Cargando…
Track reconstruction performance optimization using machine learning for the upgrade of the ALICE experiment
With the preparation of the future ALICE3 detector planned for the LHC Run 5 and 6, the use of new reconstruction algorithms, more adapted to its new geometry and more efficient, is needed. This project is about optimizing the performances for the charged particle track reconstruction in high-multip...
Autor principal: | Chalumeau, Anaelle |
---|---|
Lenguaje: | eng |
Publicado: |
2023
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2875212 |
Ejemplares similares
-
Upgrade of the ALICE inner tracking system: Construction and commissioning
por: Fantoni, Alessandra
Publicado: (2020) -
Perspectives of the ALICE Experiment and Detector Upgrade
por: Garcia-Solis, Edmundo
Publicado: (2015) -
Full kinematic reconstruction of charged B mesons with the upgraded Inner Tracking System of the ALICE Experiment
por: Stiller, Johannes Hendrik
Publicado: (2016) -
Machine learning and parallelism in the reconstruction of LHCb and its upgrade
por: De Cian, Michel
Publicado: (2016) -
The Upgrade of the ALICE Inner Tracking System
por: Terrevoli, Cristina
Publicado: (2012)