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DOE OSTI2025

Performance of Muon Neutrino Reconstruction at ICARUS using SPINE Machine Learning.

ICARUS is a liquid argon time projection chamber (LArTPC) neutrino experiment at Fermilab. Located ~600 m from the Booster Neutrino Beam (BNB) target, it serves as the far detector in the Short-Baseline Neutrino (SBN) Program. The primary objective of the SBN Program is to probe neutrino oscillation physics at short baselines using multiple detectors, including measurements of both muon neutrino disappearance and electron neutrino appearance. A key requirement for the neutrino oscillation measurements is robust event reconstruction, including accurate and precise particle identification (PID) and kinematic reconstruction across a wide range of topologies. To achieve the required performance, we employ the SPINE (“Scalable Particle Imaging with Neural Embeddings”) package, a state-of-the-art machine learning reconstruction framework. This talk presents the status of muon neutrino reconstruction using SPINE at ICARUS, including the evaluation of reconstruction performance that will enable the full physics program at ICARUS and at the SBN Program.

Totani, Dante [Colorado State U.] (ORCID:000000019↗

DOE OSTI2025

Measurement of cross sections for mesonless charged-current muon neutrino interactions on argon with and without protons at MicroBooNE

urrent and upcoming neutrino experiments at Fermilab will rely on liquid argon time projection chambers (LArTPCs) as the primary detector technology. To reach the ambitious precision required for their physics goals, a detailed understanding of neutrino-argon scattering must be achieved. For the present Short-Baseline Neutrino program, the dominant reaction channel is charged-current muon neutrino interactions leading to mesonless final states with and without protons. Using a large data set of neutrino interactions recorded by the MicroBooNE LArTPC detector at Fermilab, we report progress towards new measurements of differential cross sections in this channel. The analysis leverages multiple event reconstruction paradigms and observables specifically chosen to maximize sensitivity to nuclear effects of interest for improving neutrino scattering models. Related previous cross-section results from MicroBooNE and a preview of what to expect from the new analysis will both be featured in this presentation.

Liu, Liang [Fermilab]↗

DOE OSTI2025

ArCS: A Magnetized LArTPC in a Test Beam

Over the past few decades, Liquid Argon Time Projection Chambers (LArTPCs) have emerged as a central technology for rare-event detection, due to their calorimetric and imaging capabilities. Adding a magnetic field to LArTPCs would enable charge identification and momentum measurements via curvature. For neutrino experiments, this is crucial for wrong-sign neutrino rejection, electron/positron and electron/photon discrimination, and improved momentum reconstruction. The ArCS (Argon detector with Charge Separation) experiment at Fermilab's Test Beam Facility will place a 47 40 90 cm LArTPC inside a 0.7 T magnet to: (i) establish charge sign discrimination for electrons and positrons, (ii) reconstruct particle momenta via curvature, and (iii) determine the minimal magnetic field needed for these measurements. This poster will present the project status, with updates on installation and simulations of expected performance.

Cicogna, Giulia [Bologna U.]↗

DOE OSTI2025

Finding Nuclear Clusters in the Short-Baseline Near Detector

Production of nuclear clusters such as deuterons, tritons, helions and alpha particles has only recently been simulated for neutrino-nucleus interactions, and has not yet been measured in neutrino experiments. The Short-Baseline Near Detector (SBND) is the first Liquid Argon Time Projection Chamber (LArTPC) with high enough resolution and a large enough neutrino flux to accurately measure the cross-section for the production of heavier-than-proton fragments in neutrino interactions. SBND is a 112-ton LArTPC, and lies 110 m downstream from the Booster Neutrino Beam target, where it has already collected the world's largest dataset of neutrino-argon interactions. In these processes, the intranuclear cascade and nuclear de-excitation stages can both produce nuclear clusters. With LArTPC technology's excellent reconstruction capabilities and SBND's unprecedented neutrino statistics, a measurement of these nuclear clusters could distinguish between nuclear models and improve neutrino energy reconstruction. This poster presents the status of simulation, reconstruction, and prospects for a measurement of nuclear clusters in SBND.

Beever, Anna [Sheffield U.] (ORCID:000900069339924↗

DOE OSTI2025

Modelling detector-specific reconstruction uncertainties in LAr-TPC

The Short-Baseline Neutrino (SBN) program features three Liquid Argon Time Projection Chamber (LAr-TPC) detectors positioned along the Booster Neutrino Beam (BNB) axis: the Short Baseline Neutrino Near Detector, MicroBooNE, and the ICARUS T600. As the largest operational LAr-TPC, ICARUS T600 serves as the far detector, located 600 m from the BNB target. While its primary goal is to record neutrino events, it also detects other ionizing events, including cosmic rays. This work focuses on analyzing and modeling detector-specific reconstruction uncertainties in LAr-TPC. These inefficiencies, identified during the Pattern Recognition phase handled by the PANDORA algorithm, impact subsequent Particle Fits and Offline Analysis. Specifically, inaccuracies in track reconstruction can lead to significant physical consequences, such as erroneous particle energy estimates and poor Particle Identification (PID), reducing the efficiency of neutrino event characterization. A key issue addressed is split tracks, caused by missing hits or incomplete track stitching by PANDORA. The aim of this internship is to characterize, model, and quantify the impact of split tracks on track reconstruction.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Optimizing TinyTPC Test Stand for Low Energy Event Reconstruction

Introducing dopants into liquid argon offers a promising avenue to enhance the sensitivity and performance of LAr detectors such as DUNE. To explore this opportunity, we are optimizing and deploying the TinyTPC test stand, a compact time projection chamber with LArPix readout to study the effects of photosensitive dopants on the charge detected. TinyTPC enables comparative measurements of low-energy responses under various operational configurations and provides a platform to study the behavior of pixel readouts at low energy. We ensured system reliability through continuous current and voltage monitoring, modeling the detector's electrical behavior, and indirectly estimating total resistance under testing conditions. We ran the Blanche cryostat under various thresholds and gain configurations to evaluate their potential impact to low-energy event reconstruction and advancing R&D efforts for dopant integration in neutrino detectors

Van Loenen, Drew [Franciscan U. Steubenville]↗

DOE OSTI2025

ACHILLES-GENIE Interface for Neutrino Simulations, ADRIANO2 Tile Prototype for High-Granularity Dual-Readout Calorimetry

ICARUS (Imaging Cosmic And Rare Underground Signals) is a liquid argon time projection chamber (LArTPC) detector that pursues the sterile neutrino, which relies on accurate simulations of neutrino-argon interactions. REDTOP (Rare Eta Decays To Observe new Physics) is a proposed low-energy, high-intensity meson factory designed to explore rare $\eta$/$\eta'$ meson decays and probe physics beyond the Standard Model. As a next-generation experiment, this requires both accurate simulations and innovative detector technologies. This project contributes to both ICARUS, from a simulation perspective, and REDTOP, from both a simulation and detection perspective, through the event generation of lepton-nucleon interactions and the physical enhancement of the calorimeter technology within the REDTOP detector. We developed an interface between ACHILLES (A CHIcago Land Lepton Event Simulator), a theory-driven lepton-level event generator, and GENIE, a robust event generator framework used for neutrino physics. By incorporating the precise theoretical cross-section calculations of ACHILLES into the experimental realism of GENIE, the interface allows for improved accuracy of neutrino-nucleon simulations, which can be adapted for the proton beam specifications of the REDTOP meson factory as well as for the ICARUS experiment. In parallel, we developed an improved prototype for the ADRIANO2 (A Dual Readout Integrally Active Non-segmented Option) dual-readout calorimeter tiles for the REDTOP detector. To improve the efficiency of the lead-glass tiles trapping Cherenkov light for energy reconstruction and particle identification, we optimized the application of a highly reflective coating. Through viscosity and thickness control, masking, and a custom spray technique, we refined the coating process to reduce surface defects and improve light yield. Together, these efforts strengthen the ICARUS neutrino program and REDTOP's capability of detecting rare decay events.

Visser, Erin [Michigan State U.]↗

DOE OSTI2025

NUMI Flux Systematic Uncertainties

The Imaging Cosmic And Rare Underground Signals (ICARUS) detector is a 476 t active liquid argon time projection chamber neutrino detector at Fermilab. ICARUS lies 795 m downstream and 5.75◦ off-axis from the Neutrinos at the Main Injector (NuMI) beam. To create a neutrino beam NuMI directs pulsed beam of 120 GeV protons onto a graphite target to create hadrons, which are then focused by magnetic horns and allowed to decay into neutrinos. At the ICARUS off-axis angle the neutrino flux originates from the decays of unfocused/antifocused pions decays and from high-transverse momentum kaon decays. These contributions allow ICARUS to observe a significant flux of (anti-)electron and (anti-)muon neutrinos in a kinematic region relevant to the upcoming DUNE experiment. These factors also introduce various model uncertainties that have not been studied in detail by existing on-axis experiments. This poster will explore the systematic uncertainties in the NuMI flux at ICARUS that arise from uncertainties on hadron interaction cross sections and beamline operation conditions.

Alrahman, Fatima Abd [Houston U.]↗

DOE OSTI2025

Searching for Sterile Neutrinos Using an Exclusive 1$\mu$;1$\rho$ Selection: The Short Baseline Near Detector (SBND)

Over the last two decades, we have seen several of short-baseline neutrino oscillation experiments report results which challenged mainstream theories of neutrino oscillations. On the forefront of exploring these anomalies further is Fermilab's Short-Baseline Neutrino (SBN) program, which consists of two large liquid argon time projection chambers (LArTPCs), SBND and ICARUS, placed in alignment with the Booster Neutrino Beam (BNB). I'll be showing the strength that a 1mu1p selection at the SBN program can have for delivering world-leading sensitivity to distortions in the muon neutrino spectrum due to sterile neutrino oscillations.

Rowe, Nathaniel [Chicago U.]↗

DOE OSTI2025

Comparing CRT and Pandora Tagged Tracks in ICARUS

The ICARUS Liquid Argon Time Projection Chamber (LArTPC) is used to investigate short-baseline neutrino oscillations and the possible existence of sterile neutrinos. To aid in identifying and rejecting cosmic ray backgrounds, the system is outfitted with external Cosmic Ray Taggers (CRTs). The CRT is able to measure more tracks and at a wider range of angles, useful in further detailing future calibrations. This project compared the most probable values (MPVs) of charge deposition between CRT tagged and TPC tagged tracks. The Y-Z maps of charge scale for both datasets show a strong correlation, not just in their overall structure, but also in how they reflect known detector effects. Both reconstruction paths showed similar structures in their charge distribution, such as less effective wire section or mechanical support, confirming that CRT-tagged tracks, despite being external, respond to the same calibration landscape as Pandora tracks, validating previous Pandora reconstructions and values. Overall, the analysis supports the idea that the CRT tags are a useful addition to ICARUS calibration efforts. Their broad angular range and independence from Pandora reconstruction make them a helpful secondary tool and a potential asset in extending calibration across the detector volume.

Thayer, Abigail [Colorado State U.] (ORCID:0009000↗

DOE OSTI2024

New MeV-Scale Capabilities in Large Neutrino LArTPCs Using Ambient Radiogenic and Cosmogenic Activity in MicroBooNE

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions present in their data. We use data from MicroBooNE, an 85 tonnes LArTPC exposed to Fermilab neutrino beams from 2015 until 2021, to demonstrate new calorimetric and particle discrimination capabilities for isolated $\sim \mathrm{O}(1 \mathrm{MeV})$ energy depositions referred to as blips. We observe a concentration of low energy ( $<3$ MeV ) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV Tl-208 decay gamma rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of Tl-208 in the fiberglass composing these struts. Cosmogenicallyproduced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions.

Andrade Aldana, Diego Armando↗

DOE OSTI2026

Status of the Short-Baseline Near Detector at Fermilab

The Short-Baseline Near Detector (SBND) is one of the Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, and is the near detector in the Short-Baseline Neutrino (SBN) Program. The detector has completed Run 1, successfully recording approximately 3 million neutrino interactions, and started Run 2 in the autumn of 2025. SBND is characterized by superb imaging capabilities and will record around 3 million neutrino interactions per year. Thanks to its unique combination of measurement resolution and statistics, SBND will soon carry out a rich program of neutrino interaction measurements and novel searches for physics beyond the Standard Model (BSM). As the near detector, it will enable the full potential of the SBN sterile neutrino program by performing a precise characterization of the unoscillated event rate and constraining the BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the physics reach, current status, and future prospects of SBND are discussed.

Del Tutto, Marco [Fermilab]↗

DOE OSTI2026

Status of the Short-Baseline Near Detector at Fermilab

Del Tutto, Marco [Fermilab]↗

DOE OSTI2026

Advancing Artificial Intelligence with Liquid Argon Neutrino Experiments (Technical Report)

The grant allowed two main contributions: 1) The development of a first successful demonstration of the employment of Optimal Transport in liquid argon time projection chamber neutrino detectors. Optimal Transport, used in other contexts and specifically with LHC calorimetric data, was adapted to address a key particle identification challenge in LArTPCs: the separation of pi0 backgrounds from single-electrons produced in charged-current electron neutrino interactions. The work, leveraging ML methods such as k-nearest-neighbor (kNN) and support-vector-machine (SVM), showed an increase in background rejection of a factor of two or more. Work is now ongoing to incorporate this development in physics analyses for LArTPC experiments and more broadly expand the use of OT in LArTPC detectors including DUNE. This work was done in collaboration with the phenomenology group led by Nathaniel Craig at UCSB. 2) The deployment of NuGraph2, a graph neural network developed for LArTPC reconstruction, in the MicroBooNE experiment. NuGraph2 uses novel graph-neural-network methods on the rather simple LArTPC inputs of reconstructed hits, greatly simplifying the workflow compared to the use of waveform or signal-deconvolved wire ROIs. The network performed particle classification and was shown to address many challenging problems in LArTPC imaging including track-shower separation and the identification of protons and charged pions from primary muons. Our group collaborated with Giuseppe Cerati (FNAL scientist) who is one of the core developers of NuGraph2 to integrate this tool in MicroBooNE’s analysis framework. This consisted in tow key contributions: a) Studying performance on real data, which came with several months of iterations because the MC-trained version of the network was found to show significant bias that our group investigated and addressed. b) Integrating the output hit labeling of NuGraph2 into the existing particle tracking and shower reconstruction code. As a result of this work led by our team NuGraph2 is now enabling a suite of new analyses which benefit from enhanced capabilities and thus broader physics reach. The grant supported primarily the salary of UCSB graduate student Chuyue “Michaelia” Fang as well as partial summer salary support for PI Caratelli. Some funds were used for travel by Michaelia to ML related schools and conferences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Measurements of the 239 Pu(n,f)/ 235 U(n,f) and 238 U(n,f)/ 235 U(n,f) Cross-Section Ratios Using Quasi-Monoenergetic Neutron Beams

Neutron-induced fission cross-section ratio measurements were carried out at Triangle Universities Nuclear Laboratory (TUNL) over multiple experiment campaigns from 2021-2023. The total beam time for these measurements across all the experimental campaigns was approximately three weeks. This work was intended to serve as an independent validation of the fissionTPC cross-section ratio measurements. In contrast to the white spectrum neutron source and time-projection chamber utilized in the fissionTPC, these measurements utilized pulsed, quasi-monoenergetic neutron beams and fission ionization chambers. Therefore, this work has different sources of systematic error and can be used as a complementary measurement. In this report we describe our fission cross-section ratio measurements, analysis, results and provide a detailed uncertainty budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Signal Processing in SBND with Calibrated and Validated Electronics and Field Responses

SBND is a liquid argon time projection chamber in Fermilab’s Short-Baseline Neutrino Program, located 110 m from the neutrino source and operating in a high-rate environment with unprecedented statistics. Charged particles from neutrino interactions ionize the argon, and the resulting electrons drift to the anode wires, inducing current signals recorded as raw waveforms. These waveforms are a convolution of deposited charge with the electronics and TPC field responses, making accurate signal processing essential for recovering the true charge distribution. Signal processing forms the starting point for SBND reconstruction, directly impacting hit finding, charge calibration, clustering, and the reconstruction of tracks and showers, and therefore playing a key role in energy reconstruction and particle identification. In this poster, we present an overview of the SBND signal processing chain, including noise removal, channel-by-channel electronics correction, signal identification, and deconvolution using measured electronics and TPC field responses. We demonstrate that the two kernel functions—electronics and field responses—achieve high precision when compared to data, ensuring that the SBND signal processing chain provides a robust and accurate foundation for event reconstruction and precision physics measurements.

Singh, Prabhjot [Louisiana State U.] (ORCID:000000↗

DOE OSTI2026

Prong Segmentation using Point Set Transformers in Multiple View Neutrino Detectors

NOvA is a long-baseline neutrino experiment studying neutrino oscillations by detecting neutrinos from the NuMI beam at Fermilab. Its physics analysis relies on accurate prong segmentation, which involves matching each hit to its source particle and identifying the particle type. This task has commonly been addressed using a combination of traditional clustering algorithms and convolutional neural networks (CNNs). However, NOvA’s detector design presents data as two sparse and decoupled 2D images (XZ and YZ views) rather than a native 3D representation, posing a significant challenge for traditional CNN-based models. In this talk, we propose a novel neural network based on the Point Set Transformer. By treating detector hits as sparse point clouds and implementing a cross-view attention mechanism, our model enables efficient information mixing between both views. Evaluated on NOvA simulated data, our model achieves superior accuracy while requiring significantly fewer computational resources compared to other models. Furthermore, the model demonstrates great performance when applied to Liquid Argon Time Projection Chamber (LArTPC) data, which shows its potential as a universal prong segmentation algorithm for multiple view neutrino detectors.

Liu, Jiaxi [UC, Irvine]↗

DOE OSTI2026

Inclusive Search for Anomalous Single-Photon Production in MicroBooNE

The MicroBooNE experiment is an 85-ton active volume liquid argon time projection chamber (LArTPC) neutrino detector situated in the Fermilab Booster Neutrino Beam. One of the main goals for MicroBooNE is to investigate the “low energy excess” (LEE) of electromagnetic events observed by the MiniBooNE experiment by leveraging the unique capabilities of the LArTPC technology to distinguish photons from electron electromagnetic showers. In this poster, we present an inclusive search for anomalous production of single-photon events from neutrino interactions in the MicroBooNE experiment, motivated by the MiniBooNE LEE. The analysis uses the Wire-Cell reconstruction framework to select a sample of inclusive single-photon final-state interactions and leverages simultaneous measurements of sidebands to constrain signal and background predictions and reduce uncertainties. We perform a blind analysis using a dataset collected from February 2016 to July 2018 from the Booster Neutrino Beam (BNB) at Fermilab. In the full signal region, we observe agreement between the data and the prediction, with a goodness-of-fit p-value of 0.11. We then isolate a sub-sample of these events containing no visible protons, and observe 93 $/pm$ 22(stat.) $\pm$ 35(syst.) data events above prediction, corresponding to just above 2$\sigma$ local significance, concentrated at shower energies below 600 MeV.

Yandel, Erin [Los Alamos] (ORCID:0000000277123709)↗