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.
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ATLAS Collaboration(Aad, G. et al), Akiot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2023). Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3. J. Instrum., 18(11), P11006–38pp.
Abstract: The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH -> b (b) over barb (b) over bar, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%.
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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., Cardillo, F., Castillo, F. L., et al. (2021). Performance of the ATLAS RPC detector and Level-1 muon barrel trigger at root s=13 TeV. J. Instrum., 16(7), P07029–64pp.
Abstract: The ATLAS experiment at the Large Hadron Collider (LHC) employs a trigger system consisting of a first-level hardware trigger (L1) and a software-based high-level trigger. The L1 muon trigger system selects muon candidates, assigns them to the correct LHC bunch crossing and classifies them into one of six transverse-momentum threshold classes. The L1 muon trigger system uses resistive-plate chambers (RPCs) to generate the muon-induced trigger signals in the central (barrel) region of the ATLAS detector. The ATLAS RPCs are arranged in six concentric layers and operate in a toroidal magnetic field with a bending power of 1.5 to 5.5 Tm. The RPC detector consists of about 3700 gas volumes with a total surface area of more than 4000 m(2). This paper reports on the performance of the RPC detector and L1 muon barrel trigger using 60.8 fb(-1) of proton-proton collision data recorded by the ATLAS experiment in 2018 at a centre-of-mass energy of 13 TeV. Detector and trigger performance are studied using Z boson decays into a muon pair. Measurements of the RPC detector response, efficiency, and time resolution are reported. Measurements of the L1 muon barrel trigger efficiencies and rates are presented, along with measurements of the properties of the selected sample of muon candidates. Measurements of the RPC currents, counting rates and mean avalanche charge are performed using zero-bias collisions. Finally, RPC detector response and efficiency are studied at different high voltage and front-end discriminator threshold settings in order to extrapolate detector response to the higher luminosity expected for the High Luminosity LHC.
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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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