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Agaras, M. N. et al, & Fiorini, L. (2023). Laser calibration of the ATLAS Tile Calorimeter during LHC Run 2. J. Instrum., 18(6), P06023–35pp.
Abstract: This article reports the laser calibration of the hadronic Tile Calorimeter of the ATLAS experiment in the LHC Run 2 data campaign. The upgraded Laser II calibration system is described. The system was commissioned during the first LHC Long Shutdown, exhibiting a stability better than 0.8% for the laser light monitoring. The methods employed to derive the detector calibration factors with data from the laser calibration runs are also detailed. These allowed to correct for the response fluctuations of the 9852 photomultiplier tubes of the Tile Calorimeter with a total uncertainty of 0.5% plus a luminosity-dependent sub-dominant term. Finally, we report the regular monitoring and performance studies using laser events in both standalone runs and during proton collisions. These studies include channel timing and quality inspection, and photomultiplier linearity and response dependence on anode current.
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ATLAS Tile Calorimeter Community(Abdallah, J. et al), Castillo Gimenez, V., Costelo, J., Ferrer, A., Fullana, E., Gonzalez, V., et al. (2013). The optical instrumentation of the ATLAS Tile Calorimeter. J. Instrum., 8, P01005–21pp.
Abstract: The Tile Calorimeter, covering the central region of the ATLAS experiment up to pseudorapidities of +/-1.7, is a sampling device built with scintillating tiles that alternate with iron plates. The light is collected in wave-length shifting (WLS) fibers and is read out with photomultipliers. In the characteristic geometry of this calorimeter the tiles lie in planes perpendicular to the beams, resulting in a very simple and modular mechanical and optical layout. This paper focuses on the procedures applied in the optical instrumentation of the calorimeter, which involved the assembly of about 460,000 scintillator tiles and 550,000 WLS fibers. The outcome is a hadronic calorimeter that meets the ATLAS performance requirements, as shown in this paper.
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CALICE Collaboration(White, A. et al), & Irles, A. (2023). Design, construction and commissioning of a technological prototype of a highly granular SiPM-on-tile scintillator-steel hadronic calorimeter. J. Instrum., 18(11), P11018–39pp.
Abstract: The CALICE collaboration is developing highly granular electromagnetic and hadronic calorimeters for detectors at future energy frontier electron-positron colliders. After successful tests of a physics prototype, a technological prototype of the Analog Hadron Calorimeter has been built, based on a design and construction techniques scalable to a collider detector. The prototype consists of a steel absorber structure and active layers of small scintillator tiles that are individually read out by directly coupled SiPMs. Each layer has an active area of 72 x 72 cm2 and a tile size of 3 x 3 cm2. With 38 active layers, the prototype has nearly 22, 000 readout channels, and its total thickness amounts to 4.4 nuclear interaction lengths. The dedicated readout electronics provide time stamping of each hit with an expected resolution of about 1 ns. The prototype was constructed in 2017 and commissioned in beam tests at DESY. It recorded muons, hadron showers and electron showers at different energies in test beams at CERN in 2018. In this paper, the design of the prototype, its construction and commissioning are described. The methods used to calibrate the detector are detailed, and the performance achieved in terms of uniformity and stability is presented.
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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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Olleros, P., Caballero, L., Domingo-Pardo, C., Babiano, V., Ladarescu, I., Calvo, D., et al. (2018). On the performance of large monolithic LaCl3(Ce) crystals coupled to pixelated silicon photosensors. J. Instrum., 13, P03014–17pp.
Abstract: We investigate the performance of large area radiation detectors, with high energy-and spatial-resolution, intended for the development of a Total Energy Detector with gamma-ray imaging capability, so-called i-TED. This new development aims for an enhancement in detection sensitivity in time-of-flight neutron capture measurements, versus the commonly used C6D6 liquid scintillation total-energy detectors. In this work, we study in detail the impact of the readout photosensor on the energy response of large area (50 x 50 mm(2)) monolithic LaCl3(Ce) crystals, in particular when replacing a conventional mono-cathode photomultiplier tube by an 8 x 8 pixelated silicon photomultiplier. Using the largest commercially available monolithic SiPM array (25 cm(2)), with a pixel size of 6 x 6 mm(2), we have measured an average energy resolution of 3.92% FWHM at 662 keV for crystal thick-nesses of 10, 20 and 30 mm. The results are confronted with detailed Monte Carlo (MC) calculations, where optical processes and properties have been included for the reliable tracking of the scintillation photons. After the experimental validation of the MC model, we use our MC code to explore the impact of a smaller photosensor segmentation on the energy resolution. Our optical MC simulations predict only a marginal deterioration of the spectroscopic performance for pixels of 3 x 3 mm(2).
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