|
|
Gololo, M. G. D., Carrio Argos, F., & Mellado, B. (2022). Tile Computer-on-Module for the ATLAS Tile Calorimeter Phase-II upgrades. J. Instrum., 17(6), P06020–14pp.
Abstract: The Tile PreProcessor (TilePPr) is the core element of the Tile Calorimeter (TileCal) off-detector electronics for High-luminosity Large Hadron Collider (HL-LHC). The TilePPr comprises FPGA-based boards to operate and read out the TileCal on-detector electronics. The Tile Computer on Module (TileCoM) mezzanine is embedded within TilePPr to carry out three main functionalities. These include remote configuration of on-detector electronics and TilePPr FPGAs, interface the TilePPr with the ATLAS Trigger and Data Acquisition (TDAQ) system, and interfacing the TilePPr with the ATLAS Detector Control System (DCS) by providing monitoring data. The TileCoM is a 10-layer board with a Zynq UltraScale+ ZU2CG for processing data, interface components to integrate with TilePPr and the power supply to be connected to the Advanced Telecommunication Computing Architecture carrier. A CentOS embedded Linux is deployed on the TileCoM to implement the required functionalities for the HL-LHC. In this paper we present the hardware and firmware developments of the TileCoM system in terms of remote programming, interface with ATLAS TDAQ system and DCS system.
|
|
|
|
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.
|
|
|
|
ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fassi, F., Ferrer, A., et al. (2013). Characterisation and mitigation of beam-induced backgrounds observed in the ATLAS detector during the 2011 proton-proton run. J. Instrum., 8, P07004–72pp.
Abstract: This paper presents a summary of beam-induced backgrounds observed in the ATLAS detector and discusses methods to tag and remove background contaminated events in data. Trigger-rate based monitoring of beam-related backgrounds is presented. The correlations of backgrounds with machine conditions, such as residual pressure in the beam-pipe, are discussed. Results from dedicated beam-background simulations are shown, and their qualitative agreement with data is evaluated. Data taken during the passage of unpaired, i.e. non-colliding, proton bunches is used to obtain background-enriched data samples. These are used to identify characteristic features of beam-induced backgrounds, which then are exploited to develop dedicated background tagging tools. These tools, based on observables in the Pixel detector, the muon spectrometer and the calorimeters, are described in detail and their efficiencies are evaluated. Finally an example of an application of these techniques to a monojet analysis is given, which demonstrates the importance of such event cleaning techniques for some new physics searches.
|
|
|
|
Poley, L. et al, & Lacasta, C. (2017). Investigations into the impact of locally modified sensor architectures on the detection efficiency of silicon micro-strip sensors. J. Instrum., 12, P07006–17pp.
Abstract: The High Luminosity Upgrade of the LHC will require the replacement of the Inner Detector of ATLAS with the Inner Tracker (ITk) in order to cope with higher radiation levels and higher track densities. Prototype silicon strip detector modules are currently developed and their performance is studied in both particle test beams and X-ray beams. In previous test beam measurements of prototype modules, the response of silicon sensors has been studied in detailed scans across individual sensor strips. These scans found instances of sensor strips collecting charge across areas on the sensor deviating from the geometrical width of a sensor strip. The variations have been linked to local features of the sensor architecture. This paper presents results of detailed sensor measurements in both X-ray and particle beams investigating the impact of sensor features (metal pads and p-stops) on the sensor strip response.
|
|
|
|
ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo Gimenez, V., et al. (2021). The ATLAS Fast TracKer system. J. Instrum., 16(7), P07006–61pp.
Abstract: The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited eta-phi region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.
|
|
