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Machine learning in online/offline calibration and reconstruction at the LHC

Year: 2024

Type: conference-paper

Abstract: These proceedings report on the status and use of machine learning algorithms and especially neural networks in online and offline reconstruction and calibration for the four major experiments at CERN. The paper provides an overview and specific examples, ranging from raw data readout to final offline calibrations.

Source: Large Hadron Collider Physics Conference (LHCP)

DOI: 10.22323/1.478.0151

Author: Christian Sonnabend

Language: English

Topic: Particle Detector Development and Performance

Subfield: Nuclear and High Energy Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4405950184

FWCI:

Cites: 4

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Related to: 10