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Register a new userA steerable UV laser system for the calibration of liquid argon time projection chambers
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A number of liquid argon time projection chambers (LAr TPCs) are being build or are proposed for neutrino experiments on long- and short baseline beams. For these detectors a distortion in the drift field due to geometrical or physics reasons can affect the reconstruction of the events. Depending on the TPC geometry and electric drift field intensity this distortion could be of the same magnitude as the drift field itself. Recently, we presented a method to calibrate the drift field and correct for these possible distortions. While straight cosmic ray muon tracks could be used for calibration, multiple coulomb scattering and momentum uncertainties allow only a limited resolution. A UV laser instead can create straight ionization tracks in liquid argon, and allows one to map the drift field along different paths in the TPC inner volume. Here we present a UV laser feed-through design with a steerable UV mirror immersed in liquid argon that can point the laser beam at many locations through the TPC. The straight ionization paths are sensitive to drift field distortions, a fit of these distortion to the linear optical path allows to extract the drift field, by using these laser tracks along the whole TPC volume one can obtain a 3D drift field map. The UV laser feed-through assembly is a prototype of the system that will be used for the MicroBooNE experiment at the Fermi National Accelerator Laboratory (FNAL).
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A 10 kilo-tonne dual-phase liquid argon TPC is one of the detector options considered for the Deep Underground Neutrino Experiment (DUNE). The detector technology relies on amplification of the ionisation charge in ultra-pure argon vapour and oers several advantages compared to the traditional single-phase liquid argon TPCs. A 4.2 tonne dual-phase liquid argon TPC prototype, the largest of its kind, with an active volume of 3x1x1 $m^3$ has been constructed and operated at CERN. In this paper we describe in detail the experimental setup and detector components as well as report on the operation experience. We also present the first results on the achieved charge amplification, prompt scintillation and electroluminescence detection, and purity of the liquid argon from analyses of a collected sample of cosmic ray muons.
Liquid Argon Time Projection Chambers (LArTPCs) have been selected for the future long-baseline Deep Underground Neutrino Experiment (DUNE). To allow LArTPCs to operate in the high-multiplicity near detector environment of DUNE, a new charge readout technology is required. Traditional charge readout technologies introduce intrinsic ambiguities, combined with a slow detector response, these ambiguities have limited the performance of LArTPCs, until now. Here, we present a novel pixelated charge readout that enables the full 3D tracking capabilities of LArTPCs. We characterise the signal to noise ratio of charge readout chain, to be about 14, and demonstrate track reconstruction on 3D space points produced by the pixel readout. This pixelated charge readout makes LArTPCs a viable option for the DUNE near detector complex.
Liquid argon time projection chambers (LArTPCs) are now a standard detector technology for making accelerator neutrino measurements, due to their high material density, precise tracking, and calorimetric capabilities. An electric field (E-field) is required in such detectors to drift ionized electrons to the anode to be collected. The E-field of a TPC is often approximated to be uniform between the anode and the cathode planes. However, significant distortions can appear from effects such as mechanical deformations, electrode failures, or the accumulation of space charge generated by cosmic rays. The latter is particularly relevant for detectors placed near the Earths surface and with large drift distances and long drift time. To determine the E-field in situ, an ultraviolet (UV) laser system is installed in the MicroBooNE experiment at Fermi National Accelerator Laboratory. The purpose of this system is to provide precise measurements of the E-field, and to make it possible to correct for 3D spatial distortions due to E-field non-uniformities. Here we describe the methodology developed for deriving spatial distortions, the drift velocity and the E-field from UV-laser measurements.
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.
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.
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