|
|
Ahlburg, P. et al, & Marinas, C. (2020). EUDAQ – a data acquisition software framework for common beam telescopes. J. Instrum., 15(1), P01038–30pp.
Abstract: EUDAQ is a generic data acquisition software developed for use in conjunction with common beam telescopes at charged particle beam lines. Providing high-precision reference tracks for performance studies of new sensors, beam telescopes are essential for the research and development towards future detectors for high-energy physics. As beam time is a highly limited resource, EUDAQ has been designed with reliability and ease-of-use in mind. It enables flexible integration of different independent devices under test via their specific data acquisition systems into a top-level framework. EUDAQ controls all components globally, handles the data flow centrally and synchronises and records the data streams. Over the past decade, EUDAQ has been deployed as part of a wide range of successful test beam campaigns and detector development applications.
|
|
|
|
ANTARES Collaboration(Adrian-Martinez, S. et al), Aguilar, J. A., Bigongiari, C., Dornic, D., Emanuele, U., Gomez-Gonzalez, J. P., et al. (2012). The positioning system of the ANTARES Neutrino Telescope. J. Instrum., 7, T08002–20pp.
Abstract: The ANTARES neutrino telescope, located 40km off the coast of Toulon in the Mediterranean Sea at a mooring depth of about 2475m, consists of twelve detection lines equipped typically with 25 storeys. Every storey carries three optical modules that detect Cherenkov light induced by charged secondary particles (typically muons) coming from neutrino interactions. As these lines are flexible structures fixed to the sea bed and held taut by a buoy, sea currents cause the lines to move and the storeys to rotate. The knowledge of the position of the optical modules with a precision better than 10cm is essential for a good reconstruction of particle tracks. In this paper the ANTARES positioning system is described. It consists of an acoustic positioning system, for distance triangulation, and a compass-tiltmeter system, for the measurement of the orientation and inclination of the storeys. Necessary corrections are discussed and the results of the detector alignment procedure are described.
Keywords: Timing detectors; Detector modelling and simulations II (electric fields, charge transport, multiplication and induction, pulse formation, electron emission, etc); Detector alignment and calibration methods (lasers, sources, particle-beams); Detector control systems (detector and experiment monitoring and slow-control systems, architecture, hardware, algorithms, databases)
|
|
|
|
ATLAS Collaboration(Aad, G. et al), Aikot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2024). The ATLAS trigger system for LHC Run 3 and trigger performance in 2022. J. Instrum., 19(6), P06029–110pp.
Abstract: The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022-2025).
|
|
|
|
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%.
|
|
|
|
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.
|
|
