Machine learning in top quark physics at ATLAS and CMS
Abstract
This note presents an overview of current and potential future applications of machine-learning-based techniques in the study of the top quark. The research community has developed a diverse set of ideas and tools, including algorithms for the efficient reconstruction of recorded collision events and innovative methods for statistical inference. Recent applications of some techniques by the ATLAS and CMS collaborations are also highlighted.
Fields of Study & Subjects
Particle physics theoretical and experimental studies
Particle Detector Development and Performance
High-Energy Particle Collisions Research
Publication details
- Journal / source
- SciPost Physics Proceedings
- Issue
- 18
- Publication date
- 29 January 2026
- Language
- EN