Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider

Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named “AMVA4NewPhysics” studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely ne...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Rev.Phys 2021-12, Vol.7, p.100063, Article 100063
Hauptverfasser: Stakia, Anna, Dorigo, Tommaso, Banelli, Giovanni, Bortoletto, Daniela, Casa, Alessandro, de Castro, Pablo, Delaere, Christophe, Donini, Julien, Finos, Livio, Gallinaro, Michele, Giammanco, Andrea, Held, Alexander, Morales, Fabricio Jiménez, Kotkowski, Grzegorz, Liew, Seng Pei, Maltoni, Fabio, Menardi, Giovanna, Papavergou, Ioanna, Saggio, Alessia, Scarpa, Bruno, Strong, Giles C., Tosciri, Cecilia, Varela, João, Vischia, Pietro, Weiler, Andreas
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named “AMVA4NewPhysics” studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented along with the evaluation of their performances.
ISSN:2405-4283
2405-4283
DOI:10.1016/j.revip.2021.100063