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Ortiz Arciniega, J. L., Carrio, F., & Valero, A. (2019). FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions. J. Instrum., 14, P09002–13pp.
Abstract: The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented.
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Caballero, L., Albiol, F., Corbi Bellot, A., Domingo-Pardo, C., Leganes Nieto, J. L., Agramunt Ros, J., et al. (2018). Gamma-ray imaging system for real-time measurements in nuclear waste characterisation. J. Instrum., 13, P03016–23pp.
Abstract: Acompact, portable and large field-of-viewgamma camera that is able to identify, locate and quantify gamma-ray emitting radioisotopes in real-time has been developed. The device delivers spectroscopic and imaging capabilities that enable its use it in a variety of nuclear waste characterisation scenarios, such as radioactivity monitoring in nuclear power plants and more specifically for the decommissioning of nuclear facilities. The technical development of this apparatus and some examples of its application in field measurements are reported in this article. The performance of the presented gamma-camera is also benchmarked against other conventional techniques.
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ATLAS TRT collaboration(Mindur, B. et al), Mitsou, V. A., & Valls Ferrer, J. A. (2016). Gas gain stabilisation in the ATLAS TRT detector. J. Instrum., 11, P04027–19pp.
Abstract: The ATLAS (one of two general purpose detectors at the LHC) Transition Radiation Tracker (TRT) is the outermost of the three tracking subsystems of the ATLAS Inner Detector. It is a large straw-based detector and contains about 350,000 electronics channels. The performance of the TRT as tracking and particularly particle identification detector strongly depends on stability of the operation parameters with most important parameter being the gas gain which must be kept constant across the detector volume. The gas gain in the straws can vary significantly with atmospheric pressure, temperature, and gas mixture composition changes. This paper presents a concept of the gas gain stabilisation in the TRT and describes in detail the Gas Gain Stabilisation System (GGSS) integrated into the Detector Control System (DCS). Operation stability of the GGSS during Run-1 is demonstrated.
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LHCb Collaboration(Aaij, R. et al), Jaimes Elles, S. J., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Rebollo De Miguel, M., et al. (2024). Helium identification with LHCb. J. Instrum., 19(2), P02010–23pp.
Abstract: The identification of helium nuclei at LHCb is achieved using a method based on measurements of ionisation losses in the silicon sensors and timing measurements in the Outer Tracker drift tubes. The background from photon conversions is reduced using the RICH detectors and an isolation requirement. The method is developed using pp collision data at root s = 13 TeV recorded by the LHCb experiment in the years 2016 to 2018, corresponding to an integrated luminosity of 5.5 fb(-1). A total of around 10(5) helium and antihelium candidates are identified with negligible background contamination. The helium identification efficiency is estimated to be approximately 50% with a corresponding background rejection rate of up to O(10(12)). These results demonstrate the feasibility of a rich programme of measurements of QCD and astrophysics interest involving light nuclei.
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Rebel, B., Hall, C., Bernard, E., Faham, C. H., Ito, T. M., Lundberg, B., et al. (2014). High voltage in noble liquids for high energy physics. J. Instrum., 9, T08004–57pp.
Abstract: A workshop was held at Fermilab November 8-9, 2013 to discuss the challenges of using high voltage in noble liquids. The participants spanned the fields of neutrino, dark matter, and electric dipole moment physics. All presentations at the workshop were made in plenary sessions. This document summarizes the experiences and lessons learned from experiments in these fields at developing high voltage systems in noble liquids.
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NEXT Collaboration(Rogers, L. et al), Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., Carrion, J. V., et al. (2018). High voltage insulation and gas absorption of polymers in high pressure argon and xenon gases. J. Instrum., 13, P10002–19pp.
Abstract: High pressure gas time projection chambers (HPGTPCs) are made with a variety of materials, many of which still await proper characterization in high pressure noble gas environments. As HPGTPCs increase in size toward ton-scale detectors, assemblies become larger and more complex, creating a need for detailed understanding of how structural supports and high voltage insulators behave. This includes identification of materials with predictable mechanical properties and without surface charge accumulation that may lead to field deformation or sparking. This paper explores the mechanical and electrical effects of high pressure gas environments on insulating polymers PTFE, HDPE, PEEK, POM and UHMW in argon and xenon, including studying gas absorption, swelling and high voltage insulation strength.
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DUNE Collaboration(Abud, A. A. et al), Amedo, P., Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., et al. (2023). Highly-parallelized simulation of a pixelated LArTPC on a GPU. J. Instrum., 18(4), P04034–35pp.
Abstract: The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype.
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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2015). Identification of beauty and charm quark jets at LHCb. J. Instrum., 10, P06013–29pp.
Abstract: Identification of jets originating from beauty and charm quarks is important for measuring Standard Model processes and for searching for new physics. The performance of algorithms developed to select b- and c-quark jets is measured using data recorded by LHCb from proton-proton collisions at root s = 7TeV in 2011 and at root s = 8TeV in 2012. The efficiency for identifying a b (c) jet is about 65%(25%) with a probability for misidentifying a light-parton jet of 0.3% for jets with transverse momentum pT > 20GeV and pseudorapidity 2 : 2 < eta < 4.2. The dependence of the performance on the pT and eta of the jet is also measured.
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Identification of charm jets at LHCb. J. Instrum., 17(2), P02028–23pp.
Abstract: The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement.
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Renner, J., Cervera-Villanueva, A., Hernando, J. A., Izmaylov, A., Monrabal, F., Muñoz, J., et al. (2015). Improved background rejection in neutrinoless double beta decay experiments using a magnetic field in a high pressure xenon TPC. J. Instrum., 10, P12020–19pp.
Abstract: We demonstrate that the application of an external magnetic field could lead to an improved background rejection in neutrinoless double-beta (0 nu beta beta) decay experiments using a high-pressure xenon (HPXe) TPC. HPXe chambers are capable of imaging electron tracks, a feature that enhances the separation between signal events (the two electrons emitted in the 0 nu beta beta decay of Xe-136) and background events, arising chiefly from single electrons of kinetic energy compatible with the end-point of the 0 nu beta beta decay (Q(beta beta)). Applying an external magnetic field of sufficiently high intensity (in the range of 0.5-1 Tesla for operating pressures in the range of 5-15 atmospheres) causes the electrons to produce helical tracks. Assuming the tracks can be properly reconstructed, the sign of the curvature can be determined at several points along these tracks, and such information can be used to separate signal (0 nu beta beta) events containing two electrons producing a track with two different directions of curvature from background (single-electron) events producing a track that should spiral in a single direction. Due to electron multiple scattering, this strategy is not perfectly efficient on an event-by-event basis, but a statistical estimator can be constructed which can be used to reject background events by one order of magnitude at a moderate cost (about 30%) in signal efficiency. Combining this estimator with the excellent energy resolution and topological signature identification characteristic of the HPXe TPC, it is possible to reach a background rate of less than one count per ton-year of exposure. Such a low background rate is an essential feature of the next generation of 0 nu beta beta experiments, aiming to fully explore the inverse hierarchy of neutrino masses.
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