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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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Cervello, A., Carrio, F., Garcia, R., Martos, J., Soret, J., Torres, J., et al. (2022). The TileCal PreProcessor interface with the ATLAS global data acquisition system at the HL-LHC. Nucl. Instrum. Methods Phys. Res. A, 1043, 167492–2pp.
Abstract: The Large Hadron Collider (LHC) has envisaged a series of upgrades towards a High Luminosity LHC (HL-LHC) delivering five times the LHC nominal instantaneous luminosity. It will take place throughout 2026-2028, corresponding to the Long Shutdown 3. During this upgrade, the ATLAS Tile Hadronic Calorimeter (TileCal) will replace completely on-and off-detector electronics adopting a new read-out architecture. Signals captured from TileCal are digitized by the on-detector electronics and transmitted to the TileCal PreProcessor (TilePPr) located off-detector, which provides the interface with the ATLAS trigger and data acquisition systems.TilePPr receives, process and transmits the data from the on-detector system and transmits it to the Front -End Link eXchange (FELIX) system. FELIX is the ATLAS common hardware in all the subdetectors designed to act as a data router, receiving and forwarding data to the SoftWare Read-Out Driver (SWROD) computers. FELIX also distributes the Timing, Trigger and Control (TTC) signals to the TilePPr to be propagated to the on-detector electronics. The SWROD is an ATLAS common software solution to perform detector specific data processing, including configuration, calibration, control and monitoring of the partitionIn this contribution we will introduce the new read-out elements for TileCal at the HL-LHC, the intercon-nection between the off-detector electronics and the FELIX system, the configuration and implementation for the test beam campaigns, as well as future developments of the preprocessing and monitoring status of the calorimeter modules through the SWROD infrastructure.
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Goasduff, A. et al, & Gadea, A. (2021). The GALILEO gamma-ray array at the Legnaro National Laboratories. Nucl. Instrum. Methods Phys. Res. A, 1015, 165753–15pp.
Abstract: GALILEO, a new 4 pi high-resolution gamma-detection array, based on HPGe detectors, has been developed and installed at the Legnaro National Laboratories. The GALILEO array greatly benefits from a fully-digital readout chain, customized DAQ, and a variety of complementary detectors to improve the resolving power by the detection of particles, ions or high-energy gamma-ray transitions. In this work, a full description of the array, including electronics and DAQ, is presented together with its complementary instrumentation.
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PreSPEC and AGATA Collaborations(Ralet, D. et al), & Gadea, A. (2015). Data-flow coupling and data-acquisition triggers for the PreSPEC-AGATA campaign at GSI. Nucl. Instrum. Methods Phys. Res. A, 786, 32–39.
Abstract: The PreSPEC setup for high-resolution 'gamma-ray spectroscopy using radioactive ion beams was employed for experimental campaigns in 2012 and 2014. The setup consisted of the state of the art Advanced GAmma Tracking Array (AGATA) and the High Energy gamma cleteCTOR (HECTOR+) positioned around a secondary target at the final focal plane of the GSI FRagment Separator (FRS) to perform in-beam gamma-ray spectroscopy of exotic nuclei. The Lund York Cologne CAlorimeter (LYCCA) was used to identify the reaction products. In this paper we report on the trigger scheme used during the campaigns. The dataflow coupling between the Multi-Branch System (MBS) based Data AcQuisition (DAQ) used for FRS-LYCCA and the “Nouvelle Acquisition temps Reel Version 1.2 Avec Linux” (NARVAL) based acquisition system used for AGATA are also described.
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Punzi, G., Baldini, W., Bassi, G., Contu, A., Fantechi, R., He, J. B., et al. (2024). Detector-embedded reconstruction of complex primitives using FPGAs. Nucl. Instrum. Methods Phys. Res. A, 1069, 169782–4pp.
Abstract: The slowdown of Moore's law and the growing requirements of future HEP experiments with ever-increasing data rates pose important computational challenges for data reconstruction and trigger systems, encouraging the exploration of new computing methodologies. In this work we discuss a FPGA-based tracking system, relying on a massively parallel pattern recognition approach, inspired by the processing of visual images by the natural brain (“retina architecture”). This method allows a large efficiency of utilisation of the hardware, low power consumption and very low latencies. Based on this approach, a device has been designed within the LHCb Upgrade-II project, with the goal of performing track reconstruction in the forward acceptance region in real-time during the upcoming Run 4 of the LHC. This innovative device will perform track reconstruction before the event-building, in a short enough time to provide pre-reconstructed tracks (“primitives”) transparently to the processor farm, as if they had been generated directly by the detector. This allows significant savings in higher-level computing resources, enabling handling higher luminosities than otherwise possible. The feasibility of the project is backed up by the results of tests performed on a realistic hardware prototype, that has been opportunistically processing actual LHCb data in parallel with the regular DAQ in the LHC Run 3.
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