Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC

The High Luminosity era of the Large Hadron Collider (LHC) starting in 2029 promises exciting discovery potential, giving unprecedented sensitivity to key new physics models and precise characterization of the Higgs boson. In order to maintain current performance in this challenging environment, the...

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Main Authors: Julia Gonski, on behalf of the ATLAS Liquid Argon Calorimeter Group
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Instruments
Subjects:
Online Access:https://www.mdpi.com/2410-390X/6/3/28
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author Julia Gonski
on behalf of the ATLAS Liquid Argon Calorimeter Group
author_facet Julia Gonski
on behalf of the ATLAS Liquid Argon Calorimeter Group
author_sort Julia Gonski
collection DOAJ
description The High Luminosity era of the Large Hadron Collider (LHC) starting in 2029 promises exciting discovery potential, giving unprecedented sensitivity to key new physics models and precise characterization of the Higgs boson. In order to maintain current performance in this challenging environment, the ATLAS liquid argon electromagnetic calorimeter will get entirely new electronics that reads out the entire detector with full precision at the LHC frequency of 40 MHz, and provides high granularity trigger information, while withstanding high operational radiation doses. New results will be presented from both front-end and off-detector component development, along with highlights from machine learning applications. The future steps and outlook of the project will be discussed, with an eye towards installation in the ATLAS cavern beginning in 2026.
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spelling doaj.art-7c788ee11399405db3bcf5767ccf05882023-11-23T16:56:00ZengMDPI AGInstruments2410-390X2022-08-01632810.3390/instruments6030028Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHCJulia Gonski0on behalf of the ATLAS Liquid Argon Calorimeter Group1Nevis Laboratories, Columbia University, Irvington, NY 10533, USANevis Laboratories, Columbia University, Irvington, NY 10533, USAThe High Luminosity era of the Large Hadron Collider (LHC) starting in 2029 promises exciting discovery potential, giving unprecedented sensitivity to key new physics models and precise characterization of the Higgs boson. In order to maintain current performance in this challenging environment, the ATLAS liquid argon electromagnetic calorimeter will get entirely new electronics that reads out the entire detector with full precision at the LHC frequency of 40 MHz, and provides high granularity trigger information, while withstanding high operational radiation doses. New results will be presented from both front-end and off-detector component development, along with highlights from machine learning applications. The future steps and outlook of the project will be discussed, with an eye towards installation in the ATLAS cavern beginning in 2026.https://www.mdpi.com/2410-390X/6/3/28ATLASLArupgradecalorimeterreadoutelectronics
spellingShingle Julia Gonski
on behalf of the ATLAS Liquid Argon Calorimeter Group
Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC
Instruments
ATLAS
LAr
upgrade
calorimeter
readout
electronics
title Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC
title_full Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC
title_fullStr Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC
title_full_unstemmed Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC
title_short Development of the ATLAS Liquid Argon Calorimeter Readout Electronics and Machine Learning for the HL-LHC
title_sort development of the atlas liquid argon calorimeter readout electronics and machine learning for the hl lhc
topic ATLAS
LAr
upgrade
calorimeter
readout
electronics
url https://www.mdpi.com/2410-390X/6/3/28
work_keys_str_mv AT juliagonski developmentoftheatlasliquidargoncalorimeterreadoutelectronicsandmachinelearningforthehllhc
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