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DOE OSTI2023

Portable Programming Model Exploration for LArTPC Simulation in a Heterogeneous Computing Environment: OpenMP vs. SYCL

The evolution of the computing landscape has resulted in the proliferation of diverse hardware architectures, with different flavors of GPUs and other compute accelerators becoming more widely available. To facilitate the efficient use of these architectures in a heterogeneous computing environment, several programming models are available to enable portability and performance across different computing systems, such as Kokkos, SYCL, OpenMP and others. As part of the High Energy Physics Center for Computational Excellence (HEP-CCE) project, we investigate if and how these different programming models may be suitable for experimental HEP workflows through a few representative use cases. One of such use cases is the Liquid Argon Time Projection Chamber (LArTPC) simulation which is essential for LArTPC detector design, validation and data analysis. Following up on our previous investigations of using Kokkos to port LArTPC simulation in the Wire-Cell Toolkit (WCT) to GPUs, we have explored OpenMP and SYCL as potential portable programming models for WCT, with the goal to make diverse computing resources accessible to the LArTPC simulations. In this work, we describe how we utilize relevant features of OpenMP and SYCL for the LArTPC simulation module in WCT. We also show performance benchmark results on multi-core CPUs, NVIDIA and AMD GPUs for both the OpenMP and the SYCL implementations. Comparisons with different compilers will also be given where appropriate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Lepton-Nucleus Scattering Measurements for Neutrino Interactions and Oscillations

Currently running and forthcoming precision neutrino oscillation experiments aim to unambiguously determine the neutrino mass ordering, the charge-parity violating phase in the lepton sector and the possible existence of physics Beyond the Standard Model. To have an understanding of all the effects necessary for the success of these experiments, lepton-nucleus interactions must be modeled in unprecedented detail. With this thesis, expertise in both neutrino and electron cross-section modeling and analysis was leveraged in order to make fundamental and critical improvements to our understanding of these interactions. The outlined work takes a significant step towards this high-precision measurement era with three complementary approaches. Cross sections are reported using neutrino data sets from the MicroBooNE liquid argon time projection chamber detector at Fermi National Laboratory, as well as electron scattering data from the CLAS detector at Thomas Jefferson National Laboratory. Furthermore, the modeling development of the commonly used GENIE event generator is presented.

Papadopoulou, Afroditi↗

DOE OSTI2023

First Measurement of Inclusive Muon Neutrino Charged Current Triple Differential Cross Section on Argon

The field of accelerator neutrino experiments is entering an era of precision oscillation measurements where the remaining unknown neutrino measurements will be determined. The upcoming DUNE and Hyper-K experiments aim to determine the neutrino mass hierarchy and degree of Charge-Parity (CP) violation in the neutrino sector, providing potential insight on the matter-antimatter imbalance observed in the universe. However, these experiments require highly accurate measurements, and neutrino cross section modeling uncertainties may limit their capabilities. Cross section measurements at current- generation experiments can aid the development of neutrino interaction models to reduce these uncertainties. This is especially true for measurements of neutrino energy, as it drives neutrino oscillations and is of key importance to oscillation experiments. The MicroBooNE experiment uses a Liquid Argon Time Projection Chamber (LArTPC) to produce neutrino-argon cross sections as one of its physics goals. The MicroBooNE detector’s fully active volume, precision reconstruction, and calorimetry information are leveraged in the Wire-Cell analysis to produce a muon neutrino selection that is 92% pure while maintaining 68% efficiency. A reconstruction chain featuring a fully 3D charge reconstruction and a graph-based particle trajectory fit are used to produce accurate measurements of lepton kinematics as well as visible hadronic energy produced in a neutrino interaction. This thesis presents the first neutrino-argon triple-differential cross section measurement, targeting inclusive charged-current final states. Wiener SVD unfolding is used to produce a measurement over neutrino energy, muon momentum, and muon scattering angle. A series of constrained goodness of fit tests are used to demonstrate the validity of MicroBooNE’s model in describing the distribution of reconstructed kinematics seen in data to ensure the accuracy of unfolding. The validated unfolding to neutrino energy represents a step forward in the field of neutrino cross sections, and demonstrates the capabilities of the LArTPC detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Optimisation of the Search for CP-symmetry Violation at the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long baseline experiment, which will be situated in South Dakota. Its detectors will utilise liquid-argon time projection chamber technology, which is able to capture neutrino interactions with an incredible spatial and calorimetric resolution. With what will become the world’s most intense neutrino beam, a highly capable near detector, and four (10kt fducial mass) far detector modules, DUNE will be able to achieve an ambitious physics programme. Most notably, DUNE will determine whether charge-parity symmetry is broken in neutrino oscillations - a finding that would have significant implications for the understanding of the matter-antimatter asymmetry in our Universe.This thesis presents the optimisation of a CP-violation analysis at DUNE using thePandora pattern-recognition software. The analysis assumes a 3.5 year exposure (1.36 × 1023 protons on target) to a neutrino and an antineutrino beam (7 year total). Only the predicted data of the far detector modules is used; near detector samples are not included. The initial sensitivity to CP-violation is found to be 3.8σ+0.9σ−1.1σ in an estimate that includes oscillation parameter uncertainties, systematic uncertainties and statistical fluctuations, and assumes a normal-ordering of the neutrino mass hierarchy. The performance of the Pandora event reconstruction is linked to that of the analysis, which is found to be limited by the reconstruction of the initial track-like region of electrons and photons. The ShowerRefinement algorithm is developed in response to this and its implementation into the analysis workflow results in an improved sensitivity to CP-violation of 4.6σ+0.9σ−1.0σ. With a perfected neutrino interaction vertex placement, this is further increased to 5.1σ+1.0σ−1.1σ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

A Search for Heavy Neutral Leptons Decaying to Electron-Positron Pairs and Neutral Pions in the MicroBooNE Detector

This thesis presents a search for heavy neutral leptons (HNLs) decaying inside the MicroBooNE detector. The MicroBooNE detector is a liquid-argon time projection chamber located at Fermilab that receives flux from two neutrino beams; the booster neutrino beam (BNB) and the neutrinos at the main injector (NuMI) beam. The search uses data taken when the NuMI beam was on, with a total exposure of $7.01\times10^{20}$ protons on target. HNLs would be produced in kaon decays, and the source of HNLs targeted in this search is kaons decaying at rest in the NuMI hadron absorber. The kinematics of the HNLs produced in this way allow their decays to be distinguished from the majority of beam-neutrino interactions and cosmic-ray activity that constitute the background. Two HNL decay channels are studied, $\nu$\ee and \vpi. Boosted decision trees (BDTs) are trained to separate the simulated HNL decays from the expected background events. The BDT score distributions are used to calculate upper limits on the mixing angle \umusq in the mass range $10\le m_{\rm HNL}\le 245$~MeV. This is the first direct search for HNL decays to the \vpi channel, and the limits provide the most stringent constraints on \umusq in the mass range $35<\mhnl<175$~MeV.

43 PARTICLE ACCELERATORS↗

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 OSTI2023

Measurement of the pion charge exchange differential cross section on Argon with the ProtoDUNE-SP detector

The Deep Underground Neutrino Experiment (DUNE) utilizes Liquid Argon Time Projection Chamber (LArTPC) technology in its pursuit of uncovering the origins of matter. As a crucial prototype for the DUNE far detector (FD) module, ProtoDUNE-SP at CERN Neutrino Platform Facility employs a hadron test beam with a momentum range of 0.3 to 7 GeV/c to study the detector response to particles that could be produced in the neutrino interactions at the DUNE FD. Furthermore, ProtoDUNE-SP is dedicated to testing event reconstruction and performing detector calibration under controlled conditions. Neutral pion reconstruction performance is an important benchmark of the calorimetric and tracking capability of LArTPC, and understanding neutral pion in LArTPC is crucial to characterize backgrounds to oscillation measurements and rare searches. To improve neutral pion reconstruction in LArTPC, a kinematic fitting algorithm is developed, achieving a 12% resolution in neutral pion energy in ProtoDUNE-SP. This enhancement enables the first measurements of the pion-argon charge exchange differential cross-section. By comparing these results with the current model, valuable constraints can be made to improve generator simulations in the future DUNE experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

First Search for Dark-Trident Processes Using the MicroBooNE Detector

This thesis presents a first search for dark-trident scattering in a neutrino beam using a data set corresponding to $7.2 \times 10^{20}$ protons on target taken with the MicroBooNE detector at Fermilab. Proton interactions in the neutrino target at the Main Injector produce $\pi^0$ and $\eta$ mesons, which could decay into dark matter (DM) particles via a dark photon $A^{\prime}$. A convolutional neural network is trained to identify interactions of the DM particles in the liquid-argon time projection chamber (LArTPC) exploiting its image-like reconstruction capability. In the absence of a DM signal, limits at the $90\%$ confidence level on the squared kinematic mixing parameter $\varepsilon^2$ as a function of the dark-photon mass in the range $10\le M_{A^\prime}\le 400$~MeV are provided. The limits cover previously unconstrained parameter space for the production of fermion or scalar DM particles $\chi$ for two benchmark models with mass ratios $M_{\chi}/M_{A^\prime}=0.6$ and $2$ and for dark fine-structure constants $0.1\le\alpha_D\le 1$.Date of Award1 Aug 2024Original languageEnglishAwarding InstitutionThe University of ManchesterSupervisorStefan Soldner-Rembold (Supervisor) & Justin Evans (Supervisor)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

New Search for a Sterile Neutrino at MicroBooNE with BNB and NuMI Beams

The MicroBooNE experiment employs an 85-ton active volume liquid argon time projection chamber to detect neutrinos from both the on-axis Booster Neutrino Beam (BNB) and off-axis Neutrinos at the Main Injector (NuMI) beam. This poster describes short baseline neutrino oscillations in a 3+1 sterile neutrino model and presents the MicroBooNE results using only the BNB beam. Additionally, it states the impact of a degeneracy resulting from the cancellation of $\nu_e$ appearance and disappearance and demonstrates that combining data from the BNB and NuMI beams, which have substantially different $\nu_e/\nu_\mu$ ratios, can break this degeneracy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Demonstrating MeV-Scale Physics Capabilities of Large Neutrino LArTPCs with Ambient Blip Activity in MicroBooNE

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by incorporating isolated MeV-scale features present in their data. We use data from MicroBooNE, an 85 tonne LArTPC exposed to Fermilab neutrino beams from 2015 until 2021, to demonstrate new calorimetric and particle discrimination capabilities for isolated ~O(1 MeV) energy depositions referred to as "blips". We observe concentrations of blips near fiberglass support struts along the TPC edge, with an energy spectrum indicative of specific gamma-ray decays. These and other blip sources are being used to validate calibrations in MicroBooNE's data by leveraging spectral features. This work further reports on the progress towards distinguishing between low-energy protons and electrons in large LArTPCs using cosmogenic data. The composition of proton-like blips selected using this new technique is being studied to evaluate the accuracy of cosmic ray flux models used in LArTPCs

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Electromagnetic shower separation in LArTPCs: study of the calorimetric method at LArIAT

This thesis reports a study of the prospects of using calorimetry for separating photon- from electron-initiated electromagnetic (EM) showers in liquid argon time projection chambers (LArTPCs), a prevalent need for neutrino oscillation experiments based on the LArTPC technology as $\gamma$-initiated showers are a significant background to electron neutrino ($\nu_e$) events, whose signature is electron showers. From events simulated in the LArIAT (Liquid Argon In A Testbeam) experiment's detector, we quantitatively evaluated the dependence of the calorimetric separation on the initial momentum and position (along the beamline) of the primary particle. We could conclude that the separation is more efficient if the primary particle is created inside the chamber, whereas the impact of the momentum is not as significant. Furthermore, a first step was taken towards applying the calorimetric method to the showers measured in LArIAT. A convolutional neural network (CNN) trained on simulation was deployed to find EM showers among the events collected by the experiment. The charge deposition at the beginning of the showers found is centered at a plausible value, although the width of the distribution demands further inquiry.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Elimination LArTPC Simulation Uncertainty

Liquid Argon Time Projection Chambers (LArTPC) are crucial for measuring muons and neutrinos by capturing the paths of fast-moving particles through argon gas. However, these detectors face challenges such as electron-ion recombination, diffusion, and attenuation, which introduce uncertainties in simulation models. This study, conducted by Ka ren Mkrtchyan at FERMILAB, aims to reduce these uncertainties by adjusting the amplitude and width of signals detected by the TPC wires. Initial findings indicate that the current modification algorithm requires further refinement to better align simulations with observed data. Ongoing work focuses on correcting computational bugs and enhancing the simulation model for improved accuracy and statistical confidence.

Mkrtchyan, Ka'ren↗

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 OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments [https://arxiv.org/abs/2403.11872]. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

TinyTPC: A TEST STAND FOR LAr DOPING

TinyTPC is a small scale liquid-argon time projection chamber (LArTPC) that studies how photosensitive dopants can improve the energy resolution of low energy events in LArTPCs. Bench tests to resolve high voltage breakdown issues and to improve the low voltage system readout are described. Experimental data with a radioactive source of Th-228 for the calibration of the pixelated readout and the characterization of TinyTPC's energy resolution is explained. Provisional results from the addition of isobutylene (photosensitive dopant) and xenon (wavelength shifter) to liquid-argon (LAr) are also presented. Further steps to improve voltage system and enhance the data collection are discussed.

Rodriguez Thorne, Paloma↗

DOE OSTI2024

ICARUS cosmic ray tagger efficiency

The ICARUS Cosmic Ray Tagger (CRT) was constructed with the goal to tag cosmogenic muons passing through the ICARUS Time Projection Chamber (TPC). Construction and commissioning of the detector began in Fall 2019 with the Side CRT North wall and continued for several years through the installation of the Top CRT. In this thesis I will summarize my contributions to the CRT system and describe a measurement of the installed CRT detection efficiency using the TPC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗