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DOE OSTI2022

A study of events with photoelectric emission in the DarkSide-50 liquid argon Time Projection Chamber

Finding unequivocal evidence of dark matter interactions in a particle detector is a major goal of research in physics. Liquid argon time projection chambers offer a path to probe Weakly Interacting Massive Particles scattering cross sections on nuclei down to the so-called neutrino floor, in a mass range from a few GeV to hundreds of TeV. Based on the successful operation of the DarkSide-50 detector at LNGS, a new and more sensitive experiment, DarkSide-20k, has been designed and is now under construction. A thorough understanding of the DarkSide-50 detector response and, therefore, of all types of events observed in the detector, is essential for the optimal design of the new experiment. In this article, we report on a specific set of events, namely, standard two-pulse scintillation–ionization signals with a third small amplitude pulse, occurring within the 440 μ s data acquisition window of standard events. Some of these events are due to the photoionization of the TPC cathode. We compare our results with those published by collaborations using liquid xenon time projection chambers, which observed a similar phenomenon, and, in particular, with a recent paper by the LUX Collaboration (D.S. Akerib et al. Phys.Rev.D 102, 092004 (2020)) From the measured rate of these events, we estimate for the first time the quantum efficiency of the tetraphenyl butadiene deposited on the DarkSide-50 cathode at wavelengths of around 128 nm, in liquid argon. Also, both experiments observe events likely related to the photoionization of impurities in the liquid. The probability of photoelectron emission per unit length turns out to be an order of magnitude lower in DarkSide-50 than in LUX.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Investigations on a fuzzy process: effect of diffusion on calibration and particle identification in Liquid Argon Time Projection Chambers

Ionization electron diffusion in Liquid Argon Time Projection Chambers (LArTPCs) has typically been considered at the detector design stage, but little attention has been given to its effects on calibration and particle identification. We use a GEANT4-based simulation to study how diffusion impacts these techniques, and give consideration to how this effect is simulated. We find that diffusion can cause a drift-dependent bias to both the median and Most Probable Value (MPV) of dQ/dx distributions. The bias is estimated to be ~2.5% (median) and ~5.0% (MPV) for typical maximum drift times in currently running LArTPCs before adding detector specific considerations such as electric field non-uniformities. This information indicates that these metrics should not be used for calibration without care, contrary to the conventional wisdom. The impact of diffusion on the ability of LArTPCs to separate muons and protons is small, and not expected to pose any problems in future detectors. Diffusion may however be a significant source of systematic uncertainty when separating particles of more similar masses (muons and pions, kaons and protons). Separation of such populations may be improved by implementation of a drift-time dependent particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Measurement of the atmospheric muon rate with the MicroBooNE Liquid Argon TPC

MicroBooNE is a near-surface liquid argon (LAr) time projection chamber (TPC) located at Fermilab. We measure muons originating from cosmic interactions in the atmosphere using both the charge collection and light readout detectors. The data is compared with the cosmic-ray simulation. Agreement is found between the observation, simulation and previous results. Furthermore, the angular resolution of the reconstructed muons inside the TPC is studied in simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

First Event-by-Event Identification of Cherenkov Radiation from Sub-Mev Particles in Liquid Argon

This Letter reports the event-by-event observation of Cherenkov light from sub-MeV electrons in a high scintillation light-yield liquid argon detector by the coherent CAPTAIN-Mills (CCM) experiment. The CCM200 detector, located at Los Alamos National Laboratory, instruments seven tons (fiducial volume) of liquid argon with 200 eight-inch photomultiplier tubes, 80% of which are coated in a wavelength-shifting material and the remaining 20% are uncoated. In the prompt time region of an event, defined as - 6 ≤ t < 0 ns relative to the event start time t = 0 , the uncoated photomultiplier tubes are primarily sensitive to visible Cherenkov photons. Using gamma rays from a Na 22 source for production of sub-MeV electrons, we isolated prompt Cherenkov light with > 5 σ confidence and developed a selection to obtain a low-background electromagnetic sample. This is the first event-by-event observation of Cherenkov photons from sub-MeV electrons in a high-yield scintillator detector and represents a milestone in low-energy particle detector development.

Aguilar-Arevalo, A. A. [UNAM, Mexico]↗
DOE OSTI2024

Demonstration of neutron identification in neutrino interactions in the MicroBooNE liquid argon time projection chamber

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all final state particles above some detection threshold, undetected neutrons remain a considerable source of missing energy with little to no data constraining their production rates and kinematics. We present the first demonstration of tagging neutrino-induced neutrons in liquid argon time projection chambers using secondary protons emitted from neutron-argon interactions in the MicroBooNE detector. We describe the method developed to identify neutrino-induced neutrons and demonstrate its performance using neutrons produced in muon-neutrino charged current interactions. The method is validated using a small subset of MicroBooNE’s total dataset. The selection yields a sample with 60% of selected tracks corresponding to neutron-induced secondary protons. At this purity, the integrated efficiency is 8.4% for neutrons that produce a detectable proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Characterization and QC practice of 16-channel ADC ASIC at cryogenic temperature for Liquid Argon TPC front-end readout electronics system in DUNE experiment

ColdADC is a low-noise 16-channel analog-to-digital converter ASIC designed for cold readout electronics of Liquid Argon Time Projection Chambers (LArTPCs) in the Deep Underground Neutrino Experiment (DUNE). ColdADC was specifically designed for operation at cryogenic temperatures (77 K–89 K). Cold electronics is considered to be an enabling technology for liquid argon detectors in neutrino experiments. The main function of the chip is to digitize signals from the 16-channel charge-sensitive amplifier designed at BNL (LArASIC) and send digitized signals to the data aggregator and serializer chip (COLDATA). ColdADC operates with a resolution of 12 bits and a sampling rate of 2 MS/s per channel. A complete characterization of prototype chips was conducted at cryogenic temperature, involving power consumption, noise and linearity performance. In the first DUNE Far-Detector module, 384000 data channels will be read out, corresponding to 24000 ColdADC chips. Therefore, systematic testing of ColdADC chips at cryogenic temperature is vital for the quality and reliability of DUNE Single-Phase modules. We have developed a Quality Control (QC) test stand that includes ColdADC evaluation and characterization at cryogenic temperature. The QC procedure was applied to a first batch of 33 chips, corresponding to 528 data channels. The obtained results meet all the required DUNE specifications for ColdADC. Moreover, the testing outcome allowed us to identify possibilities of performance optimization that are currently being addressed in the design of the next version of the chip. The Quality Control procedure is proved to be successful and will be a reference design for future large-batch production testing of final ColdADC ASICs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Self-compensating light calorimetry with liquid argon time projection chamber for GeV neutrino physics

The Liquid Argon Time Projection Chamber (LArTPC) is a powerful dual calorimeter capable of estimating particle energy from both ionization charge and scintillation light. Here, our study shows that, due to the recombination luminescence, the LArTPC functions as a self-compensating light calorimeter: the missing energy in the hadronic component is compensated for by the increased luminescence relative to the electromagnetic component. Using 0.5-5 GeV electron neutrino charged current interactions as a case study, we show that good compensation of the electron-to-hadron response ratio (e/h) from 1-1.05 can be achieved across a broad range of drift electric fields (0.2-1.8 kV / cm), with better performance for neutrino energies above 2 GeV. This study highlights the potential of light calorimetry in LArTPCs for GeV neutrino energy reconstruction, complementing traditional charge calorimetry. Under ideal conditions of uniform light collection, we show that LArTPC light calorimetry can achieve an energy resolution comparable to the charge imaging calorimetry. Challenges arising from nonuniform light collection in large LArTPCs can be mitigated with a position-dependent light yield correction derived from 3D charge signal imaging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Electromagnetic shower reconstruction in the ICARUS liquid argon time projection chamber detector

The ICARUS-T600 liquid argon time projection chamber (LArTPC) detector is taking data at shallow depth as the far detector of the Short Baseline Neutrino (SBN) program at Fermilab, to search for a possible sterile neutrino signal at $\Delta m^{2} \approx 1~\text{eV}^{2}$ with the Booster (BNB) and Main Injector (NuMI) neutrino beams at $\GeV{\sim 0.8}$ and $\GeV{\sim 2}$ average energies respectively. The LArTPC technology, developed by the ICARUS collaboration and now a standard in neutrino physics, offers impressive charged-particle imaging capabilities with $\sim1 \ \text{mm}$ spatial resolution, enabling efficient discrimination between track-like signatures (e.g., from muons, pions, and protons) and electromagnetic showers (from electrons and photons). Moreover, electron and photon signatures can be distinguished both with the calorimetric measurement of local energy depositions at the shower start and with the cm-scale conversion gap signature of photons. This contribution discusses event reconstruction at ICARUS focusing on Pandora, a multi-algorithm pattern recognition software widely used in LArTPC experiments. Over a hundred Pandora algorithms and tools are used to reconstruct cosmic rays and neutrino interactions in the ICARUS detector. Recent developments have focused on the reconstruction of electromagnetic shower signatures, crucial to ensure a robust and efficient reconstruction of charged-current $\nu_e$ interactions, which serve as a key signature of sterile neutrino oscillations at SBN. In this contribution, recent improvements to the reconstruction are discussed, focusing on the discrimination between tracks and electromagnetic showers using neutrino simulations and data.

Triozzi, Riccardo [Padua U.; INFN, Padua] (ORCID:0↗
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 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. 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.

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 OSTI2022

Scintillation light detection in the 6-m drift length ProtoDUNE Dual Phase liquid argon TPC

The Deep Underground Neutrino Experiment (DUNE) is a leading-edge experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE-Dual Phase (DP) is a 6 × 6 × 6 m$^{3}$ liquid argon time-projection-chamber (LArTPC) operated at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE far detector. In ProtoDUNE-DP, the scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, we present the performance of the ProtoDUNE-DP photon detection system, comparing different wavelength-shifting techniques and the use of xenon-doped LAr as a promising option for future large LArTPCs. The scintillation light production and propagation processes are analyzed and compared to simulations, improving understanding of the liquid argon properties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Neutrino Hunting: Looking through a UV Lens Scintillation Photon Detection in a Large-Volume Liquid Argon Time Projection Chamber, Exposed to a Multi-GeV Charged Particle Beam

The Deep Underground Neutrino Experiment (DUNE) will be a world-class neutrino observatory and nucleon decay detector designed to answer fundamental questions about elementary particles and their role in the universe. The DUNE experiment will consist of a a Near Detector, located at Fermilab, and a Far Detector, approximately 1.5~km underground at the Sanford Underground Research Facility in South Dakota, located $\sim$1300~km away. The accelerator complex at Fermilab will host an intense beam of neutrinos directed toward the two detectors. My dissertation centers on the implementation of technologies used to detect scintillation photon signals in liquid argon in the context of the DUNE's Far Detector Single-Phase (SP) module design, and features direct contributions to the Photon Detection System (PDS) deployed in the ProtoDUNE-SP Large-Volume Liquid Argon Time Projection Chamber (LArTPC) prototype. The PDS is needed for non-beam event timing, such as atmospheric neutrinos, proton d ecay, and supernova detection. The PDS provides a prompt signal ($t_{0}$ information) for micro-second event time determination, which improves the TPC's spatial localization along drift direction, enables accurate ionization-signal-attenuation determination, and even provides calorimetry. My dissertation will discuss an overview of the DUNE and ProtoDUNE-SP experiment and how we detect neutrinos in LAr, via charge and scintillation light. It will discuss my core experimental and analysis work, in regards to the Photon Detection System; including my contributions in establishing procedures for the commissioning and integration for the Photon Detector System that will be valuable during the construction, installation, commissioning, and operations of the DUNE Far Detector. In addition, it will comprehensively discuss the capability of three different photon detection technologies, and their characteristics and responses to muon and electron beam particles over a range of beam momenta , from 0.3~GeV/$c$ - 7~GeV/$c$. Further, the overall progress detailed in this thesis will help pave the way toward understanding the physical properties of these detectors, which will contribute to the success of the sensitivity measurements required for determining the neutrino mass hierarchy and $\delta_{CP}$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Demonstration and performance of an online data selection algorithm for liquid argon time projection chambers using MicroBooNE

The MicroBooNE detector is a liquid argon time projection chamber (LArTPC) that produces three-dimensional images of particle interactions using ionization charge collected by anode wire plane arrays and scintillation light collected by a light detection system. In addition to testing long-standing experimental neutrino anomalies and performing measurements of neutrino interactions with argon nuclei using the Fermilab Booster Neutrino Beam, MicroBooNE aims to develop methodologies for rare beyond the Standard Model and off-beam physics searches. Looking ahead to the upcoming Deep Underground Neutrino Experiment (DUNE), with MicroBooNE serving as a valuable testbed, achieving high sensitivity and livetime for off-beam physics while satisfying data processing and storage constraints will require data-driven, intelligent, and online or real-time data selection techniques. These techniques are essential for reducing data rates and preserving rare signals with high accuracy. In this paper, we describe a fast data selection algorithm suitable for online execution to identify electrons from stopping cosmic ray muons in the MicroBooNE detector utilizing ionization charge information, and present its performance. This represents the first demonstration of online data selection in a LArTPC using real data and charge information exclusively and provides an important proof-of-principle for applying such techniques to other LArTPC experiments such as the Short-Baseline Near Detector and DUNE.

Abratenko, P. [Tufts U. (main)]↗
DOE OSTI2021

Development of a 83 mKr source for the calibration of the CENNS-10 liquid argon detector

We report on the preparation of and calibration measurements with a 83 mKr source for the CENNS-10 liquid argon detector. 83 mKr atoms generated in the decay of a 83 Rb source were introduced into the detector via injection into the Ar circulation loop. Scintillation light arising from the 9.4 keV and 32.1 keV conversion electrons in the decay of 83 mKr in the detector volume were then observed. This calibration source allows the characterization of the low-energy response of the CENNS-10 detector and is applicable to other low-energy-threshold detectors. The energy resolution of the detector was measured to be 9% at the total 83 mKr decay energy of 41.5 keV. Lastly, we performed an analysis to separately calibrate the detector using the two conversion electrons at 9.4 keV and 32.1 keV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Analysis of scintillation light dependence on liquid Argon purity

Previous studies have investigated the correlation between impurity concentrations in Liquid Argon (LAr) and the temporal evolution of either the slow scintillation decay time or the light yield. These impurities typically consist of various molecular species. Electronegative contaminants directly affect electron drift and photon production, while other molecules, such as nitrogen (N_2),can influence LAr scintillation properties without necessarily affecting electron lifetime. Many current and future neutrino and dark-matter experiments use LAr detectors. This study aims to evaluate the measured electron lifetimes in relation to the timing characteristics of the scintillation light signal in the SBN ICARUS detector at Fermi National Accelerator Laboratory. The ICARUS experiment consists of two cryostats that have shown some discrepancies in the measured electron lifetime over the years. In particular, this study addresses the use of data collected under varying purity conditions in the two cryostats.

Saia, Clara [Catania Astrophys. Observ.]↗
DOE OSTI2021

Sensitivity of future liquid argon dark matter search experiments to core-collapse supernova neutrinos

Future liquid-argon DarkSide-20k and Argo detectors, designed for direct dark matter search, will be sensitive also to core-collapse supernova neutrinos, via coherent elastic neutrino-nucleus scattering. This interaction channel is flavor-insensitive with a high-cross section, enabling for a high-statistics neutrino detection with target masses of ~50 t and ~360 t for DarkSide-20k and Argo respectively. Thanks to the low-energy threshold of ~0.5 keVnr achievable by exploiting the ionization channel, DarkSide-20k and Argo have the potential to discover supernova bursts throughout our galaxy and up to the Small Magellanic Cloud, respectively, assuming a 11-M progenitor star. In this work, we report also on the sensitivity to the neutronization burst, whose electron neutrino flux is suppressed by oscillations when detected via charged current and elastic scattering. Finally, the accuracies in the reconstruction of the average and total neutrino energy in the different phases of the supernova burst, as well as its time profile, are also discussed, taking into account the expected background and the detector response.

79 ASTRONOMY AND ASTROPHYSICS↗