Tesi etd-10012023-232628 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
MALUCCHI, MATTEO
URN
etd-10012023-232628
Titolo
Enhancing b-tagging for the analysis of the Higgs boson decay to bottom quarks with the CMS experiment
Dipartimento
FISICA
Corso di studi
FISICA
Relatori
relatore Rizzi, Andrea
Parole chiave
- hep
- cms
- lhc
- machine learning
- higgs
- b-tagging
Data inizio appello
23/10/2023
Consultabilità
Completa
Riassunto
The ability to accurately identify and classify heavy-flavour jets produced in high-energy particle collisions is crucial for many analyses in CMS. In this thesis we introduce the ParticleEdge network, a Graph Neural Network-based b-tagging algorithm that showcases superior performance compared to the previous-generation algorithms utilized in CMS. Moreover, additional research was undertaken to assess the implications of improved b-tagging techniques on the analysis of the Higgs boson decay to b-quarks.
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| Nome file | Dimensione |
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| Tesi_Malucchi.pdf | 19.79 Mb |
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