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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 OSTI2024

The DUNE Experiment

The Deep Underground Neutrino Experiment (DUNE) is a next generation long-baseline neutrino experiment built to answer some of the most fundamental questions in the universe. DUNE will consist of two neutrino detectors placed in the world’s most intense neutrino beam facility named as Long-Baseline Neutrino Facility (LBNF). It consists of a near detector and a far detector that is comprised initially of two modules and eventually of four modules, each of fiducial mass 17.5 ktons of liquid Argon. The far detector is located 1300 km from the beam source placed underground at the Sanford Underground Research Laboratory in Lead, South Dakota. DUNE will measure the un-oscillated neutrinos nucleus interactions at near detector and oscillated interactions at far detector which will be able to address the questions about the preponderance of matter over antimatter in the early universe, searches for leptonic charge-parity symmetry violation, proton decay, supernova neutrino bursts and unification of forces. This article discussed the goals and physics of the DUNE experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Computing for the DUNE Long-Baseline Neutrino Oscillation Experiment

This is a talk given at Computers in High Energy Physics in Adelaide, South Australia, Australia in November 2019. It is partially intended to explain the context of DUNE Computing for computing specialists. The DUNE collaboration consists of over 180 institutions from 33 countries. The experiment is in preparation now with commissioning of the first 10kT fiducial volume Liquid Argon TPC expected over the period 2025-2028 and a long data taking run with 4 modules expected from 2029 and beyond. An active prototyping program is already in place with a short test beam run with a 700T, 15,360 channel prototype of single-phase readout at the neutrino platform at CERN in late 2018 and tests of a similar sized dual-phase detector scheduled for mid-2019. The 2018 test beam run was a valuable live test of our computing model. The detector produced raw data at rates of up to ~2GB/s. These data were stored at full rate on tape at CERN and Fermilab and replicated at sites in the UK and Czech Republic. In total 1.2 PB of raw data from beam and cosmic triggers were produced and reconstructed during the six week test beam run. Baseline predictions for the full DUNE detector data, starting in the late 2020's are 30-60 PB of raw data per year. In contrast to traditional HEP computational problems, DUNE's Liquid Argon TPC data consist of simple but very large (many GB) 2D data objects which share many characteristics with astrophysical images. This presents opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

DUNE Software and Computing Challenges

The DUNE experiment will begin running in the late 2020's. The goals of the experiment include 1) studying neutrino oscillations using a beam of neutrinos from Fermilab in Illinois to the Sanford Underground Research Facility, 2) studying astrophysical neutrino sources and rare processes and 3) understanding the physics of neutrino interactions in matter. The DUNE Far Detector, consisting of four 17 kt LArTPC modules, will produce "events" rang-ing in size from 6 GBs to more than 100 TBs, posing unique challenges for DUNE software and computing. The data processing algorithms, particularly for raw data, drive the requirements for the future DUNE software framework documented here.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Scintillation light detection performance for the DUNE ND-LAr 2 × 2 modules

The Deep Underground Neutrino Experiment (DUNE) will be using a liquid argon time projection chamber (LAr TPC) with optically separated modules in the Near Detector (ND) complex. A prototype experiment, DUNE ND-LAr 2 × 2, is composed of four test modules. They detect ionization charge through a pixel-based readout and scintillation light through fibers in light collection modules and light traps called ArCLights. The light detection performance for two modules of DUNE ND-LAr 2 × 2 that took cosmic ray data at the University of Bern is shown. We present further the role of the 2 × 2 prototype in DUNE and how it is used to demonstrate the reconstruction capabilities of its light detectors in terms of energy thresholds and timing resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Status of DUNE Offline Computing

We summarize the status of Deep Underground Neutrino Experiment (DUNE) Offline Software and Computing program. We describe plans for the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes in pursuit of the experiment's physics goals of precision measurements of neutrino oscillation parameters, detection of astrophysical neutrinos, measurement of neutrino interaction properties and searches for physics beyond the Standard Model. In contrast to traditional HEP computational problems, DUNE's Liquid Argon Time Projection Chamber data consist of simple but very large (many GB) data objects which share many characteristics with astrophysical images. We have successfully reconstructed and simulated data from 4% prototype detector runs at CERN. The data volume from the full DUNE detector, when it starts commissioning late in this decade will present memory management challenges in conventional processing but significant opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing. Our goal is to develop infrastructure resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

DUNE Database Development

The DUNE experiment will produce vast amounts of metadata, which describe the data coming from the read-out of the primary DUNE detectors. Various databases will make up the overall DB architecture for this metadata. ProtoDUNE at CERN is the largest existing prototype for DUNE and serves as a testing ground for - among other things - possible database solutions for DUNE. The subset of all metadata that is accessed during offline data reconstruction and analysis is referred to as ‘conditions data’ and it is stored in a dedicated database. As offline data reconstruction and analysis will be deployed on HTC and HPC resources, conditions data is expected to be accessed at very high rates. It is therefore crucial to store it in a granularity that matches the expected access patterns allowing for extensive caching. This requires a good understanding of the sources and use cases of conditions data. This contribution will briefly summarize the database architecture deployed at ProtoDUNE and explain the various sources of conditions data. We will present how the conditions data is retrieved and streamed from the databases and how it is handled to match expected access patterns.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

One of the major scientific goals of the Deep Underground Neutrino Experiment (DUNE) is to detect and measure the neutrino flux from galactic core-collapse supernovae. These neutrinos, which exist in the low energy range of up to a few tens of MeV and are responsible for carrying away over 99% of the gravitational binding energy of the supernova, provide an opportunity to study the end of life evolution of massive stars, as well as unique properties and interactions of neutrinos. Because galactic supernovae are expected to occur only on the timespan of every few decades, it is crucial that DUNE is able to detect supernova neutrino interactions when they occur. However, detecting these supernova interactions requires sifting through a large amount of data, and DUNE detectors require a trigger to signal when supernova neutrino events occur. Machine learning provides a potential approach to creating this trigger. This project generates ADC and ground truth images of neutrino interactions in a LArTPC detector as simulated by the Model of Argon Reaction Low Energy Yields (MARLEY) to be used for machine learning. The eventual goal of this work is to facilitate DUNE s detection of supernova neutrino interactions by building a machine learning pipeline to train the trigger algorithm.

Damish, Stephanie↗
DOE OSTI2024

Signal discrimination for neutron-antineutron oscillation sensitivity study at DUNE

The Deep Underground Neutrino Experiment (DUNE) aims to measure neutrino oscillations as well as search for beyond the standard model physics such as baryon number violating (BNV) processes. DUNE will use a 70 kt Liquid Argon Time Projection Chamber (LArTPC) located more than 1 km underground. A promising BNV process is neutron-antineutron oscillation $\left(n\rightarrow\bar{n}\right)$ which, if discovered, would offer unique insight into the baryon asymmetry of the universe. We are developing a classification algorithm that separates $n\rightarrow\bar{n}$ events from major background atmospheric neutrino interactions using DUNE far detector simulations. We will perform the classification of signals and backgrounds by analyzing key features such as the multiplicity, isotropy, and kinematics of the reconstructed events. In the future, this algorithm can be used to obtain the sensitivity of the DUNE detectors to the neutron-antineutron oscillation lifetime.

Wheeler, Justin↗
DOE OSTI2025

Automating Testing of DUNE Electronics via a Finite State Machine

The Deep Underground Neutrino Experiment (DUNE) is a flagship international collaboration designed to study neutrinos—tiny, nearly massless particles that may hold answers to fundamental questions about the Universe. Fermilab’s Robotic Test Stand (RTS) plays a critical role in ensuring the quality of approximately 50,000 Application-Specific Integrated Circuit (ASIC) chips that will be used in DUNE’s massive liquid argon detectors. These electronics will be inside the cryostat; therefore, they will need to have a high yield of working chips and low noise. To improve the automation and reliability of the RTS, this project focused on designing and implementing a Python-based finite state machine (FSM) to manage chip handling workflows. The FSM was developed as a modular software framework to coordinate robotic arm movements, manage chip tray positions, and monitor system states during testing. Key features include robust error handling routines, a pause/resume system for safe mid-cycle interruptions, and a simulation mode for iterative testing without hardware dependencies. The system was designed to prepare for seamless integration with RTS hardware components such as the robotic arm and vision system. This integration will streamline collaboration and enable efficient deployment of updates across the six institutions performing testing. The outcomes of this internship contribute to Fermilab’s mission to advance high-energy physics and support the DOE’s national goals by directly improving the testing of equipment to be used in DUNE. The project also provided valuable experience in software design and contributing to the success of DUNE.

Kang, Caleb [Fermilab]↗
DOE OSTI2024

Perspectives for Measuring Neutrino Cross-Sections at Short Baseline Detectors (ICARUS and DUNE-PRISM-like Detector) and Their Implications for Precision Physics

Neutrino physics is rapidly advancing with current and future experiments promising high-statistics data, enabling unprecedented accuracy in measuring Standard Model (SM) parameters and providing crucial insights into neutrino-nucleus interactions. The ICARUS experiment, utilizing LAr TPC technology, is pivotal in this growth. As the far detector of the SBN program at Fermilab, ICARUS is set to investigate the neutrino anomalies observed in LSND and MiniBooNE and prepare for future long-baseline experiments like DUNE. Positioned along the BNB and 5.75°off-axis from the NuMI beamline, ICARUS benefits from numerous neutrino interactions, allowing for precise neutrino-argon nucleus cross-section measurements, which will benchmark future DUNE measurements. This work presents the prospects and progress in measuring the cross-section of the NuMI νµ CC inclusive channel in the ICARUS experiment. High-statistics data will also enable precise determinations of fundamental parameters like the weak mixing angle and the neutrino charge radius (NCR), crucial for testing the SM and exploring potential new physics. This work includes studies of future near detectors, such as DUNE-PRISM, which are sensitive to radiative corrections in neutrino-electron scattering. The DUNE-PRISM configuration allows for the analysis of different neutrino energy spectra, promising accurate NCR measurements with controlled systematic uncertainties.

Moreno-Granados, Guadalupe↗
DOE OSTI2025

Large Language Model Integration for Knowledge Retrieval and Interaction for the DUNE Experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment that will generate an unprecedented volume of heterogeneous information-from documentation and technical notes to experimental data and reconstruction pipelines. Efficient knowledge retrieval and contextual understanding are increasingly critical for collaboration-wide productivity and onboarding. In this work, we present DUNE-GPT, a prototype framework that leverages large language models (LLMs) and retrieval-augmented generation (RAG) to enable natural-language querying of DUNE's internal documentation and technical resources. The system provides an intelligent interface for DUNE collaborators to interact with experiment-specific knowledge while maintaining data privacy and infrastructure compliance within Fermilab computing resources.

Rafique, A. [Argonne (main)]↗
DOE OSTI2026

A Bayesian approach to the long-baseline neutrino oscillation sensitivity of DUNE

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible using a Bayesian approach. We present four-dimensional posterior probability distributions of the oscillation parameters, highlighting the breadth of correlation in the parameter space of interest, especially between $\sin^2 θ_{23}$ and $\sin^2 θ_{13}$. We exploit the flexibility of the Bayesian framework to incorporate parameter constraints post hoc and assess the impact of applying a reactor short-baseline $θ_{13}$ constraint. A significant increase in the sensitivity to the $θ_{23}$ octant is found when including the constraint. Posterior distributions of derived quantities can be easily constructed from MCMC results. This work presents the first study of DUNE's sensitivity to the Jarlskog invariant, $J$, a quantity that provides a parametrisation-independent measure of charge-parity violation in the leptonic sector.

Abbaslu, Saeed [IPM, Tehran] (ORCID:00000003356771↗
DOE OSTI2020

Mercury methylation potential in a sand dune on Lake Michigan's eastern shoreline

Lake Michigan hosts the largest freshwater sand dune system in the world and is economically important for the fishery industry and tourism. Due to industrial pollution and atmospheric mercury (Hg) deposition, toxic levels of methylmercury (MeHg) have been found in the Lake biota, but little information is known regarding MeHg sources and Hg methylation potential in the shoreline sand dunes. In this study, we conducted anaerobic incubation experiments with beach sands collected from Ludington, Michigan, and examined the effects of organic carbon substrate addition, inorganic nitrogen, and mineral magnetite on Hg methylation. Despite nutrient poor and low-organic carbon conditions, appreciable Hg methylation activity coupled with carbon degradation was observed in the sands. Addition of acetate as a carbon source substantially increased MeHg production from 2 to 380 ng/kg sediment while acetate was rapidly degraded in the first 19 days of incubation. Ammonium addition showed little influence on carbon degradation or Hg methylation, whereas iron oxide addition (~1% dry weight) significantly inhibited both carbon degradation and MeHg production (by up to 90%), highlighting strongly coupled interactions between microbes, carbon substrates, and minerals. This research demonstrates the potential of microbial Hg methylation in the sand dunes, which may play a role in MeHg input and bioaccumulation in the Lake Michigan ecosystem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

How to identify different new neutrino oscillation physics scenarios at DUNE

Next generation neutrino oscillation experiments are expected to measure the remaining oscillation parameters with very good precision. They will have unprecedented capabilities to search for new physics that modify oscillations. DUNE, with its broad band beam, good particle identification, and relatively high energies will provide an excellent environment to search for new physics. If deviations from the standard three-flavor oscillation picture are seen however, it is crucial to know which new physics scenario is found so that it can be verified elsewhere and theoretically understood. We investigate several benchmark new physics scenarios by looking at existing long-baseline accelerator neutrino data from NOvA and T2K and determine at what sensitivity DUNE can differentiate among them. We consider sterile neutrinos and both vector and scalar non-standard neutrino interactions, all with new complex phases, the latter of which could conceivably provide absolute neutrino mass scale information. We find that, in many interesting cases, DUNE will have good model discrimination. We also perform a new fit to NOvA and T2K data with scalar NSI.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluation of a high-performance storage buffer with 3D XPoint devices for the DUNE data acquisition system

The DUNE detector is a neutrino physics experiment that is expected to take data starting from 2028. The data acquisition (DAQ) system of the experiment is designed to sustain several TB/s of incoming data which will be temporarily buffered while being processed by a software based data selection system. In DUNE, some rare physics processes (e.g. Supernovae Burst events) require storing the full complement of data produced over 1-2 minute window. These are recognised by the data selection system which fires a specific trigger decision. Upon reception of this decision data are moved from the temporary buffers to local, high performance, persistent storage devices. In this paper we characterize the performance of novel 3DXPoint SSD devices under different workloads suitable for high-performance storage applications. We then illustrate how such devices may be applied to the DUNE use-case: to store, upon a specific signal, 100 seconds of incoming data at 1.5 TB/s distributed among 150 identical units each operating at approximately 10GB/s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Evolution of DUNE’s Production System

The DUNE experiment will start running in 2029 and record 30 PB/year of raw waveforms from Liquid Argon TPCs and photon detectors. The size of individual readouts can range from 100 MB to a typical 8 GB full readout of the detector, and even 100 TB for extended readouts from supernova candidates. These data then need to be cataloged, stored and distributed for processing worldwide. This massive amount of data and a heterogeneous computing environment necessitates a powerful and robust distributed computing infrastructure. In the process of building up that infrastructure, DUNE’s production system has recently undergone an overhaul, in which it has integrated 1) a new workflow management system (justIN) 2) a new data catalog (MetaCat) and 3) a state-of-the-art data management system (Rucio). Simulations of DUNE’s Far Detector and its prototypes ProtoDUNE Horizontal Drift (ProtoDUNE-HD) and ProtoDUNE Vertical Drift (ProtoDUNE-VD), as well as data from ProtoDUNE-HD serve as the first tests of this infrastructure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Hunting for light dark matter with DUNE PRISM

We present the prospects for exploring low-scale dark sectors with the future DUNE experiment and the impact of the movable off-axis near detector concept, DUNE-PRISM, and a higher energy beam configuration. We focus on a simple scenario which extends the Standard Model by a “dark” U(1), comprising scalar or fermion dark matter and a dark photon kinetically mixed with the photon. We consider nucleus and electron scattering signatures of dark matter produced in the beam via neutral pseudoscalar meson decays. Our results show that, by analysing the energy spectra of single electron events in multiple off-axis angle, DUNE-PRISM can substantially increase the experimental sensitivity to these models, reaching theoretical targets for thermal relic dark matter for a wide range of dark photon and dark matter masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗