study neutrinos while also gaining important experience in operating and analyzing with this technology. SBND, MicroBooNE, and ICARUS have collected or are collecting data from beams at Fermilab (near Chicago) to explore the possibility of a sterile neutrino and/or other beyond Standard Model (BSM) physics. SBND and ICARUS will be used to conduct a two-detector analysis as part of the Short Baseline Neutrino (SBN) Program. Additionally, these detectors are enabling important neutrino interaction studies necessary to prepare for the next generation of oscillation experiments. One such oscillation experiment that will come online over the next years is the Deep Underground Neutrino Experiment (DUNE), which will install multiple 10 kiloton LAr TPCs underground in South Dakota (south of Saskatchewan) to conduct oscillation measurements with neutrinos originating in a beamline at Fermilab. A detector complex will be installed at Fermilab as well, to study the beam before the expected flavour oscillations. This “near detector” will also employ a LAr TPC, with a segmented and pixel-based design, as well as other technologies to constrain uncertainties in the oscillation measurement by characterizing the beam and neutrino interactions. This talk will discuss the ICARUS and DUNE experiments, the LAr TPC detector technology, and the efforts to realize and leverage these experiments to better understand the properties of neutrinos.
Howard, Bruce L. [Fermilab]↗
Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network
The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within ±1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.
43 PARTICLE ACCELERATORS↗
Coherent scattering of cosmic neutrinos
It is shown that cosmic neutrino scattering can be non-negligible when coherence effects previously neglected are taken into account. The coherent neutrino scattering cross section is derived and the neutrino index of refraction evaluated. As an example of coherent neutrino scattering, a detector using critical reflection is described which in principle can detect the low energy cosmic neutrino background allowed by the measured cosmological red shift.
Opher, R.↗
Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network
The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within 1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.
Utaegbulam, Hilary↗
DNN-based Signal Processing for Liquid Argon Time Projection Chambers
We investigate a deep learning-based signal processing for liquid argon time projection chambers (LArTPCs), a leading detector technology in neutrino physics. Identifying regions of interest (ROIs) in LArTPCs is challenging due to signal cancellation from bipolar responses and various detector effects observed in real data. We approach ROI identification as an image segmentation task, and employ a U-ResNet architecture. The network is trained on samples that incorporate detector geometry information and include a range of detector variations. Our approach significantly outperforms traditional methods while maintaining robustness across diverse detector conditions. This method has been adopted for signal processing in the Short-Baseline Neutrino program and provides a valuable foundation for future experiments such as the Deep Underground Neutrino Experiment.
Bhat, Avinay [Chicago U.]↗