Time Projection Chamber Detector Research Articles

Molecular sieve vacuum swing adsorption purification and radon reduction system for gaseous dark matter and rare-event detectors

In the field of directional dark matter experiments SF6 has emerged as an ideal target gas. A critical challenge with this gas, and with other proposed gases, is the effective removal of contaminant gases. This includes radon which produce unwanted background events, but also common pollutants such as water, oxygen and nitrogen, which can capture ionisation electrons, resulting in loss of detector gas gain over time. We present here a novel molecular sieve (MS) based gas recycling system for the simultaneous removal of both radon and common pollutants from SF6. The apparatus has the additional benefit of minimising gas required in experiments and utilises a Vacuum Swing Adsorption (VSA) technique for continuous, long-term operation. The gas system's capabilities were tested with a 100 L low-pressure SF6 Time Projection Chamber (TPC) detector. For the first time, we present a newly developed low-radioactive MS type 5 Å. This material was found to emanate radon at 98% less per radon captured compared to commercial counterparts, the lowest known MS emanation at the time of writing. Consequently, the radon activity in the TPC detector was reduced, with an upper limit of less than 7.2 mBq at a 95% confidence level (C.L.). Incorporation of MS types 3 Å and 4 Å to absorb common pollutants was found successfully to mitigate against gain deterioration while recycling the target gas.

Kubernetes for the Deep Underground Neutrino Experiment Data Acquisition

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino experiment based in the USA which is expected to start taking data in 2029. DUNE aims to precisely measure neutrino oscillation parameters by detecting neutrinos from the LBNF beamline (Fermilab) at the Far Detector, 1,300 kilometres away, in South Dakota at the Sanford Underground Research Facility. The Far Detector will consist of four cryogenic Liquid Argon Time Projection Chamber detectors of 17 kT, each producing more than 1 TB/sec of data. The main requirements for the data acquisition system are the ability to run continuously for extended periods of time, with a 99% up-time requirement, and the functionality to record both beam neutrinos and low energy neutrinos from the explosion of a neighbouring supernova, should one occur during the lifetime of the experiment. The key challenges are the high data rates that the detectors generate and the deep underground environment, which places constraints on power and space. To overcome these challenges, DUNE plans to use a highly optimised C++ software suite and a server farm of about 110 nodes continuously running about two hundred multicore processes located close to the detector, 1.5 kilometres underground. Thirty nodes will be at the surface and will run around two hundred processes simultaneously. DUNE is studying the use of the Kubernetes framework to manage containerised workloads and take advantage of its resource definitions and high up-time services to run the DAQ system. Progress in deploying these systems at the CERN neutrino platform on the prototype DUNE experiments is reported.

Reconstruction of missing data of the PandaX-IIIexperiment TPC using neural network

The PandaX-III is a Neutrinoless Double-Beta Decay (NLDBD) experiment which uses a Time Projection Chamber (TPC) detector with a readout plane formed of Micromegas modules, which allows reconstruction of track topology for the background discrimination as well as reconstruction of the energy of the events. In NLDBD experiments, in order to achieve the highest sensitivity to the decay, it is necessary for the detector to have a high energy resolution, the background level should be low, and techniques for background discrimination must be applied as well. In reality, inhomogeneous signal gain at each module and the presence of missing channels lead to an incorrect energy reconstruction of the events. In this work, a method based on a Convolutional Neural Networks (CNN) aiming to reconstruct the kinematics of the event from imperfect data with missing channels is presented. Preliminary results of the reconstruction of the missing data using CNN are showing an increase in detection efficiency. The detection efficiency was evaluated on the simulated data with three channels randomly chosen per Micromegas module and artificially set as missing. Direct reconstruction of the energy gives the efficiency of 78%, while after applying CNN it increases to 86%, providing a promising application of this technique.

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1pm 0.6% and 84.1pm 0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.

A numerical solver for investigating the space charge effect on theelectric field in liquid argon time projection chambers

This paper reports the development of a numerical solver aimed to simulate the interaction between the space charge (i.e. ions) distribution and the electric field in liquid argon time projection chamber (LArTPC) detectors. The ion transport equation is solved by a time-accurate, cell-centered finite volume method and the electric potential equation by a continuous finite element method. The electric potential equation updates the electric field which provides the drift velocity to the ion transport equation. The ion transport equation updates the space charge density distribution which appears as the source term in the electric potential equation. The interaction between the space charge distribution and the electric field is numerically simulated within each physical time step. The convective velocity in the ion transport equation can include the background flow velocity in addition to the electric drift velocity. The numerical solver has been parallelized using the Message Passing Interface (MPI) library. Numerical tests show and verify the capability and accuracy of the current numerical solver. It is planned that the developed numerical solver, together with a Computational Fluid Dynamics (CFD) package which provides the flow velocity field, can be used to investigate the space charge effect on the electric field in large-scale particle detectors.

Development of multichannel readout electronics prototype system for TPC detector of CSR External-Target Experiment

We present a multichannel readout electronics prototype system developed for the Time Projection Chamber (TPC) detector of CSR External-Target Experiment (CEE). The whole system consists of two Front-End readout Electronics (FEE) boards, fiber converters, host computers and a trigger fan-out board. A single FEE board is mainly equipped with four SAMPA chips and a Field Programmable Logic Array (FPGA), processing 128 channels of signals from the TPC detector. The SAMPA chips convert the charge signals into digital signals and send them to FPGA for data processing, and then transmit the data to the host computer through a fiber converter. The control commands from the host computer software realize the control of SAMPA and monitor temperature and current. In the dynamic range of input charge from 2 fC to 100 fC, the readout electronics output amplitude linearity is better than 1%. The relative energy resolution of electronics is about 23% at a minimum input charge of 1.4 fC. The test results with TPC illustrate that with a 55Fe source, an energy resolution of 28.5% was acquired, and with cosmic rays, the track resolution on the pad plane is less than 390μm.

The light detection system of the ICARUS detector in the Short Baseline Neutrino program at Fermilab

The Short Baseline Neutrino (SBN) program at Fermilab is an extensive experimental programme aiming at searching for sterile neutrino(s) [1], whose existence is one of the fundamental open questions of neutrino physics. It employs three Liquid Argon Time Projection Chamber (LArTPC) detectors, called ICARUS, MicroBooNE and SBND, sampling the Booster Neutrino Beam (BNB) at different locations from its target. The SBN detectors, working near the Earth’s surface, are subjected to a substantial cosmic background, which can mimic genuine neutrino interactions. Thus, it is essential to distinguish the signals related to the neutrino beams from those induced by the cosmic rays. The light detection system is a vital part of LArTPCs, but its role is even more critical for surface-operating detectors like ICARUS. The ICARUS light detection system is based on 360 Photomultiplier Tubes (PMTs). Its main role is to provide an efficient trigger and contribute to the 3D reconstruction of detected events. The light detection system calibration and further trigger system improvements were performed for the final detector configuration during the detector commissioning at Fermilab. The trigger system effectively exploits the information given by the PMTs. To further increase that system’s efficiency in event filtering, an alternative method based on Convolutional Neural Network (CNN) has been developed. Simulation-based results show that this technique can reduce the cosmic background by up to 76% with a neutrino selection efficiency of 99%. However, to filter the real data cases, which are usually not identical to the simulated ones, this method was improved by applying Domain Adversarial Neural Network (DANN). The results prove that adversarial training through a DANN can alleviate the simulation bias, demonstrating the first successful application of DANN for CNN as an event classifier for a LArTPC.

Warsaw Active-Target TPC: A new detector for photonuclear reactions studies at astrophysical energies

An active-target time-projection chamber (TPC) optimised for studying nuclear reactions of astro-physical interest was developed by the University of Warsaw for studying photo-disintegration reactions using intense, monochromatic γ-ray beams. Different reactions can be studied by tuning composition and density of the gaseous target for particular energy of the gamma beam. The Warsaw TPC detector, with its active volume of about 33x20x20 cm3 centred around the beam axis and micro-pattern structures (GEMs) employed to amplify the primary ionisation induced by charged particles produced in reactions in the gaseous target, is characterised by a readout based on signal strips, arranged into 3-coordinate redundant system. The 3D kinematics of charged particles in the event are reconstructed from a total of about 103 channels read out by digitising front-end electronics based on the General Electronics for TPCs (GET). In this paper the principles of detector operation and basic track reconstruction methods are discussed and illustrated by means of preliminary results from pilot measurements conducted in 2021-22.

Status and prospects of TPC prototype using the UV laser mimic tracks

To meet the high precision physical goals in the future e + e − circular collider (CEPC), the high resolution tracker detector for the particle track reconstruction (¡100μ m) and particle identification are required. Time Projection Chamber (TPC) is one of the main concept option of the central tracker detector. On behalf of the track detector subgroup in CEPC, the status and update R&D results of TPC module and prototype for the specific requirements will be presented in this article. TPC module will could suppress the ions in chamber continuously running in the different gains (2000-5000) and T2K mixture gases, and TPC prototype with Micro-pattern Gaseous Detector (MPGD) detector module integrated the narrow laser mimic tracks system. the update results of the spatial resolution, particles identified (dE/dx) were been investigated. In this TPC prototype, the precision drift time of the different laser mimic tracks ionized primary electrons in the specific operation working gases were recorded. Some considerations of the low power consumption readout requirements will be given according to the pad TPC detector operating at the high luminosity Z pole at CEPC.

Status and prospects of TPC module and prototype at high luminosity Z physics on CEPC

The Circular Electron–Positron Collider (CEPC) has been proposed as a Higgs and high luminosity [Formula: see text] factory for the last few years in China. To achieve the high precision physical goals at CEPC, the high resolution ([Formula: see text]) tracker for the particle track reconstruction and particle identification are demanded. Time Projection Chamber (TPC) is one of the main concept proposal of the central tracker detector in very large 3D volume, it has an excellent performance on the moment measurement, [Formula: see text] measurement and the spatial resolution. The simulation results were given when the TPC detector will operate at the high luminosity [Formula: see text] pole at the future [Formula: see text] circular collider. The pixelated readout TPC is a potential option to replace the traditional pad readout with the low gain, low occupancy, and outstanding pattern recognition. In the last several years, a TPC module, the readout electronics and prototype for the specific requirements have been developed at the Institute of High Energy Physics (IHEP). TPC module will could suppress the ions in chamber continuously running in the different gains (2000–5000) under T2K mixture gases. A TPC prototype with [Formula: see text] active area G detector module integrated the narrow 266[Formula: see text]nm UV laser tracks along the drift length of 500[Formula: see text]mm, and the low power consumption ([Formula: see text]) Application-Specific Integrated Circuits (ASIC) chip including analog to digital converter (ADC) function has been developed too. The update results of the spatial resolution has been obtained after some experimental studies have been done by the TPC prototype.

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.

Effect of diffusion on the peak value of energy loss observed in a LArTPC

Liquid Argon Time Projection Chamber (LArTPC) detectors observe ionization electrons to measure charged particle trajectories and energy. In a LArTPC, the long time (∼ms) between when the ionization is produced and when it is collected means that diffusion can smear the charge by an amount comparable to the spatial resolution of the detector, given by the spacing between charge sensing channels (∼mm). This smearing has an impact on the distribution of energy losses measured by each channel. In particular, the smearing increases the length of the charged particle trajectory observed by each channel, and therefore the most-probable-value (MPV) of particle energy loss recorded by that channel. We find, for example, that this effect shifts the MPV dE/dx of a muon with an energy of 1 GeV by ∼4% for a 2 ms drift time and 4.7 mm wire spacing, as in the DUNE-FD LArTPC. This has implications for the energy-scale calibration and electron lifetime measurements in a LArTPC, which both use the MPV of the muon energy loss distribution as a “standard candle”. The impact of diffusion on these calibrations is assessed.

Implementation of the trigger system of the ICARUS-T600 detector at Fermilab

The ICARUS-T600 liquid argon (LAr) time projection chamber (TPC) detector is currently deployed as a far detector of the Short Baseline Neutrino (SBN) program at Fermilab (USA) to search for a possible LSND-like sterile neutrino signal at Δm2≈1 eV2 with the Booster (BNB) and Main Injector (NuMI) Neutrino Beams [1]. A global physical event rate of ≈0.6Hz, including the genuine neutrino interactions in LAr, beam halos and cosmic interactions inside the proton pulse time windows, is expected, roughly corresponding to ≈4 PB of data for the total 6.6×1020 protons on target exposure if the full ICARUS-T600 detector is read-out (≈200 MB event size). The designed trigger system described here would collect the genuine neutrino interactions with a ≈95% expected efficiency.

Performance of TPC detector prototype integrated with UV laser tracks for the circular collider

Several new experimental concepts in high-energy particle physics have been proposed in recent years. The physical goals include precisely measuring the properties of particles such as Higgs, Z and W, and even looking for signs of new physics at future colliders. To meet the evolving requirements for particle track detector, Time Projection Chamber (TPC) detector prototype integrated with a UV laser track system was developed for the main track detector at Circular Electron Positron Collider (CEPC). This prototype consists of 6 horizontal laser tracks around TPC detector chamber, a fast electronics readout of 1280 channels, a GEM detector with 200×200mm2 active area, and the DAQ system. The hit resolution, dE/dx resolution and drift velocity were studied by measuring and analyzing using the TPC prototype and UV laser tracks. The dE/dx resolution of the prototype was measured to be (8.9±0.4)%. Extrapolating this to CEPC TPC with 220 layers and longer track, the resolution was estimated to be (3.36±0.26)%. All results indicated that the TPC detector prototype integrated with UV laser tracks can work well.

Search for an anomalous excess of inclusive charged-current νe interactions in the MicroBooNE experiment using Wire-Cell reconstruction

We report a search for an anomalous excess of inclusive charged-current (CC) $\nu_e$ interactions using the Wire-Cell event reconstruction package in the MicroBooNE experiment, which is motivated by the previous observation of a low-energy excess (LEE) of electromagnetic events from the MiniBooNE experiment. With a single liquid argon time projection chamber detector, the measurements of $\nu_{\mu}$ CC interactions as well as $\pi^0$ interactions are used to constrain signal and background predictions of $\nu_e$ CC interactions. A data set collected from February 2016 to July 2018 corresponding to an exposure of 6.369 $\times$ 10$^{20}$ protons on target from the Booster Neutrino Beam at FNAL is analyzed. With $x$ representing an overall normalization factor and referred to as the LEE strength parameter, we select 56 fully contained $\nu_e$ CC candidates while expecting 69.6 $\pm$ 8.0 (stat.) $\pm$ 5.0 (sys.) and 103.8 $\pm$ 9.0 (stat.) $\pm$ 7.4 (sys.) candidates after constraints for the absence (eLEE$_{x=0}$) of the median signal strength derived from the MiniBooNE observation and the presence (eLEE$_{x=1}$) of that signal strength, respectively. Under a nested hypothesis test using both rate and shape information in all available channels, the best-fit $x$ is determined to be 0 (eLEE$_{x=0}$) with a 95.5% confidence level upper limit of $x$ at 0.502. Under a simple-vs-simple hypotheses test, the eLEE$_{x=1}$ hypothesis is rejected at 3.75$\sigma$, while the eLEE$_{x=0}$ hypothesis is shown to be consistent with the observation at 0.45$\sigma$. In the context of the eLEE model, the estimated 68.3% confidence interval of the $\nu_e$ hypothesis to explain the LEE observed in the MiniBooNE experiment is disfavored at a significance level of more than 2.6$\sigma$ (3.0$\sigma$) considering MiniBooNE's full (statistical) uncertainties.

Probing light vector mediators with coherent scattering at future facilities

Future experiments dedicated to the detection of Coherent Elastic Neutrino-Nucleus Scattering may be powerful tools in probing light new physics. In this paper we study the sensitivity on light Z′ mediators of two proposed experiments: a directional low pressure Time Projection Chamber detector, νBDX-DRIFT, that will utilize neutrinos produced at the Long Baseline Neutrino Facility, and several possible experiments to be installed at the European Spallation Source. We compare the results obtained with existing limits from fixed-target, accelerator, solar neutrino and reactor experiments. Furthermore, we show that these experiments have the potential to test unexplored regions that, in some case, could explain the anomalous magnetic moment of the muon or peculiar spectral features in the cosmic neutrino spectrum observed by IceCube.

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

A deep-learning based raw waveform region-of-interest finder for the liquid argon time projection chamber

The liquid argon time projection chamber (LArTPC) detector technology has an excellent capability to measure properties of low-energy neutrinos produced by the sun and supernovae and to look for exotic physics at very low energies. In order to achieve those physics goals, it is crucial to identify and reconstruct signals in the waveforms recorded on each TPC wire. In this paper, we report on a novel algorithm based on a one-dimensional convolutional neural network (CNN) to look for the region-of-interest (ROI) in raw waveforms. We test this algorithm using data from the ArgoNeuT experiment in conjunction with an improved noise mitigation procedure and a more realistic data-driven noise model for simulated events. This deep-learning ROI finder shows promising performance in extracting small signals and gives an efficiency approximately twice that of the traditional algorithm in the low energy region of ∼0.03–0.1 MeV. This method offers great potential to explore low-energy physics using LArTPCs.

Oxygen Formation in the Light of Gamma-Beams: [Precision Measurements of the 12C(α, γ) Reaction with Gamma-Beams and a Time Projection Chamber

The carbon/oxygen (C/O) ratio at the end of stellar helium burning is not known with sufficient accuracy due to the large uncertainty in the cross-section of the 12C(α, γ)16O reaction. We developed a new method to measure this reaction that is significantly different from the experimental efforts of the past four decades. Data were measured with vanishingly small background, inside one detector, that also serves as an active target (AT-TPC). Angular distributions of the 12C(α, γ)16O reaction were obtained by measuring the inverse 16O(γ, α)12C reaction with gamma-beams (from the HIγS facility) and an optical readout time projection chamber (O-TPC) detector. We agree with current world data on the measured total reaction cross-section. We further evidence the strength of our method with angular distributions measured over the 1–resonance at Ecm ~ 2.4 MeV. We extract the E1-E2 mixing phase angle (ϕ12) over this resonance and obtained values that follow the trend of prediction based on unitarity of the scattering amplitude. Our technique promises to yield results that will surpass the quality of the currently available data. We continue these measurements to lower energies at the HIγS facility of TUNL at Duke University, and anticipate measurements down to Ecm = 1.1 MeV at the ELI-NP, the EU facility in Romania..

Precision measurements on oxygen formation in stellar helium burning with gamma-ray beams and a Time Projection Chamber

The carbon/oxygen (C/O) ratio at the end of stellar helium burning is the single most important nuclear input to stellar evolution theory. However, it is not known with sufficient accuracy, due to large uncertainties in the cross-section for the fusion of helium with 12C to form 16O, denoted as 12C(α, γ)16O. Here we present results based on a method that is significantly different from the experimental efforts of the past four decades. With data measured inside one detector and with vanishingly small background, angular distributions of the 12C(α, γ)16O reaction were obtained by measuring the inverse 16O(γ, α)12C reaction with gamma-beams and a Time Projection Chamber (TPC) detector. We agree with current world data for the total reaction cross-section and further evidence the strength of our method with accurate angular distributions measured over the 1− resonance at Ecm ~ 2.4 MeV. Our technique promises to yield results that will surpass the quality of the currently available data.