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DOE OSTI2025

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 Standard Model symmetries -- can be learned from near-detector data. We then perform a neutrino oscillation analysis with simulated far-detector events, finding that the modeled cross section achieves results consistent with what could be obtained if the true cross section were known exactly. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

Wagman, Michael L. [Fermilab] (ORCID:0000000176701↗
DOE OSTI2025

Recent results from MicroBooNE

Modelling and reconstructing neutrino-nucleus scattering is difficult, but it is crucial to do it precisely to enable next-generation oscillation measurements. Liquid argon time projection chambers (LArTPCs), such as MicroBooNE, can be the tool for this job as they are excellent precision neutrino detectors with their ability to produce detailed three-dimensional interaction images and precise energy and spatial resolution. MicroBooNE currently possesses the world's largest neutrino-argon scattering data set collected over five years using the BNB and NuMI neutrino beams at Fermilab. The experiment has performed measurements over a broad range of physics topics including neutrino argon cross sections, searches for BSM physics, and investigations of the MiniBooNE LEE excess. Many of these measurements are essential for improving the modelling of nuclear effects for both MicroBooNE and future LArTPC neutrino experiments, such as DUNE. This talk will give an overview of recent MicroBooNE results, the analysis techniques that enable them, and prospects for future measurements.

Parkinson, Holly B. [U. Edinburgh (main)] (ORCID:0↗
DOE OSTI2022

Evolution of HEP Processing Frameworks

HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of their large-scale data processing needs. Data-processing frameworks are being faced with new challenges this decade. The computing landscape has changed from the past three decades of homogeneous single-core x86 batch jobs running on grid sites. Frameworks must now work on a heterogeneous mixture of different platforms: multi-core machines, different CPU architectures, and computational accelerators; and different computing sites: grid, cloud, and high-performance computing. We describe these challenges in more detail and how frameworks may confront them. Given their historic success, frameworks will continue to be critical software systems that enable HEP experiments to meet their computing needs. Frameworks have weathered computing revolutions in the past; they will do so again with support from the HEP community

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

CHARGED-CURRENT DOUBLE-DIFFERENTIAL CROSS SECTION MEASUREMENT OF ELECTRON NEUTRINOS IN LOW RECOIL REGION ON HYDROCARBON AT ∼7 GEV

Measuring neutrino mixing angles, especially the CP violation phase and mass hierarchy, is one of the priorities of the neutrino community and long baseline neutrino oscillation programs, such as T2K and NOvA, provided the most precise measurements to date. One of the dominating uncertainties of the measurements is the neutrino interaction model due to the difficulty of modeling the nuclear effects from first principles. As a result, neutrino scattering experiments such as MINERvA were conducted to provide data as input to reduce this uncertainty. This thesis presents a charged-current double-differential cross section measurement of electron neutrinos using the MINERvA detector in terms of available energy (a proxy of energy transfer), three-momentum transfer, and/or transverse momentum of the final state electron. This measurement focuses on the transition region between quasi-elastic and resonance processes, where the multi-nucleon knockout process dominates. The result is compared to a modified GENIE model and similar measurements using muon neutrino samples. In addition, this measurement reproduces the photon-like excess seen by previous MINERvA electron neutrino measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

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↗
DOE OSTI2026

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↗
DOE OSTI2026

Developing New Beam Constraints to Improve Sterile Neutrino Searches at NOvA

NOvA is a long-baseline neutrino oscillation experiment utilizing two functionally identical liquid scintillator detectors located 14 mrad off-axis from the NuMI beam at Fermilab. The position of the Near Detector (ND), 1 km from the neutrino production target, means it sees a range of off-axis angles (12.6-17.2 mrad), resulting in a noticeable energy gradient across the detector face. In addition, the neutrino production points vary widely along the decay pipe, which leads to a distribution of true neutrino baselines (L), and limits the sensitivity of our current sterile neutrino searches. This work presents a new "baseline reconstruction" technique designed to exploit our off-axis position to triangulate the precise origin of neutrinos within the NuMI beamline. By projecting the total momentum vector of Charged Current (CC) and Neutral Current (NC) interactions back to the central beam axis, we estimate the individual baseline for each event. We describe the technique, evaluate its performance, and demonstrate how this can improve the sensitivity of future searches for sterile neutrinos through reduced flux systematic uncertainties and improved L/E resolution.

Burns, Jessica [Cincinnati U.]↗
DOE OSTI2024

Physics Potential of a Future Large n Detector in Korea

The demand for underground labs for neutrino and rare event search experiments has been increasing over the last few decades. Yemilab, constructed in October 2022, is the first deep (1~km) underground lab dedicated to science in Korea, where a large cylindrical cavern (D: 20~m, H: 20~m) was excavated in addition to the main caverns and halls. The large cavern could be utilized for a low background neutrino experiment by a liquid scintillator-based detector (LSC) where a 2.26 kiloton LS target would be filled.It's timely to have such a large but ultra-pure LS detector after the shutdown of the Borexino experiment so that solar neutrinos can be measured much more precisely. Interesting BSM physics searches can be also pursued with this detector when it's combined with an electron linac, a proton cyclotron (IsoDAR source), or a radioactive source. This talk discusses the concept of a candidate detector and the physics potential of a large liquid scintillator detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Search for Electron Neutrinos in Multiple Topologies with the MicroBooNE Experiment

This note presents the status of the measurement of electron neutrinos from the Fermilab Booster Neutrino Beamline (BNB) with the MicroBooNE experiment. The analysis is aimed at investigating the nature of the low energy excess of electromagnetic activity observed by the MiniBooNE experiment. The $ν_e$ event selection relies on topological and calorimetric information to characterise particles produced in these interactions, leveraging the Pandora multi-algorithm reconstruction framework as well as custom particle identification and pattern recognition tools. Results presented in this note use 5.88 × 10 20 protons on target of data collected between 2015 and 2018. These include the performance of particle identification tools for $\mu/p$ and $e/\gamma$ separation, along with electromagnetic shower calibration with the largest sample of $\pi^0$ events measured on argon. Progress towards the completion of this analysis is shown through the measurement of high-energy charged-current $ν_e$ interactions and their kinematic distributions using both inclusive (1eX) and exclusive (1$e$0$p$0$\pi$ and 1$e$N$p$0$\pi$) channels. Measurements of charged-current $ν_µ$ interactions aimed at constraining flux and cross-section systematic uncertainties are also shown. We present the analysis’ preliminary sensitivity of an electron-like signal hypothesis to the MiniBooNE excess which includes flux, cross-section, and detector systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Prospects for Light Dark Matter Searches at Large-Volume Neutrino Detectors

We propose a new approach to search for light dark matter (DM), with keV–GeV mass, via inelastic nucleus scattering at large-volume neutrino detectors such as Borexino, DUNE, Super-K, Hyper-K, and JUNO. The approach uses inelastic nuclear scattering of cosmic-ray boosted DM, enabling a low-background search for DM in these experiments. Large neutrino detectors, with higher thresholds than dark matter detectors, can be used, since the nuclear deexcitation lines are O ( 10 ) MeV . Using a hadrophilic dark-gauge-boson-portal model as a benchmark, we show that the nuclear inelastic channels generally provide better sensitivity than the elastic scattering for a large region of light DM parameter space. Published by the American Physical Society 2024

Dutta, Bhaskar↗
DOE OSTI2024

Photo- and Electro-Induced Hadron Production from Nuclei at Jefferson Laboratory

Understanding many-body knockout processes is crucial for nuclear physics, particularly in photo- and electro-induced reactions. In turn, understanding two- and three-body forces, including higher-order forces, is vital for a complete understanding of atoms. We present photo-induced many-proton knockout processes, with multiplicities from 1 to 6, using 12C, CH2, and C4H9OH targets in the g9a FROST dataset. Our analysis covers photon energies from 600 to 4500 MeV, significantly expanding current world data. Comparing our experimental data to the state-of-the-art GiBUU model offers a new challenge in the model’s theoretical description of many-body processes. GiBUU reasonably describes the data at lower photon energies but struggles at higher energies and missing masses, likely due to missing processes, such as initial 3-pion photoproduction. Our results will inform future developments in describing proton knockout processes, indicating GiBUU’s overall reasonable description of many-proton knockout data up to around 2.2 GeV. We also assess various electro-induced reactions using 2D, 12C, and 40Ar targets in the RGM dataset. Our results, obtained at electron beam energies of 2, 4, and 6 GeV, are compared in detail to GENIE and GiBUU, two widely used theory models in neutrino oscillation experiments. Discrepancies between model predictions and experimental data underscore the need for refining the two theoretical models. Despite discrepancies, GiBUU provides a more accurate modelling of electro-induced reactions, especially for 40Ar - crucial for future neutrino oscillation facilities such as DUNE. Understanding the fundamental nuclear physics involved in neutrino-nuclei interactions is essential for reducing the systematic uncertainties in extracting neutrino oscillation parameters. Many-body processes significantly contribute to the background processes observed in neutrino-nuclei interactions, hence the results from both analyses are crucial for developing the theoretical framework for the underlying nuclear physics.

Williams, Rhidian↗
DOE OSTI2025

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.]↗
DOE OSTI2025

Neutrino-nucleus cross section impacts on neutrino oscillation measurements

The challenges in neutrino-nucleus cross section modeling and its impact on neutrino oscillation experiments are widely recognized. However, a comprehensive and theoretically robust estimation of cross section uncertainties has been lacking, and few studies have quantitatively examined their impact on oscillation measurements. In this work, we evaluate the effect of cross section uncertainties on oscillation parameters using setups inspired by NOvA and DUNE. To characterize these uncertainties, we adopt multiple neutrino-nucleus event generators and simulate a realistic experimental procedure that incorporates near-detector data and near-to-far-detector extrapolation. Our results confirm that cross section uncertainties cannot significantly bias oscillation results in current statistics-dominated experiments like NOvA. However, they could lead to substantial bias for future systematics-dominated experiments like DUNE, even when near-detector data are employed to mitigate uncertainties. These findings underscore the need for further studies on the quantitative impacts of cross section modeling, improved strategies to utilize near-detector data and the PRISM concept, and more robust cross section models to optimize the success of future experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

The DUNE Photon Detection System

DUNE is an underground neutrino oscillation experiment that will be performing precision measurements of the PMNS matrix to determine unambiguously the mass ordering and the leptonic CP violation. It also comprises a rich non-accelerator physics program for the detection of supernova neutrinos, nucleon decay, and BSM physics. DUNE employs a high-power neutrino beam under construction at Fermilab together with the DUNE Near Detector, and four liquid argon TPCs (Far Detector) that will be installed at the Sanford Underground Research Facility in South Dakota, 1300 km away from the neutrino source. The photon detection system (PDS) – which records the 128 nm scintillation light of argon and provides the time of interaction of the beam neutrinos in the Far Detector - is critical for studying nucleon decay and detecting Supernova Neutrino Bursts. The PDS also complements the calorimetric measurement performed by the TPC (i.e. the charge readout) and contributes to the energy calibration and time performance of the Far Detector. The article is an overview of the design of the PDS for the first DUNE far detector module, with special emphasis on VUV light trapping in a cryogenic environment, its technical challenges, and the expected physics performance. The status of the construction of the PDS and its validation in the Run II of ProtoDUNE-SP will be also presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

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.]↗
DOE OSTI2022

Characterization of the correlated background for a sterile neutrino search using the first dataset of the JSNS$^2$ experiment

JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment that is searching for sterile neutrinos via the observation of ν¯ μ → ν¯ e appearance oscillations using muon decay-at-rest neutrinos. Before dedicated data taking in the first-half of 2021, we performed a commissioning run for 10 days in June 2020. Using the data obtained in this commissioning run, in this paper, we present an estimate of the correlated background which imitates the ν¯ e signal in a sterile neutrino search. In addition, in order to demonstrate future prospects of the JSNS 2 experiment, possible pulse shape discrimination improvements towards reducing cosmic ray induced fast neutron background are described.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

First neutrino + antineutrino disappearance results from NOvA

NOvA is a long-baseline neutrino oscillation experiment measuring νμ \nu_{\mu} disappearance and νe \nu_e appearance within the NuMI beam from Fermilab. The experiment uses a Near and a Far Detector placed 810 km away from each other and at 14 milliradians off the beam-axis resulting in an observed energy spectrum that peaks at 2 GeV, close to the oscillation maximum. A combined νμ \nu_{\mu} + ν¯μ \bar\nu_{\mu} disappearance result will be presented including NOvA's first collected anti-neutrino data for a total exposure of 16×1020 16\times10^{20} protons-on-target which, in addition to an upgraded analysis, will enable the experiment to set new limits to the allowed regions for Δm232 \Delta m^2_{32} and sin2θ23 ^2\theta_{23} and make a measurement of Δm232 \Delta m^2_{32} among the world's best.

Mendez, Diana Patricia [Sussex U.]↗
DOE OSTI2023

Hybrid Detector (Final Technical Report)

We report updates since the first demonstration of a phonon-mediated silicon detector technology that provides a primary phonon measurement in a low-voltage region, and a simultaneous indirect measurement of the ionization signal through Neganov–Trofimov–Luke amplification in a high voltage region, both in a monolithic crystal. We present characterization of charge and phonon transport between the two stages of the detector and the resulting background discrimination capability at low energies. This new detector technology has the potential to significantly enhance the sensitivity of dark matter and coherent neutrino scattering experiments beyond the capabilities of current technologies that have limited discrimination at low energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗