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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...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1016/j.revip.2021.100063 http://cds.cern.ch/record/2791315 |
| _version_ | 1780972300482379776 |
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| author | 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 Jiménez Morales, Fabricio 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 |
| author_facet | 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 Jiménez Morales, Fabricio 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 |
| author_sort | Stakia, Anna |
| collection | CERN |
| description | 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. |
| id | cern-2791315 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2021 |
| record_format | invenio |
| spelling | cern-27913152023-01-31T10:16:07Zdoi:10.1016/j.revip.2021.100063http://cds.cern.ch/record/2791315engStakia, AnnaDorigo, TommasoBanelli, GiovanniBortoletto, DanielaCasa, Alessandrode Castro, PabloDelaere, ChristopheDonini, JulienFinos, LivioGallinaro, MicheleGiammanco, AndreaHeld, AlexanderJiménez Morales, FabricioKotkowski, GrzegorzLiew, Seng PeiMaltoni, FabioMenardi, GiovannaPapavergou, IoannaSaggio, AlessiaScarpa, BrunoStrong, Giles C.Tosciri, CeciliaVarela, JoãoVischia, PietroWeiler, AndreasAdvances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Colliderphysics.data-anOther Fields of Physicshep-phParticle Physics - Phenomenologycs.LGComputing and Computershep-exParticle Physics - ExperimentBetween 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.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.arXiv:2105.07530oai:cds.cern.ch:27913152021-05-16 |
| spellingShingle | physics.data-an Other Fields of Physics hep-ph Particle Physics - Phenomenology cs.LG Computing and Computers hep-ex Particle Physics - Experiment 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 Jiménez Morales, Fabricio 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 Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider |
| title | Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider |
| title_full | Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider |
| title_fullStr | Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider |
| title_full_unstemmed | Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider |
| title_short | Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider |
| title_sort | advances in multi-variate analysis methods for new physics searches at the large hadron collider |
| topic | physics.data-an Other Fields of Physics hep-ph Particle Physics - Phenomenology cs.LG Computing and Computers hep-ex Particle Physics - Experiment |
| url | https://dx.doi.org/10.1016/j.revip.2021.100063 http://cds.cern.ch/record/2791315 |
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