https://doi.org/10.1140/epjs/s11734-024-01238-8
Review
How deep learning is complementing deep thinking in ATLAS
1
School of Physics, University of Witwatersrand, Johannesburg, South Africa
2
Royal Society Wolfson Visiting Fellow at the University of Glasgow, Glasgow, UK
Received:
25
March
2024
Accepted:
28
June
2024
Published online:
5
July
2024
ATLAS collaboration uses machine learning (ML) algorithms in many different ways in its physics programme, starting from object reconstruction, simulation of calorimeter showers, signal to background discrimination in searches and measurements, tagging jets based on their origin and so on. Anomaly detection (AD) techniques are also gaining popularity where they are used to find hidden patterns in the data, with lesser dependence on simulated samples as in the case of supervised learning-based methods. ML methods used in detector simulation and in jet tagging in ATLAS will be discussed, along with four searches using ML/AD techniques.
© The Author(s) 2024
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