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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Production, quality assurance and quality control of the SiPM Tiles for the DarkSide-20k Time Projection Chamber

The DarkSide-20k dark matter direct detection experiment will employ a 21 m 2 silicon photomultiplier (SiPM) array, instrumenting a dual-phase 50 tonnes liquid argon Time Projection Chamber (TPC). SiPMs are arranged into modular photosensors called Tiles, each integrating 24 SiPMs onto a printed circuit board (PCB) that provides signal amplification, power distribution, and a single-ended output for simplified readout. Tiles are further grouped into Photo-Detector Units (PDUs). This paper details the production of the Tiles and the Quality Assurance and Quality Control (QA-QC) protocol established to ensure their performance and uniformity. The production and QA-QC of the Tiles are carried out at Nuova Officina Assergi (NOA), an ISO-6 clean room facility at LNGS. This process includes wafer-level cryogenic characterisation, precision die attaching, wire bonding, and extensive electrical and optical validation of each Tile. The overall production yield exceeds 83.5%, matching the requirements of the DarkSide-20k production plan. These results validate the robustness of the Tile design and its suitability for operation in a cryogenic environment.

Acerbi, F. [Fondazione Bruno Kessler]↗
DOE OSTI2023

Development of Nanocomposite Coatings for Future Large-Scale Time Projection Chambers

In the context of this award we tested the performance of thin high-resistivity coatings for their potential usage as field shaping systems in future large scale xenon Time Projection Chambers (TPC). A successful implementation of such thin coatings would likely simplify the design of potential future detectors, allowing to overcome some of the challenges observed with traditional systems constituted by massive discrete electrodes. We studied a wide range of materials and characterized their optical and electrical performances as functions of temperature and wavelength. The measurement campaign indicated that uniform coatings covering the full PTFE substrate (usually used as reflector in LXe TPCs) impact too severely on the light collection performance of such detectors when used with deep UV light. Despite tuning the composition and thicknesses of nanocomposite coatings, we were not able to identify a single coating, properly working at LXe temperature, that would simultaneously fulfill the resistance and optical requirements. Following the risk mitigation strategy identified in the proposal we moved the focus of the R&D to identify proper materials that, when coated with grid-like patterns on PTFE, would not alter meaningfully its optical properties (with respect to bare PTFE panels) but would still serve as effective field shaping systems, properly containing the drift field in TPC detectors. Among the various materials we identified germanium as the most promising one, providing a good adhesion to PTFE and the proper range of sheet resistivity. The Ge-patterned coating tested within a small scale LXe TPC showed good performance as a field shape system and, as desired, did not reduce the detector light yield. These results are encouraging and such technology should further be investigated as a potential alternative to more traditional field shaping electrodes. Incidentally, in the context of this R&D, we stumbled upon an unexpected behavior suggesting that some of the treatments performed on the PTFE panels, in preparation of the coatings, meaningfully boosted the PTFE reflectivity. The most probable candidate is the O2 plasma cleaning procedure. This hypothesis will be tested in the near future by operating the small scale TPC at UChicago first with regular PTFE panels and then with panels bombarded with O2 plasma (but no coatings). This finding, if confirmed, might open up the possibility of further boosting UV light collection in future large detectors by performing such a treatment on the PTFE surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reconstructing 3D Charge Depositions in the MicroBooNE Liquid Argon Time Projection Chamber using Convolutional Neural Networks

We have developed a convolutional neural network (CNN) that reconstructs the three dimensional location of ionization produced by charge particles traversing a wire-readout liquid argon time projection chamber (LArTPC) at MicroBooNE. This method is the first CNN application to reconstruct 3D space points directly from two dimensional images of the different wire plane views. I.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. Furthermore, this event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

NEXT-CRAB-0: a high pressure gaseous xenon time projection chamber with a direct VUV camera based readout

The search for neutrinoless double beta decay(0νββ) remains one of the most compelling experimentalavenues for the discovery in the neutrino sector.Electroluminescent gas-phase time projection chambers are wellsuited to 0νββ searches due to their intrinsicallyprecise energy resolution and topological event identificationcapabilities. Scalability to ton- and multi-ton masses requiresreadout of large-area electroluminescent regions with fine spatialresolution, low radiogenic backgrounds, and a scalable dataacquisition system. This paper presents a detector prototype thatrecords event topology in an electroluminescent xenon gas TPC viaVUV image-intensified cameras. This enables an extendable readoutof large tracking planes with commercial devices that reside almostentirely outside of the active medium. Following furtherdevelopment in intermediate scale demonstrators, this technique mayrepresent a novel and enlargeable method for topological eventimaging in 0νββ.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Neutrino beam bunch structure reconstruction with precision timing in the ICARUS liquid argon time projection chamber

The ICARUS detector has been operating smoothly since 2021 as the far detector in the Short Baseline Neutrino (SBN) program at Fermilab, collecting neutrino interactions from both the Booster Neutrino Beam (BNB) and off-axis from the Neutrinos at the Main Injector (NuMI) beam. Analysis of neutrino interactions in ICARUS requires mitigation of substantial cosmogenic backgrounds. This is achieved by using an external Cosmic Ray Tagger (CRT) and a Photomultiplier Tube (PMT) system embedded in the liquid argon. The intrinsic neutrino beam bunch structure, inherited time structure from the Radio Frequency (RF) system used to accelerate the protons, can be resolved at the ICARUS detector using precise timing information. Located at shallow depth, ICARUS is exposed to a high flux of cosmic rays that can be mistaken for neutrino interactions. To mitigate this background, the CRT and a 3-meter-thick concrete overburden were installed. To better model backgrounds, ICARUS makes use of an overlay technique where simulated neutrino events are superimposed on detector beam-off data. PMTs installed within a Time Projection Chamber detect argon scintillation light emitted by high energy charged particles passing through the chamber and provide the event timing of neutrino interactions. The nanosecond-level beam bunch structure is reconstructed with the PMT system and can be used to further understand backgrounds and enhance neutrino physics capabilities. In this thesis, I will discuss background mitigation techniques using precision timing and present a novel technique to select neutrino events from our unbiased data stream using the beam bunch structure.

Heggestuen, Anna [Colorado State U.] (ORCID:000000↗
DOE OSTI2022

Neutrino interaction measurements with the MicroBooNE and ArgoNeuT liquid argon time projection chambers

Abstract Precise modeling of neutrino interactions on argon is crucial for the success of future experiments such as the Deep Underground Neutrino Experiment (DUNE) and the Short-Baseline Neutrino (SBN) program, which will use liquid argon time projection chamber (LArTPC) technology. Argon is a large nucleus, and nuclear effects—both on the initial and final-state particles in the interaction—are expected to be large in neutrino–argon interactions. Therefore, measurements of neutrino scattering cross sections on argon will be of particular importance to future DUNE and SBN oscillation measurements. This article presents a review of neutrino–argon interaction measurements from the MicroBooNE and ArgoNeuT collaborations, using two LArTPC detectors that have collected data in the NuMI and Booster Neutrino Beams at Fermilab. Measurements are presented of charged-current muon neutrino scattering in the inclusive channel, the ‘0 $$\pi $$ π ’ channel (in which no pions but some number of protons may be produced), and single pion production (including production of both charged and neutral pions). Measurements of electron neutrino scattering are presented in the form of $$\nu _e+\bar{\nu }_e$$ ν e + ν ¯ e inclusive scattering cross sections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Unpaired image translation to mitigate domain shift in liquid argon time projection chamber detector responses

Deep learning algorithms often are developed and trained on a training dataset and deployed on test datasets. Any systematic difference between the training and a test dataset may severely degrade the final algorithm performance on the test dataset—what is known as the domain shift problem . This issue is prevalent in many scientific domains where algorithms are trained on simulated data but applied to real-world datasets. Typically, the domain shift problem is solved through various domain adaptation (DA) methods. However, these methods are often tailored for a specific downstream task, such as classification or semantic segmentation, and may not easily generalize to different tasks. This work explores the feasibility of using an alternative way to solve the domain shift problem that is not specific to any downstream algorithm. The proposed approach relies on modern Unpaired Image-to-Image (UI2I) translation techniques, designed to find translations between different image domains in a fully unsupervised fashion. In this study, the approach is applied to a domain shift problem commonly encountered in Liquid Argon Time Projection Chamber (LArTPC) detector research when seeking a way to translate samples between two differently distributed LArTPC detector datasets deterministically. This translation allows for mapping real-world data into the simulated data domain where the downstream algorithms can be run with much less domain-shift-related performance degradation. Conversely, using the translation from the simulated data to a real-world domain can increase the realism of the simulated dataset and reduce the magnitude of any systematic uncertainties. To evaluate the quality of the translations, we use both pixel-wise metrics and a downstream task to measure the effectiveness of UI2I methods for mitigating the domain shift problem. We adapted several popular UI2I translation algorithms to work on scientific data and demonstrated the viability of these techniques for solving the domain shift problem with LArTPC detector data. To facilitate further development of DA techniques for scientific datasets, the ‘Simple Liquid-Argon Track Samples’ dataset used in this study is also published.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Benefits of MeV-scale reconstruction capabilities in large liquid argon time projection chambers

Using truth-level Monte Carlo simulations of particle interactions in a large volume of liquid argon, we demonstrate physics capabilities enabled by reconstruction of topologically compact and isolated low-energy features, or “blips,” in large liquid argon time projection chamber (LArTPC) events. These features are mostly produced by electron products of photon interactions depositing ionization energy. The blip identification capability of the LArTPC is enabled by its unique combination of size, position resolution precision, and low energy thresholds. Here, we show that consideration of reconstructed blips in LArTPC physics analyses can result in substantial improvements in calorimetry for neutrino and new physics interactions and for final-state particles ranging in energy from the MeV to the GeV scale. Blip activity analysis is also shown to enable discrimination between interaction channels and final-state particle types. In addition to demonstrating these gains in calorimetry and discrimination, some limitations of blip reconstruction capabilities and physics outcomes are also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

TITUS: Visualization of Neutrino Events in Liquid Argon Time Projection Chambers

The amount and complexity of data recorded by high energy physics experiments are rapidly growing, and with these grow the difficulties in visualizing such data. To study the physics of neutrinos, a type of elementary particle, scientists use liquid argon time projection chamber (LArTPC) detectors, among other technologies. LArTPCs have a very high spatial resolution and resolve many of the elementary particles that come out of a neutrino interacting within the argon in the detector. Visualizing these neutrino interactions is of fundamental importance to understanding the properties of neutrinos, but also monitoring and checking on the detector conditions and operations. From these ideas, we have developed TITUS, an event display that shows images recorded by these neutrino detectors. TITUS is a piece of software that reads data coming from LArTPC detectors (as well as the corresponding simulation) and allows users to explore such data in multiple ways. TITUS is flexible to enable fast prototyping and customization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Gamma Ray Detection In Liquid Argon Time Projection Chambers

Gamma rays are photons in excess of 100 keV of energy and can be produced by a variety of mechanisms like radioactive decay and inelastic neutrino-argon interactions. A reconstruc- tion of Compton scattering gamma rays was developed for use in liquid argon time projection chambers. This reconstruction was tested with detectors developed to demonstrate the ca- pabilities of Deep Underground Neutrino Experiment (DUNE) Near Detector Liquid Argon target (ND LAr). In October 2024, a radioactive fluorine-18 source was placed next to the Full Scale Demonstrator. The data obtained was used to test this reconstruction algorithm. It was able to determine the direction of the photons with an error of less than 10 percent. In addition to this work, there has been significant work on designing a liquid argon based Positron Emission Tomography (PET) scanner. PET scanners detect gamma rays emitted by a tracer chemical to help screen for diseases like cancer. In addition to the applications to medical imaging, this thesis briefly explores the applications of this reconstruction to de-excitation photons produced in interactions between neutrinos and argon nuclei. These applications could improve studies focusing on neutrinos originating from accelerators and supernovae.

Murphy, Thomas [Syracuse U.]↗
DOE OSTI2020

Detection prospects for the second-order weak decays of 124 Xe in multi-tonne xenon time projection chambers

We investigate the detection prospects for two-neutrino and neutrinoless second-order weak decays of 124 Xe – double-electron capture (0/2νECEC), electron capture with positron emission (0/2νECβ + ) and double-positron emission (0/2νβ + β + ) – in multi-tonne xenon time projection chambers. We simulate the decays in a liquid xenon medium and develop a reconstruction algorithm which uses the multi-particle coincidence in these decays to separate signal from background. This is used to compute the expected detection efficiencies as a function of position resolution and energy threshold for planned experiments. In addition, we consider an exhaustive list of possible background sources and find that they are either negligible in rate or can be greatly reduced using our topological reconstruction criteria. In particular, we draw two conclusions: First, with a theoretical half-life of $T^{2νECβ^+}_{1/2}$= (1.7 ± 0.6) ∙10 23 year, the 2νECβ + decay of 124 Xe will likely be detected in upcoming Dark Matter experiments (e.g. XENONnT or LZ), and their major background will be γ-rays from detector construction materials. Second, searches for the 0νECβ + decay mode will likely be background-free, and new parameter space may be within reach. To this end we investigate two different scenarios of existing experimental constraints on the effective neutrino mass. The necessary 500 kg-year exposure of 124 Xe could be achieved by the baseline design of the DARWIN observatory, or by extracting and using the 124 Xe from the tailings of the nEXO experiment. We demonstrate how a combination of 124 Xe results with those from 0νβ - β - searches in 136 Xe could help to identify the neutrinoless decay mechanism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC), a time projection chamber is used as the main tracking detector, which records particle trajectories in a volume of three-dimensional (3D) cylinder. The resulting data are usually very sparse with occupancy around 10.8%. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE), outperforms traditional methods both in compression rate and reconstruction accuracy. BCAE can also utilize the computation power of graphical processing units suitable for deployment in a modern heterogeneous highperformance computing environment. This work introduces two BCAE variants: BCAE++ and BCAE-2D. BCAE++ achieves a 15% better compression ratio and a 77% better reconstruction accuracy measured in mean absolute error compared with BCAE. BCAE-2D treats the radial direction as the channel dimension of an image, resulting in a 3× speedup in compression throughput. In addition, we demonstrate an unbalanced autoencoder with a larger decoder can improve reconstruction accuracy without significantly sacrificing throughput. Lastly, we observe both the BCAE++ and BCAE-2D can benefit more from using half-precision mode in throughput (76 - 79% increase) without loss in reconstruction accuracy. The source code and links to data and pretrained models can be found at https://github.com/BNL-DAQ-LDRD/NeuralCompression_v2

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Observables for recoil identification in high-definition Gas Time Projection Chambers

Directional detection of nuclear recoils is broadly desirable in nuclear and particle physics. At low recoil energies, this capability may be used to confirm the cosmological origin of a dark matter signal, to penetrate the so-called neutrino floor, or to distinguish between different neutrino sources. Gas Time Projection Chambers (TPCs) can enable directional recoil detection if the readout granularity is sufficiently high, as is the case when micro-pattern gaseous detectors (MPGDs) are utilized. A key challenge in such detectors is identifying and rejecting background electron recoil events caused by gamma rays from radioactive contaminants in the detector materials and the environment. We define new observables that can distinguish electron and nuclear recoils, even at keV-scale energies, based on the simulated ionization's topology. Here we perform a simulation study that shows these observables outperform the traditionally used discriminant, dE/dx, by up to three orders of magnitude. Furthermore, these new observables work well even at ionization energies well below 10keV and remain robust even in the regime where directionality fails.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

High Energy Experimental Research Effort: Intensity Frontier Physics with Liquid Argon Time Projection Chambers (Final Technical Report DE-SC0017925)

The proposal “University of Florida High Energy Physics Intensity Frontier Research: Liquid Argon Detectors” requested one year of funding support for the PI, one postdoc and one graduate student to start their involvement in ongoing and upcoming experiments that use Liquid Argon Time Projection Chambers (LAr TPCs) to reconstruct neutrino interactions. Specifically, it was proposed that the group join the Short Baseline Near Detector (SBND) at Fermilab and that the PI continue their involvement in the Deep Underground Neutrino Detector (DUNE).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First Demonstration of a Liquid Argon Time Projection Chamber Based Search for Intranuclear Neutron-Antineutron Transitions and Annihilation in $^{40}$Ar using the MicroBooNE Detector

We present a novel methodology to search for intranuclear neutron-antineutron transition ($n\rightarrow\bar{n}$) followed by $\bar{n}$-nucleon annihilation within an $^{40}$Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of $n\rightarrow\bar{n}$ transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select $n\rightarrow\bar{n}$ events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22$\pm$6.04)\% and (0.0020$\pm$0.0003)\%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of $3.32 \times10^{26}\,$neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the $n\rightarrow\bar{n}$ lifetime in $^{40}$Ar of $\tau_{\textrm{m}} \gtrsim 1.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Neutron Reconstruction via Blips in Liquid Argon Time Projection Chambers

Neutrons are important in the separation of neutrino and antineutrino in atmospheric neutrino oscillation and in reducing atmospheric-neutrino backgrounds in beyond-standard model searches, but they are not explicitly accounted for in most current LArTPC reconstruction. We present a phenomenological study of neutron activities in liquid argon time projection chamber using detector-response constraints from existing detectors. Leveraging energy deposits from neutron scattering, primarily low-energy localized ,blips, we demonstrate the capability to identify neutrons and to reconstruct neutron multiplicity in neutrino interactions. Including neutron information significantly improves neutrino-antineutrino separation and the identification of rare events against atmospheric-neutrino backgrounds, motivating neutron-aware reconstruction for future high-precision LArTPC analyses.

Hernandez Morquecho, Miguel Angel [Minnesota U.] (↗
DOE OSTI2023

Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers

The Exa.TrkX project presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the Large Hadron Collider (LHC). Graphs describing particle interactions are formed by treating each detector hit as a node, with edges describing the relationships between hits. We utilise a multi-head attention message passing network which performs graph convolutions in order to label each node with a particle type.We present an updated variant of our GNN architecture, with several improvements. After testing the model on more realistic simulation with regions of unresponsive wires, the target was modified from edge classification to node classification in order to increase robustness. Removing edges as a classification target opens up a broader possibility space for edge-forming techniques; we explore the model’s performance across a variety of approaches, such as Delaunay triangulation, kNN, and radius-based methods. We also extend this model to the 3D context, sharing information between detector views. By using reconstructed 3D spacepoints to map detector hits from each wire plane, the model naively constructs 2D representations that are independent yet fully consistent.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗