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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). Deep-sea deployment of the KM3NeT neutrino telescope detection units by self-unrolling. J. Instrum., 15(11), P11027–18pp.
Abstract: KM3NeT is a research infrastructure being installed in the deep Mediterranean Sea. It will house a neutrino telescope comprising hundreds of networked moorings – detection units or strings – equipped with optical instrumentation to detect the Cherenkov radiation generated by charged particles from neutrino-induced collisions in its vicinity. In comparison to moorings typically used for oceanography, several key features of the KM3NeT string are different: the instrumentation is contained in transparent and thus unprotected glass spheres; two thin Dyneema (R) ropes are used as strength members; and a thin delicate backbone tube with fibre-optics and copper wires for data and power transmission, respectively, runs along the full length of the mooring. Also, compared to other neutrino telescopes such as ANTARES in the Mediterranean Sea and GVD in Lake Baikal, the KM3NeT strings are more slender to minimise the amount of material used for support of the optical sensors. Moreover, the rate of deploying a large number of strings in a period of a few years is unprecedented. For all these reasons, for the installation of the KM3NeT strings, a custom-made, fast deployment method was designed. Despite the length of several hundreds of metres, the slim design of the string allows it to be compacted into a small, re-usable spherical launching vehicle instead of deploying the mooring weight down from a surface vessel. After being lowered to the seafloor, the string unfurls to its full length with the buoyant launching vehicle rolling along the two ropes. The design of the vehicle, the loading with a string, and its underwater self-unrolling are detailed in this paper.
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Loya Villalpando, A. A., Martin-Albo, J., Chen, W. T., Guenette, R., Lego, C., Park, J. S., et al. (2020). Improving the light collection efficiency of silicon photomultipliers through the use of metalenses. J. Instrum., 15(11), P11021–13pp.
Abstract: Metalenses are optical devices that implement nanostructures as phase shifters to focus incident light. Their compactness and simple fabrication make them a potential cost-effective solution for increasing light collection efficiency in particle detectors with limited photosensitive area coverage. Here we report on the characterization and performance of metalenses in increasing the light collection efficiency of silicon photomultipliers (SiPM) of various sizes using an LED of 630 nm, and find a six to seven-fold increase in signal for a 1.3 x 1 3 mm(2) SiPM when coupled with a 10-mm-diameter metalens manufactured using deep ultraviolet stepper lithography. Such improvements could be valuable for future generations of particle detectors, particularly those employed in rare-event searches such as dark matter and neutrinoless double beta decay.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2020). Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger. J. Instrum., 15(11), P11016–48pp.
Abstract: The PreProcessor of the ATLAS Level-1 Calorimeter Trigger prepares the analogue trigger signals sent from the ATLAS calorimeters by digitising, synchronising, and calibrating them to reconstruct transverse energy deposits, which are then used in further processing to identify event features. During the first long shutdown of the LHC from 2013 to 2014, the central components of the PreProcessor, the Multichip Modules, were replaced by upgraded versions that feature modern ADC and FPGA technology to ensure optimal performance in the high pile-up environment of LHC Run 2. This paper describes the features of the new Multichip Modules along with the improvements to the signal processing achieved.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). Event reconstruction for KM3NeT/ORCA using convolutional neural networks. J. Instrum., 15(10), P10005–39pp.
Abstract: The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2020). Operation of the ATLAS trigger system in Run 2. J. Instrum., 15(10), P10004–59pp.
Abstract: The ATLAS experiment at the Large Hadron Collider employs a two-level trigger system to record data at an average rate of 1 kHz from physics collisions, starting from an initial bunch crossing rate of 40 MHz. During the LHC Run 2 (2015-2018), the ATLAS trigger system operated successfully with excellent performance and flexibility by adapting to the various run conditions encountered and has been vital for the ATLAS Run-2 physics programme For proton-proton running, approximately 1500 individual event selections were included in a trigger menu which specified the physics signatures and selection algorithms used for the data-taking, and the allocated event rate and bandwidth. The trigger menu must reflect the physics goals for a given data collection period, taking into account the instantaneous luminosity of the LHC and limitations from the ATLAS detector readout, online processing farm, and offline storage. This document discusses the operation of the ATLAS trigger system during the nominal proton-proton data collection in Run 2 with examples of special data-taking runs. Aspects of software validation, evolution of the trigger selection algorithms during Run 2, monitoring of the trigger system and data quality as well as trigger configuration are presented.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2020). Performance of the ATLAS muon triggers in Run 2. J. Instrum., 15(9), P09015–57pp.
Abstract: The performance of the ATLAS muon trigger system is evaluated with proton-proton (pp) and heavy-ion (HI) collision data collected in Run 2 during 2015-2018 at the Large Hadron Collider. It is primarily evaluated using events containing a pair of muons from the decay of Z bosons to cover the intermediate momentum range between 26 GeV and 100 GeV. Overall, the efficiency of the single-muon triggers is about 68% in the barrel region and 85% in the endcap region. The p(T) range for efficiency determination is extended by using muons from decays of J/psi mesons, W bosons, and top quarks. The performance in HI collision data is measured and shows good agreement with the results obtained in pp collisions. The muon trigger shows uniform and stable performance in good agreement with the prediction of a detailed simulation. Dedicated multi-muon triggers with kinematic selections provide the backbone to beauty, quarkonia, and low-mass physics studies. The design, evolution and performance of these triggers are discussed in detail.
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Poley, L. et al, Bernabeu, J., Civera, J. V., Lacasta, C., Leon, P., Platero, A., et al. (2020). The ABC130 barrel module prototyping programme for the ATLAS strip tracker. J. Instrum., 15(9), P09004–78pp.
Abstract: For the Phase-II Upgrade of the ATLAS Detector [1], its Inner Detector, consisting of silicon pixel, silicon strip and transition radiation sub-detectors, will be replaced with an all new 100% silicon tracker, composed of a pixel tracker at inner radii and a strip tracker at outer radii. The future ATLAS strip tracker will include 11,000 silicon sensor modules in the central region (barrel) and 7,000 modules in the forward region (end-caps), which are foreseen to be constructed over a period of 3.5 years. The construction of each module consists of a series of assembly and quality control steps, which were engineered to be identical for all production sites. In order to develop the tooling and procedures for assembly and testing of these modules, two series of major prototyping programs were conducted: an early program using readout chips designed using a 250 nm fabrication process (ABCN-250) [2, 3] and a subsequent program using a follow-up chip set made using 130 nm processing (ABC130 and HCC130 chips). This second generation of readout chips was used for an extensive prototyping program that produced around 100 barrel-type modules and contributed significantly to the development of the final module layout. This paper gives an overview of the components used in ABC130 barrel modules, their assembly procedure and findings resulting from their tests.
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NEXT Collaboration(Woodruff, K. et al), Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., et al. (2020). Radio frequency and DC high voltage breakdown of high pressure helium, argon, and xenon. J. Instrum., 15(4), P04022–15pp.
Abstract: Motivated by the possibility of guiding daughter ions from double beta decay events to single-ion sensors for barium tagging, the NEXT collaboration is developing a program of R&D to test radio frequency (RF) carpets for ion transport in high pressure xenon gas. This would require carpet functionality in regimes at higher pressures than have been previously reported, implying correspondingly larger electrode voltages than in existing systems. This mode of operation appears plausible for contemporary RF-carpet geometries due to the higher predicted breakdown strength of high pressure xenon relative to low pressure helium, the working medium in most existing RF carpet devices. In this paper we present the first measurements of the high voltage dielectric strength of xenon gas at high pressure and at the relevant RF frequencies for ion transport (in the 10MHz range), as well as new DC and RF measurements of the dielectric strengths of high pressure argon and helium gases at small gap sizes. We find breakdown voltages that are compatible with stable RF carpet operation given the gas, pressure, voltage, materials and geometry of interest.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., Castillo, F. L., et al. (2020). ATLAS data quality operations and performance for 2015-2018 data-taking. J. Instrum., 15(4), P04003–43pp.
Abstract: The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately 100 kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015-2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at root s = 13 TeV certified for physics analysis.
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Ahlburg, P. et al, & Marinas, C. (2020). EUDAQ – a data acquisition software framework for common beam telescopes. J. Instrum., 15(1), P01038–30pp.
Abstract: EUDAQ is a generic data acquisition software developed for use in conjunction with common beam telescopes at charged particle beam lines. Providing high-precision reference tracks for performance studies of new sensors, beam telescopes are essential for the research and development towards future detectors for high-energy physics. As beam time is a highly limited resource, EUDAQ has been designed with reliability and ease-of-use in mind. It enables flexible integration of different independent devices under test via their specific data acquisition systems into a top-level framework. EUDAQ controls all components globally, handles the data flow centrally and synchronises and records the data streams. Over the past decade, EUDAQ has been deployed as part of a wide range of successful test beam campaigns and detector development applications.
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