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DOE OSTI2024

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a “Module of Opportunity”, aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Snowmass Neutrino Frontier: DUNE Physics Summary

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment with a primary physics goal of observing neutrino and antineutrino oscillation patterns to precisely measure the parameters governing long-baseline neutrino oscillation in a single experiment, and to test the three-flavor paradigm. DUNE's design has been developed by a large, international collaboration of scientists and engineers to have unique capability to measure neutrino oscillation as a function of energy in a broadband beam, to resolve degeneracy among oscillation parameters, and to control systematic uncertainty using the exquisite imaging capability of massive LArTPC far detector modules and an argon-based near detector. DUNE's neutrino oscillation measurements will unambiguously resolve the neutrino mass ordering and provide the sensitivity to discover CP violation in neutrinos for a wide range of possible values of $\delta_{CP}$. DUNE is also uniquely sensitive to electron neutrinos from a galactic supernova burst, and to a broad range of physics beyond the Standard Model (BSM), including nucleon decays. DUNE is anticipated to begin collecting physics data with Phase I, an initial experiment configuration consisting of two far detector modules and a minimal suite of near detector components, with a 1.2 MW proton beam. To realize its extensive, world-leading physics potential requires the full scope of DUNE be completed in Phase II. The three Phase II upgrades are all necessary to achieve DUNE's physics goals: (1) addition of far detector modules three and four for a total FD fiducial mass of at least 40 kt, (2) upgrade of the proton beam power from 1.2 MW to 2.4 MW, and (3) replacement of the near detector's temporary muon spectrometer with a magnetized, high-pressure gaseous argon TPC and calorimeter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. Refined nuclear interaction models in these energy regimes will also be valuable for other applications, such as measurements of reactor, solar, and atmospheric neutrinos. This manuscript discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. This white paper discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Recent Progress in Low-Energy Neutrino-Nucleus Interactions Physics

Tens of MeV neutrinos, such as those from stopped pion or core-collapse supernova sources, interact with target nuclei in detectors through either coherent elastic or inelastic scattering processes. These interactions provide valuable insights into various Standard Model and Beyond the Standard Model phenomena, with significant implications for nuclear physics, particle physics, and astrophysics.The precision of coherent elastic scattering, where the nucleus remains in its ground state, depends on the accuracy of the underlying weak form factor of the nucleus. In contrast, inelastic scattering, where neutrinos excite the target nucleus to low-lying nuclear states, involves complex nuclear structures and dynamics and are quite poorly constrained. Moreover, these low-energy processes also have implications for neutrino-nucleus scattering of GeV energy neutrino beams. In this talk, I will present an overview of the field, highlight recent advancements, and outline future directions.

Pandey, Vishvas↗
DOE OSTI2026

Protons in the NOvA Test Beam

The NOvA (NuMI Off-Axis electron neutrino Appearance) Experiment is a long-baseline neutrino oscillation experiment composed of two functionally identical detectors, a 300 ton Near Detector, and a 14 kton Far Detector separated by 809 km and placed 14 mrad off the axis of the NuMI neutrino beam created at Fermilab. This configuration enables NOvA's rich neutrino physics program, which includes measuring neutrino mixing parameters, determining the neutrino mass hierarchy, and probing CP violation in the leptonic sector. The NOvA Test Beam experiment deployed at Fermilab between 2018 and 2022 used a scaled-down 30 ton detector to analyse tagged beamline particles. The beamline selected and identified electrons, muons, pions, kaons, and protons with momenta ranging from 0.4 to 1.8 GeV/c, as understanding how the detector responds to these particles found in the final state of neutrino interactions is crucial. This poster shows preliminary results from studies of proton response in the NOvA Test Beam detector.

Bannister, Emerson [Sussex U.] (ORCID:000000027535↗
DOE OSTI2025

Searching for Sterile Neutrinos In the NOvA Experiment and Measurements of Hadronic Energy Response with NOvA Test Beam Data

The NOvA (NuMI Off-Axis electron neutrino Appearance) experiment is a long-baseline neutrino oscillation experiment composed of two functionally identical detectors: a 300-ton Near Detector and a 14-kton Far Detector, separated by 809 km and placed 14 mrad off the axis of the NuMI neutrino beam created at Fermilab. This configuration enables NOvA’s rich neutrino physics program, which includes measuring neutrino mixing parameters, determining the neutrino mass hierarchy, probing CP violation in the leptonic sector, studying neutrino cross sections, searching for sterile neutrinos, and more.\\ In this thesis I will present two independent analyses developed within the NOvA experiment. The first is a search for light sterile neutrino oscillations in the 3+1 framework using $\nu_\mu$-CC and NC samples from the NOvA Near and Far Detectors. Light sterile neutrinos are hypothetical neutral leptons that do not participate in the weak interactions but can mix with the three known active neutrinos: $\nu_e$, $\nu_\mu$, and $\nu_\tau$. Anomalous results, such as $\nu_e$/$\bar{\nu}e$ appearance in a $\nu_\mu$ ($\bar{\nu}_\mu$) beam observed by the MiniBooNE and LSND experiments, can be explained by the existence of sterile neutrinos. Thus, proving the existence of this type of neutrino is essential. The latest results of these searches in the NOvA experiment, along with contributions to this effort, will be presented.\\ The second is the first measurement of the pion energy response using data from the NOvA Test Beam experiment. The NOvA Test Beam experiment, deployed at Fermilab, uses a scaled-down 30-ton NOvA detector to analyze tagged beamline particles. The beamline can select and identify electrons, muons, pions, kaons, and protons with momenta ranging from 0.4 to 1.4 GeV/c. Pions are an important component of the hadronic system in neutrino interactions, and understanding how the detector responds to these particles is crucial for the validation of the simulation and the reduction of detector calibration uncertainties, which remain one of the largest systematic uncertainties in NOvA analyses.

Dueñas Tonguino, David Francisco [Cincinnati U.] (↗
DOE OSTI2022

Recent Results from the MINER$\nu$A experiment

In the era of the fastest-growing technology in the field of particle accelerators anddetectors, the scope of neutrino physics is expanding very rapidly. The neutrino oscilla-tion parameters are being measured with a higher degree of precision. The precision ofthese oscillation parameters directly depend on the neutrino-nucleus cross section mea-surements done by various experiments with multiple nuclear targets. One of these fewexperiments is the MINERνA, a dedicated neutrino-nucleus interaction experiment atFermilab which took data from 2009 to 2019 for both neutrino and antineutrino scatter-ing in the low-energy and medium energy peaking around 3 GeV and 6 GeV, respectively.This article will cover some recent inclusive measurements from the MINERνA experi-ment. These results will provide a strong basis for future experiments like DUNE andhelp in improving the measurement of neutrino oscillation parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Calibration strategy of the PROSPECT-II detector with external and intrinsic sources

This paper presents an energy calibration scheme for an upgraded reactor antineutrino detector for the Precision Reactor Oscillation and Spectrum Experiment (PROSPECT). The PROSPECT collaboration is preparing an upgraded detector, PROSPECT-II (P-II), to advance capabilities for the investigation of fundamental neutrino physics, fission processes and associated reactor neutrino flux, and nuclear security applications. P-II will expand the statistical power of the original PROSPECT (P-I) dataset by at least an order of magnitude. The new design builds upon previous P-I design and focuses on improving the detector robustness and long-term stability to enable multi-year operation at one or more sites. The new design optimizes the fiducial volume by elimination of dead space previously occupied by internal calibration channels, which in turn necessitates the external deployment. In this paper, we describe a calibration strategy for P-II. Here, the expected performance of externally deployed calibration sources is evaluated using P-I data and a well-benchmarked simulation package by varying detector segmentation configurations in the analysis. The proposed external calibration scheme delivers a compatible energy scale model and achieves comparable performance with the inclusion of an additional AmBe neutron source, in comparison to the previous internal arrangement. Most importantly, the estimated uncertainty contribution from the external energy scale calibration model meets the precision requirements of the P-II experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Snowmass Neutrino Frontier: Neutrino Interaction Cross Sections (NF06) Topical Group Report

A thorough understanding of neutrino cross sections in a wide range of energies is crucial for the successful execution of the entire neutrino physics program. In order to extract neutrino properties, long-baseline experiments need an accurate determination of neutrino cross sections within their detector(s). Since very few of the needed neutrino cross sections across the energy spectrum are directly measured, we emphasize the need for theoretical input and indirect measurements such as electron scattering, which would complement direct measurements. In this report we briefly summarize the current status of our knowledge of the neutrino cross sections and articulate needs of the experiments, ongoing and planned, at energies ranging from CEvNS and supernova neutrino energies to the DUNE and atmospheric neutrino energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Enforcing Self-Consistent Kinematic Constraints in Neutrino Energy Estimators

Machine learning algorithms have long been utilized across many experimental collaborations within the neutrino physics community in applications to ascertain the singular kinematic quantity of initial neutrino energy for use in neutrino oscillation analyses. However, most of these algorithms do not incorporate a coherent physical picture of initial neutrino kinematics, opting to introduce loss functions involving knowledge of only |pν |. Here, we argue for the introduction of composite loss functions utilizing the full kinematic description of the neutrino, pν ≡ (E, px, py , pz ), compiling all relevant energy and angle information consistently. The use of such a fully defined variable can be seen as a usage of Physics Informed Machine Learning.

Richi, R. R.↗
DOE OSTI2022

Neutrino Interaction Identification for the DUNE Trigger

The DUNE will be a long baseline neutrino oscillation experiment using a high purity muon neutrino beam and near detector, both located at the FNAL, and a far detector hosted 1300 km downstream at the SURF. The 10 kt fiducial mass of LAr will allow DUNE to have a rich off-beam neutrino physics programme, including the study of neutrino signals from core collapse supernovae. The SP DUNE FD module will read out ionisation data at a rate of 1.2 TB\textsuperscript{-1} whilst only a total data volume of 30 PB per year can be permanently stored. DUNE will make use of FPGA resources in the front-end of the DAQ as part of the necessitated triggering system. This thesis presents a validation study of the FPGA-based TPG in the front-end DAQ using data collected by the ProtoDUNE experiment hosted at the CERN. The FPGA-based TPG was utilised as the first stage of a baseline SNB trigger whose performance was evaluated using simulated neutrino interactions for a $11.2 m_\odot$ progenitor star. The efficiency of the baseline SNB trigger was determined to have a lower limit of $97.7\substack{+ 0.2\\ -0.3}\%$ for supernovae at a distance of 20kpc, achieving the technical requirements set out for DUNE. To improve the performance of the SNB trigger at greater SNB distances, the use of a bounding box proposal network, YOLOv3, was explored. This was found to improve the efficiency of the SNB trigger to 100\% up to the far side of the Milky Way galaxy and to $92.5\substack{+ 0.5\\ -0.5}\%$ at the Large Magellanic Cloud.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Precision spectroscopy of nuclear decays using quantum optomechanical sensors

This project developed and demonstrated a fundamentally new way to detect individual nuclear decays: rather than capturing the energy that decay products deposit in a detector, we measure the tiny mechanical recoil of the entire micron- or nanometer-sized particle in which the decaying nucleus is embedded. Because momentum is conserved, this approach is sensitive even to neutral, weakly interacting particles, including neutrinos, that escape conventional detectors. During the award, the Yale group reported the first-ever mechanical detection of single nuclear decays, a result featured widely in the scientific press, and pushed the sensitivity of smaller levitated nanoparticles into the quantum measurement regime, reaching an impulse resolution within a factor of five of the fundamental Standard Quantum Limit (SQL), good enough in principle to detect the momentum kicked to the particle by a single emitted neutrino. In parallel, the LBNL group developed the theory of quantum-enhanced (sub-SQL) readout tailored to this experiment, showing how squeezed light can push the sensitivity below the SQL. Together these results establish levitated optomechanical sensors as a new tool for precision nuclear decay spectroscopy, with further applications in neutrino physics, quantum metrology, and nuclear forensics and safeguards.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Understanding hadronic interactions using advanced reconstruction techniques

ProtoDUNE-SP served as the prototype of the future Deep Underground Neutrino Experiment (DUNE). With a total liquid argon mass of 0.77 kt, it stood as the most extensive monolithic single-phase Liquid Argon Time Projection Chamber (LArTPC) ever constructed. Strategically located and operated at CERN, ProtoDUNE-SP benefited from a specialized charged-particle test beam, offering a momentum range of 0.3 - 7 GeV/c. This setup provided a unique opportunity to conduct in-depth studies on hadronic interactions within argon. Hadronic interactions play a fundamental role in neutrino physics, particularly in the intricacies of neutrino detection. We depend on analyzing the outcomes of these interactions to accurately determine both the flavor and energy of the interacting neutrinos. Pions, as one of the primary byproducts of neutrino interactions, are crucial for understanding the overall dynamics and kinematics of these processes. Accurately characterizing and understanding the interaction of pions with argon can significantly enhance the precision of neutrino simulations and measurements.Being a Liquid Argon Time Projection Chamber (LArTPC), ProtoDUNE-SP is distinguished by its ability to produce high-definition images of charged particles as they traverse through the detector's active volume. Yet, accurately reconstructing these particle interactions and determining their kinematic attributes remains a challenging task. The successes of deep learning in diverse domains, especially in image recognition, provide a promising approach for addressing this challenge in ProtoDUNE. This thesis discusses a measurement of the Piplus - argon inelastic cross section in the energy range of 2400 to 3000 MeV, using data taken by protoDUNE during the fall of 2018. Additionally, panoptic segmentation, a machine learning technique, is introduced and validated through its application in the reconstruction of the neutral pion rest mass. The aim is to showcase how these advanced methods can enhance the quality of event reconstruction.

Sarasty Segura, Carlos Eduardo↗
DOE OSTI2024

Unleashing the power of EFT in neutrino-nucleus scattering

Neutrino physics is advancing into a precision era with the construction of new experiments, particularly in the few GeV energy range. Within this energy range, neutrinos exhibit diverse interactions with nucleons and nuclei. This study delves in particular into neutrino-nucleus quasi-elastic cross sections, taking into account both standard and, for the first time, non-standard interactions, all within the framework of effective field theory (EFT). The main uncertainties in these cross sections stem from uncertainties in the nucleon-level form factors, and from the approximations necessary to solve the nuclear many-body problem. We explore how these uncertainties influence the potential of neutrino experiments to probe new physics introduced by left-handed, right-handed, scalar, pseudoscalar, and tensor interactions. For some of these interactions the cross section is enhanced, making long-baseline experiments an excellent place to search for them. Our results, including tabulated cross sections for all interaction types and all neutrino flavors, can serve as the foundation for such searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The Core-collapse Supernova Sensitivity Machine (Final Technical Report)

Core-collapse supernovae are vital phenomena for understanding the extreme physics of stellar evolution, nuclear interactions, and the origins of elements in the universe. This project developed high-resolution 3D simulations and innovative 1D turbulence models to study the explosion mechanisms, yielding critical insights into the role of turbulence, magnetohydrodynamics, and neutrino physics. The outcomes include enhanced sensitivity analyses connecting nuclear physics inputs to observable supernovae characteristics, tools for the broader research community, and substantial contributions to the training of future scientists.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗