Large Liquid Argon Time Projection Chamber Research Articles

Observation of radon mitigation in MicroBooNE by a liquid argon filtration system

The MicroBooNE liquid argon time projection chamber (LArTPC) maintains a high level of liquid argon purity through the use of a filtration system that removes electronegative contaminants in continuously-circulated liquid, recondensed boil off, and externally supplied argon gas. We use the MicroBooNE LArTPC to reconstruct MeV-scale radiological decays. Using this technique we measure the liquid argon filtration system's efficacy at removing radon. This is studied by placing a 500 kBq 222Rn source upstream of the filters and searching for a time-dependent increase in the number of radiological decays in the LArTPC. In the context of two models for radon mitigation via a liquid argon filtration system, a slowing mechanism and a trapping mechanism, MicroBooNE data supports a radon reduction factor of greater than 97% or 99.999%, respectively. Furthermore, a radiological survey of the filters found that the copper-based filter material was the primary medium that removed the 222Rn. This is the first observation of radon mitigation in liquid argon with a large-scale copper-based filter and could offer a radon mitigation solution for future large LArTPCs.

Adversarial methods to reduce simulation bias in neutrino interaction event filtering at liquid argon time projection chambers

For current and future neutrino oscillation experiments using large Liquid Argon Time Projection Chambers (LAr-TPCs), a key challenge is identifying neutrino interactions from the pervading cosmic-ray background. Rejection of such background is often possible using traditional cut-based selections, but this typically requires the prior use of computationally expensive reconstruction algorithms. This work demonstrates an alternative approach of using a 3D Submanifold Sparse Convolutional Network trained on low-level information from the scintillation light signal of interactions inside LAr-TPCs. This technique is applied to example simulations from ICARUS, the far detector of the Short Baseline Neutrino (SBN) program at Fermilab. The results of the network, show that cosmic background is reduced by up to 76.3% whilst neutrino interaction selection efficiency remains over 98.9%. We further present a way to mitigate potential biases from imperfect input simulations by applying Domain Adversarial Neural Networks (DANNs), for which modified simulated samples are introduced to imitate real data and a small portion of them are used for adverserial training. A series of mock-data studies are performed and demonstrate the effectiveness of using DANNs to mitigate biases, showing neutrino interaction selection efficiency performances significantly better than that achieved without the adversarial training.

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 m3 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.

Characterization of the DUNE photodetectors and study of the event burst phenomenon

The Deep Underground Neutrino Experiment (DUNE) is an upcoming neutrino physics experiment that will answer some of the most compelling questions in particle physics and cosmology. The DUNE far detectors employ silicon photomultipliers (SiPMs) to detect light produced by charged particles interacting in a large liquid argon time projection chamber (LArTPC). The SiPMs are photosensors consisting of an array of single-photon avalanche diodes (SPAD) operating in Geiger mode. Their high sensitivity and dynamic range, as well as the possibility to fill large surfaces with high-granularity sensors, makes them an ideal choice for DUNE. An international consortium of research groups is currently engaged in a systematic comparison of the performances of the SiPM models that have been custom developed for DUNE by two manufacturers. Such detailed studies, which include gain measurements and a structure study of the dark count rate at 77 K, are meant to determine the best choice of the photodetection system for DUNE, as well as characterize the response of the chosen detectors for the DUNE simulation. Moreover, an investigation of a newly observed phenomenon, in which quick bursts of tens of events at close range are collected in individual SiPMs, is being carried out, which potentially impacts the design of future models and their implementation in particle physics experiments.

Cosmic Ray Background Rejection with Wire-Cell LArTPC Event Reconstruction in the MicroBooNE Detector

For a large liquid argon time projection chamber (LArTPC) operating on or near the Earth's surface to detect neutrino interactions, the rejection of cosmogenic background is a critical and challenging task because of the large cosmic ray flux and the long drift time of the TPC. We introduce a superior cosmic background rejection procedure based on the Wire-Cell three-dimensional (3D) event reconstruction for LArTPCs. From an initial 1:20,000 neutrino to cosmic-ray background ratio, we demonstrate these tools on data from the MicroBooNE experiment and create a high performance generic neutrino event selection with a cosmic contamination of 14.9\% (9.7\%) for a visible energy region greater than O(200)~MeV. The neutrino interaction selection efficiency is 80.4\% and 87.6\% for inclusive $\nu_\mu$ charged-current and $\nu_e$ charged-current interactions, respectively. This significantly improved performance compared to existing reconstruction algorithms, marks a major milestone toward reaching the scientific goals of LArTPC neutrino oscillation experiments operating near the Earth's surface.

Prospects for detecting boosted dark matter in DUNE through hadronic interactions

Boosted dark matter (BDM) is a well-motivated class of dark matter (DM) candidates in which a small component of DM is relativistic at the present time. We lay the foundation for BDM searches via hadronic interactions in large liquid-argon time-projection chambers (LArTPCs), such as DUNE. We investigate BDM-nucleus scattering in detail by developing new event generation techniques with a parameterized detector simulation. We study the discovery potential in a DUNE-like experiment using the low threshold and directionality of hadron detection in LArTPCs and compare with other experiments.

Measurement of space charge effects in the MicroBooNE LArTPC using cosmic muons

Large liquid argon time projection chambers (LArTPCs), especially those operating near the surface, are susceptible to space charge effects. In the context of LArTPCs, the space charge effect is the build-up of slow-moving positive ions in the detector primarily due to ionization from cosmic rays, leading to a distortion of the electric field within the detector. This effect leads to a displacement in the reconstructed position of signal ionization electrons in LArTPC detectors (“spatial distortions”), as well as to variations in the amount of electron-ion recombination experienced by ionization throughout the volume of the TPC. We present techniques that can be used to measure and correct for space charge effects in large LArTPCs by making use of cosmic muons, including the use of track pairs to unambiguously pin down spatial distortions in three dimensions. The performance of these calibration techniques are studied using both Monte Carlo simulation and MicroBooNE data, utilizing a UV laser system as a means to estimate the systematic bias associated with the calibration methodology.

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. 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.

Scalable deep convolutional neural networks for sparse, locally dense liquid argon time projection chamber data

Deep convolutional neural networks (CNNs) show strong promise for analyzing scientific data in many domains including particle imaging detectors such as a liquid argon time projection chamber (LArTPC). Yet the high sparsity of LArTPC data challenges traditional CNNs which were designed for dense data such as photographs. A naive application of CNNs on LArTPC data results in inefficient computations and a poor scalability to large LArTPC detectors such as the Short Baseline Neutrino Program and Deep Underground Neutrino Experiment. Recently Submanifold Sparse Convolutional Networks (SSCNs) have been proposed to address this challenge. We report their performance on a 3D semantic segmentation task on simulated LArTPC samples. In comparison with standard CNNs, we observe that the computation memory and wall-time cost for inference are reduced by factor of 364 and 33 respectively without loss of accuracy. The same factors for 2D samples are found to be 93 and 3.1 respectively. Using SSCN, we present the first machine learning-based approach to the reconstruction of Michel electrons using public 3D LArTPC samples. We find a Michel electron identification efficiency of 93.9% with 96.7% of true positive rate. Reconstructed Michel electron clusters yield 95.4% in average pixel clustering efficiency and 95.5% in purity. The results are compelling to show strong promise of scalable data reconstruction technique using deep neural networks for large scale LArTPC detectors.

Study of space charge in the ICARUS T600 detector

The accumulation of positive ions, produced by ionizing particles crossing Liquid Argon Time Projection Chambers (LAr-TPCs), may generate distortions of the electric drift field affecting the track reconstruction of the ionizing events. These effects could become relevant for large LAr-TPCs operating at surface or at shallow depth, where the detectors are exposed to a copious flux of cosmic rays. A detailed study of such possible field distortions in the ICARUS T600 LAr-TPC has been performed analyzing a sample of cosmic muon tracks recorded with one T600 module operated at surface in 2001. The maximum track distortion turns out to be of few mm in good agreement with the prediction by a numerical calculation. As a cross-check, the same analysis has been performed on a cosmic muon sample recorded during the ICARUS T600 run at the LNGS underground laboratory, where the cosmic ray flux was suppressed by a factor ∼106 by 3400 m water equivalent shielding. No appreciable distortion has been observed, confirming that the effects measured on surface are actually due to ion space charge.

Status of ProtoDUNE Dual Phase

The Deep Underground Neutrino Experiment (DUNE) will use a large liquid argon (LAr) detector consisting of four modules each with a fiducial mass of 10 ktons of LAr. One of the technology options for the far detector modules is a liquid-argon Time Projection Chamber (TPC) working in Dual Phase mode. A large demonstrator, called ProtoDUNE Dual-Phase, with a 6×6×6 m3(300t) active volume, is currently under-construction at the CERN neutrino platform. As well as being the engineering prototype of a Far Detector module, it will also demonstrate the concept of a very large Dual-Phase LAr TPC. The design of the TPC including the fabrication, testing, installation and commissioning of the various detector components is outlined.

Demonstration of MeV-scale physics in liquid argon time projection chambers using ArgoNeuT

MeV-scale energy depositions by low-energy photons produced in neutrino-argon interactions have been identified and reconstructed in ArgoNeuT liquid argon time projection chamber (LArTPC) data. ArgoNeuT data collected on the NuMI beam at Fermilab were analyzed to select isolated low-energy depositions in the TPC volume. The total number, reconstructed energies and positions of these depositions have been compared to those from simulations of neutrino-argon interactions using the FLUKA Monte Carlo generator. Measured features are consistent with energy depositions from photons produced by de-excitation of the neutrino's target nucleus and by inelastic scattering of primary neutrons produced by neutrino-argon interactions. This study represents a successful reconstruction of physics at the MeV-scale in a LArTPC, a capability of crucial importance for detection and reconstruction of supernova and solar neutrino interactions in future large LArTPCs.

Three-dimensional imaging for large LArTPCs

High-performance event reconstruction is critical for current and future massive liquid argon time projection chambers (LArTPCs) to realize their full scientific potential. LArTPCs with readout using wire planes provide a limited number of 2D projections. In general, without a pixel-type readout it is challenging to achieve unambiguous 3D event reconstruction. As a remedy, we present a novel 3D imaging method, Wire-Cell, which incorporates the charge and sparsity information in addition to the time and geometry through simple and robust mathematics. The resulting 3D image of ionization density provides an excellent starting point for further reconstruction and enables the true power of 3D tracking calorimetry in LArTPCs.

DarkSide-20k: A 20 tonne two-phase LAr TPC for direct dark matter detection at LNGS

Building on the successful experience in operating the DarkSide-50 detector, the DarkSide Collaboration is going to construct DarkSide-20k, a direct WIMP search detector using a two-phase Liquid Argon Time Projection Chamber (LArTPC) with an active (fiducial) mass of 23 t (20 t). The DarkSide-20k LArTPC will be deployed within a shield/veto with a spherical Liquid Scintillator Veto (LSV) inside a cylindrical Water Cherenkov Veto (WCV). Operation of DarkSide-50 demonstrated a major reduction in the dominant $^{39}$Ar background when using argon extracted from an underground source, before applying pulse shape analysis. Data from DarkSide-50, in combination with MC simulation and analytical modeling, shows that a rejection factor for discrimination between electron and nuclear recoils of $\gt3\times10^9$ is achievable. This, along with the use of the veto system, is the key to unlocking the path to large LArTPC detector masses, while maintaining an "instrumental background-free" experiment, an experiment in which less than 0.1 events (other than $\nu$-induced nuclear recoils) is expected to occur within the WIMP search region during the planned exposure. DarkSide-20k will have ultra-low backgrounds than can be measured in situ. This will give sensitivity to WIMP-nucleon cross sections of $1.2\times10^{-47}$ cm$^2$ ($1.1\times10^{-46}$ cm$^2$) for WIMPs of $1$ TeV$/c^2$ ($10$ TeV$/c^2$) mass, to be achieved during a 5 yr run producing an exposure of 100 t yr free from any instrumental background. DarkSide-20k could then extend its operation to a decade, increasing the exposure to 200 t yr, reaching a sensitivity of $7.4\times10^{-48}$ cm$^2$ ($6.9\times10^{-47}$ cm$^2$) for WIMPs of $1$ TeV$/c^2$ ($10$ TeV$/c^2$) mass.

Measurements of muon neutrino charged-current interactions by the MicroBooNE experiment

MicroBooNE is a 170 ton Liquid Argon Time Projection Chamber (LArTPC) experiment located at Fermi National Accelerator Laboratory. It has been operating in the Booster neutrino beam since October 2015 and is already demonstrating the superb imaging capabilities of LArTPC detectors. MicroBooNE is the first large LArTPC detector to be exposed to a high-intensity neutrino beam. Among its primary physics goals are precise measurements of muon neutrino charged-current (CC) interactions on argon. In order to analyse its high-statistics data, a suite of fully automated techniques have been developed that reconstruct the LArTPC images and separate muon neutrino CC interactions from their cosmic-ray and neutral current backgrounds. These proceedings will describe the reconstruction and selection of muon neutrino CC event candidates, and present measured distributions of the observed events based on 5e19 protons on target from the first MicroBooNE data-taking period.

Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

Testing of cryogenic photomultiplier tubes for the MicroBooNE experiment

The MicroBooNE detector, to be located on axis in the Booster Neutrino Beamline (BNB) at the Fermi National Accelerator Laboratory (Fermilab), consists of two main components: a large liquid argon time projection chamber (LArTPC), and a light collection system. Thirty-two 8-inch diameter Hamamatsu R5912-02mod cryogenic photomultiplier tubes (PMTs) will detect the scintillation light generated in the liquid argon (LAr). This article first describes the MicroBooNE PMT performance test procedures, including how the light collectionsystem functions in the detector, and the design of the PMT base. The design of the cryogenic test stand is then discussed, and finally the results of the cryogenic tests are reported.

A measurement of the absorption of liquid argon scintillation light by dissolved nitrogen at the part-per-million level

We report on a measurement of the absorption length of scintillationlight in liquid argon due to dissolved nitrogen at the part-per-million (ppm)level. We inject controlled quantities of nitrogen into a highpurity volume of liquid argon and monitor the light yield from an alpha source.The source is placed at different distances from a cryogenic photomultiplier tube assembly. By comparing the light yield from each position we extractthe absorption cross section of nitrogen. Wefind that nitrogen absorbs argon scintillation light with strength of (1.51±0.15) × 10−4 cm−1ppm−1, correspondingto an absorption cross section of (4.99±0.51) × 10−21 cm2molecule−1.We obtain the relationship between absorption length and nitrogenconcentration over the 0 to 50 ppm range and discuss the implicationsfor the design and data analysis of future large liquid argon time projection chamber (LArTPC)detectors. Our results indicate that for a current-generation LArTPC, wherea concentration of 2 parts per million of nitrogen is expected, the attenuationlength due to nitrogen will be 30±3 meters.

Results from the Fermilab Materials Test Stand and Status of the Liquid Argon Purity Demonstrator

The Fermilab Materials Test Stand was developed to test the suitability of materials for use in large liquid argon time projection chambers (TPCs). In addition to determining which materials are viable for use in TPCs, the test stand has also shown that water is especially detrimental to maintaining long electron lifetimes. The Liquid Argon Purity Demonstrator is currently under construction at Fermilab. Its goal is to show that long electron lifetimes can be achieved without evacuation of the cryostat, which is of particular interest in designing large liquid argon TPCs.