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Perspective on machine learning for real-time analysis at the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb

The field of high energy physics (HEPs) has seen a marked increase in the use of machine learning (ML) techniques in recent years. The proliferation of applications has revolutionised many aspects of the data processing pipeline at collider experiments including the Large Hadron Collider (LHC). In t...

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Principais autores: S Astrand, L Boggia, M Borsato, L Bozianu, C E Cocha Toapaxi, F I Giasemis, J Hansen, P Inkaew, K E Iversen, P Jawahar, H Pineiro Monteagudo, M Olocco, S Schramm
Format: Artigo
Sprog:Inglês
Udgivet: IOP Publishing 2026-01-01
Serier:Machine Learning: Science and Technology
Fag:
machine learning
real-time analysis
LHC experiments
Online adgang:https://doi.org/10.1088/2632-2153/ae35cc
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