A Stability Analysis Framework for Oscillation Analysis and Mitigation
This presentation showcases a framework for oscillation analysis and mitigation based on small-signal analysis.
24 POWER TRANSMISSION AND DISTRIBUTION↗
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The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis
The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.
Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗
Compressed baryon acoustic oscillation analysis is robust to modified-gravity models
Abstract We study the robustness of the baryon acoustic oscillation (BAO) analysis to the underlying cosmological model. We focus on testing the standard BAO analysis that relies on the use of a template. These templates are constructed assuming a fixed fiducial cosmological model and used to extract the location of the acoustic peaks. Such “compressed analysis” had been shown to be unbiased when applied to the ΛCDM model and some of its extensions. However, it has not been known whether this type of analysis introduces biases in a wider range of cosmological models where the template may not fully capture relevant features in the BAO signal. In this study, we apply the compressed analysis to noiseless mock power spectra that are based on Horndeski models, a broad class of modified-gravity theories specified with eight additional free parameters. We study the precision and accuracy of the BAO peak-location extraction assuming DESI, DESI II, and MegaMapper survey specifications. We find that the bias in the extracted peak locations is negligible; for example, it is less than 10% of the statistical error for even the proposed future MegaMapper survey. Our findings indicate that the compressed BAO analysis is remarkably robust to the underlying cosmological model.
Astronomy & Astrophysics↗
Bayesian Fit to NOvA Data Subsamples for Three Flavor Oscillation Analysis
NOvA (NuMI Off-Axis $\nu_e$ Appearance) is a long baseline neutrino experiment designed to measure the oscillation of muon neutrinos to electron neutrinos over a distance of 810 km. NOvA uses a near and far detector to observe $\nu_\mu$ disappearance and $\nu_e$ appearance of neutrinos produced by the NuMI beam at Fermilab. NOvA uses a Bayesian analysis framework in addition to its Frequentist method to measure neutrino oscillation parameters such as the mixing angles, mass ordering, and CP-violating phase. We report preliminary results of Bayesian fits to representative NOvA datasets. Comparison of fits to $\nu_\mu$ disappearance and $\nu_e$ appearance enables a cross-check of NOvA results with reactor $\bar{\nu_e}$ disappearance measurements. NOvA also searches for violation of Lorentz invariance by analyzing fits of forward horn current (FHC) versus reverse horn current (RHC) samples. The results validate and advance NOvA's contributions to precision measurements of neutrino properties.
Zhao, Larry [Fermilab]↗
NOvA Recent Results of Three-Flavor Oscillation Analysis
The NOvA experiment is a long-baseline neutrino experiment designed to study the oscillation behavior of neutrinos and antineutrinos, utilizing Fermilab’s Megawatt-capable NuMI neutrino beam. Over the past 10 years, NOvA has collected data from two functionally identical tracking calorimeter detectors, which are situated off the NuMI beam axis and separated by 810 km. The construction of the experiment enables observation of muon (anti)neutrino disappearance and electron (anti)neutrino appearance. Consequently, precision measurements of oscillation parameters, including the mass splitting $\Delta m_{32}^{2}$ and its sign, the mixing angle $\theta_{23}$, and the phase of $CP$-symmetry violation, can be obtained. This paper presents an overview of the NOvA experiment and its latest results.
Kalitkina, Anastasiia [Dubna, JINR]↗
Joint neutrino oscillation analysis from the T2K and NOvA experiments
The landmark discovery that neutrinos have mass and can change type (or flavour) as they propagate—a process called neutrino oscillation—has opened up a rich array of theoretical and experimental questions being actively pursued today. Neutrino oscillation remains the most powerful experimental tool for addressing many of these questions, including whether neutrinos violate charge-parity (CP) symmetry, which has possible connections to the unexplained preponderance of matter over antimatter in the Universe. Oscillation measurements also probe the mass-squared differences between the different neutrino mass states (Δ$m^2$), whether there are two light states and a heavier one (normal ordering) or vice versa (inverted ordering), and the structure of neutrino mass and flavour mixing. Here we carry out the first joint analysis of datasets from NOvA and T2K, the two currently operating long-baseline neutrino oscillation experiments (hundreds of kilometres of neutrino travel distance), taking advantage of our complementary experimental designs and setting new constraints on several neutrino sector parameters. This analysis provides new precision on the $Δm_{32}^2$ mass difference, finding $-2.43_{−0.03}^{+0.04}$ x $10^{-13}$ $\textrm{eV}^2$ in the normal ordering and $-2.43^{+0.03}_{-0.04}$ x $10^{-13}$ $\textrm{eV}^2$ in the inverted ordering, as well as a 3σ interval on δ CP of [−1.38π, 0.30π] in the normal ordering and [−0.92π, −0.04π] in the inverted ordering. The data show no strong preference for either mass ordering, but notably, if inverted ordering were assumed true within the three-flavour mixing model, then our results would provide evidence of CP symmetry violation in the lepton sector.
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First Joint Oscillation Analysis of Super-Kamiokande Atmospheric and T2K Accelerator Neutrino Data
The Super-Kamiokande and T2K Collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of 19.7(16.3) × 10 20 protons on target in (anti)neutrino mode, the analysis finds a 1.9𝜎 exclusion of 𝐶𝑃 conservation (defined as 𝐽 𝐶𝑃 = 0) and a 1.2𝜎 exclusion of the inverted mass ordering.
Neutrino detection↗
Feedback and Oscillations: Constructing Feedback Systems for Root Cause Analysis of Oscillations in Power Grids
Dynamic phenomena linked to inverter-based resources (IBRs) have gained global attention. Several IBR-induced dynamics have caused bulk power system-connected wind or solar power plants to trip, and some have even led to widespread outages. In addition, many oscillations have been observed involving IBR power plants. In 2023, the IEEE Power & Energy Society (PES) IBR Subsynchronous Oscillations (SSO) task force published a journal article, “Real-World Subsynchronous Oscillation Events in Power Grids With High Penetrations of Inverter-Based Resources,” in which 19 IBR oscillation events were examined for their causation. Earlier in 2020, another PES task force article, “Definition and Classification of Power System Stability-Revisited & Extended,” authored by prominent academics, introduced converter-driven stability as a new category of stability. The international power grid industry community also took action by publishing the CIGRE Green Book, Power System Dynamic Modelling and Analysis in Evolving Networks (led by Babak Badrzadeh and Zia Emin) in 2024. In August 2024, the Energy Systems Integration Group (ESIG) released a practical guide led by Nick Miller, “Diagnosis and Mitigation of Observed Oscillations in IBR-Dominant Power System: A Practical Guide.” The goal of the guide is to assist practicing engineers in making initial judgments and conducting detailed analyses about oscillations. Finally, when addressing the classification of stability and oscillations, the guide emphasizes a causality-based taxonomy for grouping, such as voltage control-induced oscillations, synchronization-induced oscillations, and frequency or active power control-induced oscillations.
Fan, Lingling [Univ. of South Florida, Tampa, FL (↗
A Twin Circuit Theory-Based Framework for Oscillation Event Analysis in Inverter-Dominated Power Systems With Case Study for Kaua‘i System
Here, this paper proposes a real-world oscillation event analysis framework for power systems that include inverter-based resources together with synchronous generators. Specifically, the proposed framework combines both measurement-and model-based techniques to readily identify potential oscillation sources, replay the oscillation event with numerical simulation, unveil the underlying oscillation mechanism, and suggest mitigation methods for a wide range of oscillation events. To strengthen the theoretical foundation of our analysis framework, this paper proposes a twin circuit theory that provides theoretical support for one key utilized but not well-proven measurement-based oscillation source identification method-Dissipating Energy Flow. Our twin circuit theory also shows that adopting well-tuned grid-forming inverters can be a potential mitigation method for oscillation events. Finally, the effectiveness of our proposed oscillation event analysis framework is demonstrated by addressing a real-world 18-20 Hz oscillation event in Kaua‘i's power system on November 21, 2021.
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A Unified Tracer Analysis of DESI DR2 Baryon Acoustic Oscillations
We improve upon previous efforts to optimally combine overlapping galaxy samples in the DESI baryon acoustic oscillation analysis. By weighting each galaxy by its linear bias, overlapping galaxies are combined into a single, unified catalog, naturally avoiding double counting of cosmic volume and including all auto- and cross- information at the catalog level. Improvements over the previous effort include the addition of QSO out to $z=1.6$ to account for all overlapping DR2 tracers and redshift-dependent bias treatment to improve reconstruction. We report distance measurements using this unified tracer, and find them to be highly consistent with the baseline DR2 BAO analysis. We also test for tracer-dependent systematics within the DESI data, and find no evidence of tracer-dependent systematics within $0.8
Sanders, N. [Ohio U., Athens] (ORCID:0009000800202↗
Machine learning neutrino-nucleus cross sections
Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries—can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Machine Learning Neutrino-Nucleus Cross Sections
Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries— can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.
Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗
Event Selections in the NOvA 2024 Analysis
The NuMI Off-axis $\nu_e$ Experiment (NOvA) is a long-baseline neutrino oscillation experiment that studies a neutrino beam produced by the Neutrinos at the Main Injector (NuMI) facility at Fermilab to constrain the PNFS mixing angles, the neutrino mass hierarchy, and the CP-violating phase $\delta_{CP}$. These parameters are extracted by comparing the spectra of muon neutrinos and electron neutrinos measured at the near and far detectors, using an extrapolation of the Near Detector spectra. Accurate event selection is critical to this process, as only interactions with well-reconstructed energies and interaction types should be included in the oscillation analysis to reduce systematic uncertainties. In this work, we describe the selection criteria used for muon and electron neutrinos in the Near and Far Detector. We demonstrate the effectiveness of the criteria by examining the efficiency and purity of the event selections as well as their impact on key variables used in the oscillation analysis.
Chen, Hanyi [Indiana U.]↗
NOvA in 10 Minutes
NOvA is a long-baseline neutrino oscillation experiment based at Fermilab, IL, USA, that observes $\nu_\mu \ (\bar{\nu}_\mu) \to \nu_\mu\ (\bar{\nu}_\mu)$ disappearance and $\nu_\mu \ (\bar{\nu}_\mu) \to \nu_e \ (\bar{\nu}_e)$ appearance oscillations from a beam of muon neutrinos (anti-neutrinos) provided by the Fermilab's NuMI beamline. The experiment consists of two functionally identical active liquid scintillattor tracking calorimeters, both situated 14.6 mrad off-axis to the beam direction. The detectors are made out of extruded PVC cells arranged in alternating horizontal and vertical planes for 3-dimensional reconstruction of neutrino events. The NOvA experiment has a wide-ranging scientific program that includes studying standard 3-flavor neutrino oscillations, resolution of neutrino mass orderings, measuring the CP-violating phase, $\delta_{CP}$, beyond standard model (BSM) phenomenon such as non-standard interactions (NSI) and sterile neutrino searches, neutrino-nucleus cross-section measurements, exotics, astrophysics and more. The NOvA experiment leverages its identical detector technology to mitigate systematic uncertainties for its neutrino oscillation analysis. This talk will provide an overview of the experiment's detector design and the data-driven techniques used by the experiment in its neutrino oscillation analysis.
Choudhary, Brajesh [Delhi U.]↗
Reconstruction of atmospheric neutrinos in DUNE’s horizontal-drift far-detector module
This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment’s (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC) with horizontal drift (FD-HD) of ionization electrons. The reconstruction is based upon the workflow developed for DUNE’s long-baseline oscillation analysis, with some necessary machine-learning models’ retraining and the addition of features relevant only to atmospheric neutrinos such as the neutrino direction reconstruction. Where relevant, the impact of the detection of the charged particles of the hadronic system is emphasized, and comparisons are carried out between the case when lepton-only information is considered in the reconstruction (as is the case for many neutrino oscillation experiments), versus when all particles identified in the LArTPC were included. Three neutrino direction reconstruction methods have been developed and studied for the atmospheric analyses: using lepton-only information, using all reconstructed particles, and using only correlations from reconstructed hits. The results indicate that incorporating more than just lepton information significantly improves the resolution of both neutrino direction and energy reconstruction. The angle reconstruction algorithms developed in this work result in no strong dependence on particle direction for reconstruction efficiencies or neutrino flavor identification. This comprehensive review of the reconstruction of atmospheric neutrinos in DUNE’s FD-HD LArTPC is the first step towards developing a first neutrino oscillation sensitivity analysis, which will ready DUNE for its first measurements.
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PISCES two-detector covariance matrix fit for the NOvA Experiment
NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA's primary physics goals are the precise measurements of neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ , determine the neutrino mass ordering, and constrain the value of $\delta_{CP}$, via the study of muon neutrino to electron neutrino oscillation. In the standard NOvA three-flavor analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data constrain the FD prediction through a ratio method. While this allows for systematic uncertainties sharing the same effects in both detectors to cancel, it remains an FD-only fit and does not fully leverage the constraining power of the high-statistics ND. This analysis proposes a simultaneous ND+FD fit using the PISCES method. PISCES (Parameter Inference with Systematic Covariance and Exact Statistics) is a framework designed to support complex configurations such as a joint ND+FD fit. This allows PISCES to take full advantage of the ND data to directly constrain systematic uncertainties across all samples. In PISCES, systematic uncertainties are encoded in a fractional covariance matrix, and statistical uncertainties are handled with a Poisson likelihood, making the approach well suited for low-statistics samples. For interpretability, we further use a Newton–Raphson + PCA method to recover per-systematic pulls from the covariance formulation. This poster presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, describes its implementation and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method.
Rajaoalisoa, Miriama [Cincinnati U.] (ORCID:000000↗
Measurements of three-flavor neutrino oscillations from a PISCES two-detector fit to the NOvA Experiment data
NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA s primary physics goals are to measure the neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ with high precision, determine the neutrino mass hierarchy, and constrain the value of $\delta_{CP}$, primarily via the study of muon neutrino to electron neutrino oscillation. Extracting values for oscillation parameters from fits to data usually relies on treating systematic uncertainties as nuisance parameters, a strategy that suffers from poor scalability as the number of uncertainties becomes larger. This work introduces PISCES (Parameter Inference with Systematic Covariance and Exact Statistics), a novel method that circumvents this scalability problem by encoding systematic uncertainties into a covariance matrix. PISCES utilizes a nested minimization in which optimal systematic pulls are first computed using the covariance matrix in an inner minimization step, then the oscillation parameters are profiled over in the outer minimization. PISCES also uses a Poisson Likelihood term, making it ideal for the inclusion of low-statistic samples in the fits. PISCES is a flexible framework that also supports complex fits, such as a joint Near and Far detector fit. In the standard NOvA analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data indirectly constrain the FD prediction via a ratio method. PISCES, on the other hand, enables a simultaneous ND+FD fit, allowing the high-statistics ND data to directly constrain systematic uncertainties across all samples. This thesis presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, details its implementation, and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method using the full NOvA 10-year data set. The results demonstrate that PISCES can successfully fit NOvA data while incorporating the constraints from the ND detectors consistently, using physically motivated systematic uncertainties to account for data/MC discrepancies.
Rajaoalisoa, Miriama [Cincinnati U.]↗
Final Search for Short-Baseline Neutrino Oscillations with the PROSPECT-I Detector at HFIR
The PROSPECT experiment is designed to perform precise searches for antineutrino disappearance at short distances (7–9 m) from compact nuclear reactor cores. This Letter reports results from a new neutrino oscillation analysis performed using the complete data sample from the PROSPECT-I detector operated at the High Flux Isotope Reactor in 2018. The analysis uses a multiperiod selection of inverse beta decay neutrino interactions with reduced backgrounds and enhanced statistical power to set limits on electron neutrino disappearance caused by mixing with sterile neutrinos with 0.2–20 eV 2 mass splittings. Inverse beta decay positron energy spectra from six different reactor-detector distance ranges are found to be statistically consistent with one another, as would be expected in the absence of sterile neutrino oscillations. The data excludes at 95% confidence level the existence of sterile neutrinos in regions above 3 eV 2 previously unexplored by terrestrial experiments, including all space below 10 eV 2 suggested by the recently strengthened Gallium Anomaly. The best-fit point of the Neutrino-4 reactor experiment’s claimed observation of short-baseline oscillation is ruled out at more than 5 standard deviations.
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