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Carrio, F. (2022). The Data Acquisition System for the ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator. IEEE Trans. Nucl. Sci., 69(4), 687–695.
Abstract: The tile calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS experiment at the large hadron collider (LHC). In 2025, the LHC will be upgraded leading to the high luminosity LHC (HL-LHC). The HL-LHC will deliver an instantaneous luminosity up to seven times larger than the LHC nominal luminosity. The ATLAS Phase-II upgrade (2025-2027) will accommodate the subdetectors to the HL-LHC requirements. As part of this upgrade, the majority of the TileCal on-detector and off-detector electronics will be replaced using a new readout strategy, where the on-detector electronics will digitize and transmit digitized detector data to the off-detector electronics at the bunch crossing frequency (40 MHz). In the counting rooms, the off-detector electronics will compute reconstructed trigger objects for the first-level trigger and will store the digitized samples in pipelined buffers until the reception of a trigger acceptance signal. The off-detector electronics will also distribute the LHC clock to the on-detector electronics embedded within the digital data stream. The TileCal Phase-II upgrade project has undertaken an extensive research and development program that includes the development of a Demonstrator module to evaluate the performance of the new clock and readout architecture envisaged for the HL-LHC. The Demonstrator module equipped with the latest version of the on-detector electronics was built and inserted into the ATLAS experiment. The Demonstrator module is operated and read out using a Tile PreProcessor (TilePPr) Demonstrator which enables backward compatibility with the present ATLAS Trigger and Data AcQuisition (TDAQ), and the timing, trigger, and command (TTC) systems. This article describes in detail the main hardware and firmware components of the clock distribution and data acquisition systems for the Demonstrator module, focusing on the TilePPr Demonstrator.
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Briz, J. A., Nerio, A. N., Ballesteros, C., Borge, M. J. G., Martinez, P., Perea, A., et al. (2022). Proton Radiographs Using Position-Sensitive Silicon Detectors and High-Resolution Scintillators. IEEE Trans. Nucl. Sci., 69(4), 696–702.
Abstract: Proton therapy is a cancer treatment technique currently in growth since it offers advantages with respect to conventional X-ray and gamma-ray radiotherapy. In particular, better control of the dose deposition allowing to reach higher conformity in the treatments causing less secondary effects. However, in order to take full advantage of its potential, improvements in treatment planning and dose verification are required. A new prototype of proton computed tomography scanner is proposed to design more accurate and precise treatment plans for proton therapy. Our prototype is formed by double-sided silicon strip detectors and scintillators of LaBr3(Ce) with high energy resolution and fast response. Here, the results obtained from an experiment performed using a 100-MeV proton beam are presented. Proton radiographs of polymethyl methacrylate (PMMA) samples of 50-mm thickness with spatial patterns in aluminum were taken. Their properties were studied, including reproduction of the dimensions, spatial resolution, and sensitivity to different materials. Structures of up to 2 mm are well resolved and the sensitivity of the system was enough to distinguish the thicknesses of 10 mm of aluminum or PMMA. The spatial resolution of the images was 0.3 line pairs per mm (MTF-10%). This constitutes the first step to validate the device as a proton radiography scanner.
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Bonilla, J. et al, & Vos, M. (2022). Jets and Jet Substructure at Future Colliders. Front. Physics, 10, 897719–17pp.
Abstract: Even though jet substructure was not an original design consideration for the Large Hadron Collider (LHC) experiments, it has emerged as an essential tool for the current physics program. We examine the role of jet substructure on the motivation for and design of future energy Frontier colliders. In particular, we discuss the need for a vibrant theory and experimental research and development program to extend jet substructure physics into the new regimes probed by future colliders. Jet substructure has organically evolved with a close connection between theorists and experimentalists and has catalyzed exciting innovations in both communities. We expect such developments will play an important role in the future energy Frontier physics program.
Keywords: jets; jet substructure; collider; artificial intelligence; machine learning; snowmass; top quark; Higgs boson
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Figueroa, D. G., Raatikainen, S., Rasanen, S., & Tomberg, E. (2022). Implications of stochastic effects for primordial black hole production in ultra-slow-roll inflation. J. Cosmol. Astropart. Phys., 05(5), 027–48pp.
Abstract: We study the impact of stochastic noise on the generation of primordial black hole (PBH) seeds in ultra-slow-roll (USR) inflation with numerical simulations. We consider the non-linearity of the system by consistently taking into account the noise dependence on the inflaton perturbations, while evolving the perturbations on the coarse-grained background affected by the noise. We capture in this way the non-Markovian nature of the dynamics, and demonstrate that non-Markovian effects are subleading. Using the Delta N formalism, we find the probability distribution P(R) of the comoving curvature perturbation R. We consider inflationary potentials that fit the CMB and lead to PBH dark matter with i) asteroid, ii) solar, or iii) Planck mass, as well as iv) PBHs that form the seeds of supermassive black holes. We find that stochastic effects enhance the PBH abundance by a factor of O(10)-O(10(8)), depending on the PBH mass. We also show that the usual approximation, where stochastic kicks depend only on the Hubble rate, either underestimates or overestimates the abundance by orders of magnitude, depending on the potential. We evaluate the gauge dependence of the results, discuss the quantum-to-classical transition, and highlight open issues of the application of the stochastic formalism to USR inflation.
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HAWC Collaboration(Alfaro, R. et al), & Salesa Greus, F. (2022). Gamma/hadron separation with the HAWC observatory. Nucl. Instrum. Methods Phys. Res. A, 1039, 166984–13pp.
Abstract: The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (> 99.9%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.
Keywords: High energy; Crab Nebula; G/H separation; Machine Learning
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